refactor: split tts.py into per-backend packages

10 files changed, 909 insertions, 795 deletions

diff --git a/app/converter/audio.py b/app/converter/audio.py
index eb970ff..90ce5ca 100644
--- a/app/converter/audio.py
+++ b/app/converter/audio.py
@@ -1,4 +1,9 @@
-"""Audio assembly: combining chunks, speed adjustment, cleanup."""
+"""Audio assembly: combining chunks, speed adjustment, cleanup.
+
+Every function that touches the run's scratch audio takes its folder as an
+explicit CHUNKS_DIR argument — the converter owns the folder constants and
+threads them through, so there is no module-global path to mutate.
+"""
 
 import logging
 import re
@@ -13,8 +18,6 @@ from . import config
 
 logger = logging.getLogger(__name__)
 
-CHUNKS_FOLDER = Path(__file__).resolve().parent.parent.parent / "app" / "chunks"
-
 # Tolerance for "is this speed 1.0?" comparisons (banner display, atempo
 # filter elision); shared by every speed check.
 SPEED_EPSILON = 1e-6
@@ -362,6 +365,7 @@ def _collect_chunk_files(total_chunks: int,
 
 def combine_chunks(total_chunks: int, output_path: Path,
                    chunk_results: Dict[int, Optional[Path]],
+                   *, chunks_dir: Path,
                    speed: float = 1.0, output_format: str = config.AUDIO_FORMAT,
                    intermediate: bool = False,
                    meta: Optional[TrackMeta] = None,
@@ -369,14 +373,15 @@ def combine_chunks(total_chunks: int, output_path: Path,
     """Combine audio chunks into the final audiobook using ffmpeg's concat demuxer.
 
     ``chunk_results`` maps chunk numbers to the audio file each chunk produced
-    (None for failed chunks); failed and missing chunks are skipped. When
-    ``speed`` differs from 1.0, an additional speed-adjusted copy is written
-    next to the normal-speed file. ``meta``/``cover`` embed tags and cover
-    art into the output (skipped for intermediate chapter scratch audio).
-    Chunks are streamed by ffmpeg, so the whole book is never held in
-    memory. Set ``intermediate`` for scratch chapter audio on the way to a
-    larger output (e.g. a chaptered m4b) so save messages don't present it
-    as the final audiobook.
+    (None for failed chunks); failed and missing chunks are skipped. The
+    concat scratch list is written to ``chunks_dir``. When ``speed`` differs
+    from 1.0, an additional speed-adjusted copy is written next to the
+    normal-speed file. ``meta``/``cover`` embed tags and cover art into the
+    output (skipped for intermediate chapter scratch audio). Chunks are
+    streamed by ffmpeg, so the whole book is never held in memory. Set
+    ``intermediate`` for scratch chapter audio on the way to a larger output
+    (e.g. a chaptered m4b) so save messages don't present it as the final
+    audiobook.
     """
     if shutil.which("ffmpeg") is None or shutil.which("ffprobe") is None:
         logger.error("ffmpeg and ffprobe are required to combine audio chunks (install ffmpeg)")
@@ -391,7 +396,7 @@ def combine_chunks(total_chunks: int, output_path: Path,
     if missing_chunks:
         logger.warning("Missing chunks: %s", missing_chunks)
 
-    concat_list = CHUNKS_FOLDER / "_concat_list.txt"
+    concat_list = Path(chunks_dir) / "_concat_list.txt"
     try:
         with open(concat_list, "w", encoding="utf-8") as list_file:
             for chunk_file in chunk_files:
@@ -463,12 +468,12 @@ def combine_chunks(total_chunks: int, output_path: Path,
             pass
 
 
-def cleanup_chunks() -> None:
-    """Remove temporary chunk and chapter files from the scratch folder."""
+def cleanup_chunks(chunks_dir: Path) -> None:
+    """Remove temporary chunk and chapter files from the CHUNKS_DIR scratch folder."""
     try:
         chunk_count = 0
         for pattern in ("chunk_*", "chapter_*"):
-            for chunk_file in CHUNKS_FOLDER.glob(pattern):
+            for chunk_file in Path(chunks_dir).glob(pattern):
                 try:
                     if chunk_file.is_file():
                         chunk_file.unlink()
@@ -532,13 +537,15 @@ def build_ffmetadata(chapters: List[tuple], path: Path) -> None:
 
 
 def combine_chapters_to_m4b(chapter_files: List[Path], titles: List[str],
-                            output_path: Path, speed: float = 1.0,
+                            output_path: Path, *, chunks_dir: Path,
+                            speed: float = 1.0,
                             meta: Optional[TrackMeta] = None,
                             cover: Optional[Path] = None) -> bool:
     """Concatenate per-chapter audio into a single m4b with embedded chapter markers.
 
     Chapter start/end times are derived from each chapter file's duration and
-    written as ffmpeg chapter metadata. ``meta``/``cover`` embed tags and
+    written as ffmpeg chapter metadata; the concat list and metadata scratch
+    files are written to ``chunks_dir``. ``meta``/``cover`` embed tags and
     cover art. When ``speed`` differs from 1.0, a speed-adjusted copy (with
     rescaled chapter markers) is written alongside the normal-speed file.
     """
@@ -550,9 +557,9 @@ def combine_chapters_to_m4b(chapter_files: List[Path], titles: List[str],
         logger.error("No chapter files provided")
         return False
 
-    concat_list = CHUNKS_FOLDER / "_concat_list.txt"
-    metadata_file = CHUNKS_FOLDER / "_chapters.txt"
-    speed_metadata_file = CHUNKS_FOLDER / "_chapters_speed.txt"
+    concat_list = Path(chunks_dir) / "_concat_list.txt"
+    metadata_file = Path(chunks_dir) / "_chapters.txt"
+    speed_metadata_file = Path(chunks_dir) / "_chapters_speed.txt"
     try:
         chapters = []
         start_ms = 0
diff --git a/app/converter/clients/__init__.py b/app/converter/clients/__init__.py
new file mode 100644
index 0000000..e216011
--- /dev/null
+++ b/app/converter/clients/__init__.py
@@ -0,0 +1,68 @@
+"""TTS client implementations — one module per backend server.
+
+Public API: the three client classes (QwenTTSClient, FasterTTSClient,
+AudioCppTTSClient), the backend/voice-mode vocabulary, and the shared
+helpers (normalize_language, speaker tables, whisper transcription) that
+the UIs and setup wizards build on.
+"""
+
+# The TTS backends a conversion can use, in Convert-form order. Each has a
+# client module here; the backends package mirrors these keys for its
+# install/setup wizards.
+BACKEND_QWEN = "qwen"
+BACKEND_FASTER = "faster"
+BACKEND_AUDIOCPP = "audiocpp"
+BACKENDS = (BACKEND_AUDIOCPP, BACKEND_QWEN, BACKEND_FASTER)
+
+from .base import BaseTTSClient, ConversionCancelled, VOICE_MODE_CLONE, \
+    VOICE_MODE_CUSTOM, VOICE_MODES, resolve_request_seed
+from .languages import LANGUAGE_ISO_CODES, TTS_LANGUAGES, \
+    TTS_LANGUAGE_ALIASES, normalize_language
+from .speakers import QWEN3_TTS_SPEAKERS, SPEAKER_DISPLAY_NAMES, \
+    is_builtin_speaker, speaker_display_name, speaker_display_name_for
+from .transcribe import transcribe_reference_audio, whisper_backend_available
+from .qwen import CUSTOM_VOICE_MODEL_ID, MODEL_SIZE, QwenTTSClient
+from .faster import SAMPLE_RATE, FasterTTSClient
+from .audiocpp import (
+    AUDIOCPP_DEFAULT_FAMILY_PROFILE,
+    AUDIOCPP_FAMILY_PROFILES,
+    AUDIOCPP_FAMILY_QWEN3_TTS,
+    AUDIOCPP_LANG_DISPLAY,
+    AUDIOCPP_LANG_ISO,
+    AUDIOCPP_LANG_OMIT,
+    AUDIOCPP_SYNTHESIS_TASKS,
+    AUDIOCPP_TASK_TTS,
+    AUDIOCPP_TASK_VDES,
+    AUDIOCPP_VOICE_CLONE,
+    AUDIOCPP_VOICE_DESIGN,
+    AUDIOCPP_VOICE_SPEAKER,
+    AudioCppFamilyProfile,
+    AudioCppTTSClient,
+    audiocpp_entry_voice_capability,
+)
+
+__all__ = [
+    # vocabulary
+    "BACKEND_QWEN", "BACKEND_FASTER", "BACKEND_AUDIOCPP", "BACKENDS",
+    "VOICE_MODE_CUSTOM", "VOICE_MODE_CLONE", "VOICE_MODES",
+    # clients
+    "BaseTTSClient", "ConversionCancelled", "resolve_request_seed",
+    "QwenTTSClient", "FasterTTSClient", "AudioCppTTSClient",
+    # model facts
+    "MODEL_SIZE", "CUSTOM_VOICE_MODEL_ID", "SAMPLE_RATE",
+    # languages
+    "TTS_LANGUAGES", "TTS_LANGUAGE_ALIASES", "LANGUAGE_ISO_CODES",
+    "normalize_language",
+    # speakers
+    "QWEN3_TTS_SPEAKERS", "SPEAKER_DISPLAY_NAMES",
+    "speaker_display_name", "speaker_display_name_for", "is_builtin_speaker",
+    # transcription
+    "transcribe_reference_audio", "whisper_backend_available",
+    # audio.cpp family profiles
+    "AUDIOCPP_LANG_DISPLAY", "AUDIOCPP_LANG_ISO", "AUDIOCPP_LANG_OMIT",
+    "AUDIOCPP_FAMILY_QWEN3_TTS", "AUDIOCPP_TASK_TTS", "AUDIOCPP_TASK_VDES",
+    "AUDIOCPP_SYNTHESIS_TASKS", "AUDIOCPP_VOICE_SPEAKER",
+    "AUDIOCPP_VOICE_CLONE", "AUDIOCPP_VOICE_DESIGN",
+    "AudioCppFamilyProfile", "AUDIOCPP_DEFAULT_FAMILY_PROFILE",
+    "AUDIOCPP_FAMILY_PROFILES", "audiocpp_entry_voice_capability",
+]
diff --git a/app/converter/tts.py b/app/converter/clients/audiocpp.py
index 8130a44..4a161cb 100644
--- a/app/converter/tts.py
+++ b/app/converter/clients/audiocpp.py
@@ -1,121 +1,25 @@
-"""Client wrappers for the TTS backends.
+"""Client for the audio.cpp audiocpp_server (native ggml TTS families)."""
 
-QwenTTSClient talks to the Qwen3-TTS demo server (custom voice / voice clone).
-FasterTTSClient talks to the OpenAI-compatible server from the
-faster-qwen3-tts repository (voice cloning only; the reference voice is
-configured server-side — see the "Faster backend" section of the README).
-AudioCppTTSClient talks to the audiocpp_server from the audio.cpp
-repository, which can host any TTS model family audio.cpp supports
-(Qwen3-TTS, Higgs Audio, VoxCPM2, IndexTTS2, ...) through one OpenAI-style
-API; the family is detected from the server at startup (see the
-"audio.cpp backend" sections of the README).
-"""
-
-import contextlib
-import io
 import json
 import logging
-import random
 import shutil
-import sys
 import tempfile
-import threading
-import time
 import urllib.error
 import urllib.parse
 import urllib.request
-import wave
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Dict, List, Optional
 
-from . import config
-from .audio import concat_audio_files
-from .chunking import split_into_chunks
+from .. import config
+from ..audio import concat_audio_files
+from ..chunking import split_into_chunks
+from .base import BaseTTSClient, ConversionCancelled, resolve_request_seed
+from .languages import LANGUAGE_ISO_CODES, normalize_language
+from .speakers import (is_builtin_speaker, speaker_display_name,
+                       speaker_display_name_for)
 
 logger = logging.getLogger(__name__)
 
-
-class ConversionCancelled(Exception):
-    """Raised inside a conversion whose cancel event was set.
-
-    The TUI run view sets a ``threading.Event`` on the TTS client (and the
-    converter checks it between chunks/chapters/books); the retry loops
-    raise this so the cancellation propagates out of a sleeping or retrying
-    request promptly instead of finishing the retry ladder.
-    """
-
-
-# Voice modes (re-exported for the CLI and the converter orchestrator).
-VOICE_MODE_CUSTOM = "custom_voice"
-VOICE_MODE_CLONE = "voice_clone"
-VOICE_MODES = (VOICE_MODE_CUSTOM, VOICE_MODE_CLONE)
-
-# TTS backends (re-exported for the CLI and the converter orchestrator).
-BACKEND_QWEN = "qwen"
-BACKEND_FASTER = "faster"
-BACKEND_AUDIOCPP = "audiocpp"
-BACKENDS = (BACKEND_AUDIOCPP, BACKEND_QWEN, BACKEND_FASTER)
-
-# Languages understood by the Qwen3-TTS API. Display names must match the
-# demo dropdown exactly (the demo silently falls back to "Auto" for
-# unrecognized values, so languages are validated client-side first).
-TTS_LANGUAGES = (
-    "Auto",
-    "Chinese",
-    "English",
-    "German",
-    "Italian",
-    "Portuguese",
-    "Spanish",
-    "Japanese",
-    "Korean",
-    "French",
-    "Russian",
-)
-
-# Short aliases accepted on the command line (ISO 639-1 codes and common
-# shorthands), mapped to the display names above.
-TTS_LANGUAGE_ALIASES = {
-    "zh": "Chinese",
-    "en": "English",
-    "de": "German",
-    "it": "Italian",
-    "pt": "Portuguese",
-    "es": "Spanish",
-    "ja": "Japanese",
-    "ko": "Korean",
-    "fr": "French",
-    "ru": "Russian",
-    "zh-cn": "Chinese",
-    "zh-tw": "Chinese",
-    "pt-br": "Portuguese",
-    "en-us": "English",
-    "en-gb": "English",
-}
-
-# Qwen display names -> ISO 639-1 codes, for audio.cpp families whose
-# language request option takes a code instead of a display name. "Auto"
-# has no code and maps to None so the field is omitted and the server
-# applies its own default.
-LANGUAGE_ISO_CODES = {
-    "Chinese": "zh",
-    "English": "en",
-    "German": "de",
-    "Italian": "it",
-    "Portuguese": "pt",
-    "Spanish": "es",
-    "Japanese": "ja",
-    "Korean": "ko",
-    "French": "fr",
-    "Russian": "ru",
-}
-
-# --- audio.cpp model families ---------------------------------------------
-#
-# audiocpp_server exposes the same OpenAI-style API for every TTS family it
-# hosts; families only differ in a few request conventions, captured here as
-# profiles. Families that are not listed use the default profile below.
-
 # How the "language" request field is expressed by a family.
 AUDIOCPP_LANG_DISPLAY = "display"  # Qwen display names, e.g. "English"
 AUDIOCPP_LANG_ISO = "iso"          # ISO 639-1 codes, e.g. "en"
@@ -210,664 +114,8 @@ def audiocpp_entry_voice_capability(family: str, task: str,
         return AUDIOCPP_VOICE_SPEAKER
     return AUDIOCPP_VOICE_CLONE
 
-# Built-in CustomVoice speaker names for the Qwen3-TTS family. Shared by the
-# qwen-tts demo backend (config.SPEAKER, the qwen setup/form) and the
-# audio.cpp audiocpp backend's CustomVoice entry (the Convert form's Speaker
-# picker). Entries are the canonical/config form; speaker_display_name()
-# maps them to the wire (display) form via SPEAKER_DISPLAY_NAMES below.
-QWEN3_TTS_SPEAKERS = ("Vivian", "Serena", "Uncle_Fu", "Dylan", "Eric",
-                      "Ryan", "Aiden", "Ono_Anna", "Sohee")
-
-# Canonical speaker names -> display names used by the qwen-tts demo.
-SPEAKER_DISPLAY_NAMES = {
-    "ryan": "Ryan",
-    "serena": "Serena",
-    "vivian": "Vivian",
-    "uncle_fu": "Uncle Fu",
-    "aiden": "Aiden",
-    "ono_anna": "Ono Anna",
-    "sohee": "Sohee",
-    "eric": "Eric",
-    "dylan": "Dylan",
-}
-
-# Fixed model facts: both demos run the 1.7B model (the CustomVoice demo
-# takes its full HuggingFace id), and the 12Hz codec outputs 24 kHz audio.
-MODEL_SIZE = "1.7B"
-CUSTOM_VOICE_MODEL_ID = "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice"
-SAMPLE_RATE = 24000
-
-CHUNKS_FOLDER = Path(__file__).resolve().parent.parent.parent / "app" / "chunks"
-
-
-def _resolve_request_seed() -> int:
-    """Resolve the seed sent with every request.
-
-    Returns config.SEED as-is, or (with CONSTANT_SEED and SEED < 0) one
-    random value drawn per run, meant to be reused for every request so
-    the voice stays consistent across chunk boundaries. Without
-    CONSTANT_SEED, -1 is returned so the server re-samples the voice on
-    every generation.
-    """
-    seed = config.SEED
-    if config.CONSTANT_SEED and seed < 0:
-        seed = random.randrange(2 ** 31)
-    return seed
-
-
-def speaker_display_name_for(name: str) -> str:
-    """Return the wire (display) form of a Qwen3-TTS CustomVoice speaker NAME.
-
-    Accepts either the canonical/config form (e.g. "uncle_fu", "Uncle_Fu")
-    or the display form ("Uncle Fu"), case-insensitively; unknown names pass
-    through unchanged. Used by AudioCppTTSClient to normalize the --voice /
-    Speaker-picker value into what audiocpp_server expects in the request's
-    voice field.
-    """
-    return SPEAKER_DISPLAY_NAMES.get((name or "").lower(), name)
-
-
-def is_builtin_speaker(name: Optional[str]) -> bool:
-    """True when NAME is one of the Qwen3-TTS CustomVoice built-in speakers.
-
-    Matches case-insensitively across the canonical ("Uncle_Fu"), display
-    ("Uncle Fu") and shorthand ("uncle_fu") forms, so the --voice flag and
-    the Convert form's Speaker picker resolve to the same set.
-    """
-    if not name:
-        return False
-    norm = name.lower().replace("_", " ").replace("-", " ")
-    return any(norm == speaker.lower().replace("_", " ")
-               for speaker in QWEN3_TTS_SPEAKERS)
-
-
-def speaker_display_name() -> str:
-    """Return the display name for the configured custom speaker."""
-    return speaker_display_name_for(config.SPEAKER)
-
-
-def normalize_language(value: Optional[str]) -> str:
-    """Normalize a user-provided language name to a Qwen3-TTS display name.
-
-    Accepts the display names in TTS_LANGUAGES case-insensitively as
-    well as the short aliases in TTS_LANGUAGE_ALIASES (ISO 639-1 codes
-    and common shorthands). Raises ValueError for anything else, since the
-    Qwen3-TTS demo silently falls back to "Auto" for unrecognized languages.
-    """
-    if value is None:
-        raise ValueError("Language must not be None")
-    candidate = value.strip()
-    if not candidate:
-        raise ValueError("Language must not be empty")
-    for name in TTS_LANGUAGES:
-        if candidate.lower() == name.lower():
-            return name
-    alias = TTS_LANGUAGE_ALIASES.get(candidate.lower())
-    if alias:
-        return alias
-    raise ValueError(
-        f"Unknown language: {value!r}. Expected one of "
-        f"{', '.join(TTS_LANGUAGES)} (or an alias: "
-        f"{', '.join(sorted(TTS_LANGUAGE_ALIASES))})."
-    )
-
-
-def transcribe_reference_audio(audio_path: str, model_name: str = "base") -> Optional[str]:
-    """Transcribe reference audio locally using an optional Whisper backend.
-
-    The current qwen-tts demo does not expose a transcription endpoint, so
-    transcription is done client-side when a Whisper package is available.
-    Returns None if no backend is installed.
-    """
-    for backend in ("faster_whisper", "whisper"):
-        try:
-            if backend == "faster_whisper":
-                from faster_whisper import WhisperModel
-                model = WhisperModel(model_name, device="cpu", compute_type="int8")
-                segments, _ = model.transcribe(audio_path)
-                text = " ".join(seg.text.strip() for seg in segments).strip()
-            else:
-                import whisper
-                model = whisper.load_model(model_name)
-                result = model.transcribe(audio_path)
-                text = (result.get("text") or "").strip()
-            if text:
-                logger.info("Transcription complete via %s: %s", backend, text)
-                return text
-        except ImportError:
-            continue
-        except Exception as exc:
-            logger.warning("%s transcription failed: %s", backend, exc)
-    logger.warning("No Whisper backend available; transcription skipped.")
-    return None
-
-
-def whisper_backend_available() -> Optional[str]:
-    """Return the name of an importable Whisper backend, or None.
-
-    Checks faster_whisper first (preferred), then the openai-whisper
-    package, without importing the heavy model code: a bare import probe
-    is enough to tell whether the package is installed in the current
-    environment. Used by the make_audiocpp_server_json tool to warn when
-    neither is present (e.g. the wrong conda environment is active).
-    """
-    for backend in ("faster_whisper", "whisper"):
-        try:
-            __import__(backend)
-        except ImportError:
-            continue
-        return backend
-    return None
-
-
-class _BaseTTSClient:
-    """Shared chunk retry logic, heartbeat, and chunk file bookkeeping."""
-
-    # Set by the converter when the run is cancellable (the TUI run view):
-    # a threading.Event that, once set, aborts the run between requests
-    # (and interrupts retry back-off sleeps). ``quiet`` silences console
-    # prints (the run view owns the screen).
-    cancel = None
-    quiet = False
-
-    def _report(self, message: str) -> None:
-        """Print a console line unless quiet (the run view owns the screen)."""
-        if not self.quiet:
-            print(message)
-
-    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
-        """Generate one audio chunk; returns its path in the chunks folder."""
-        raise NotImplementedError
-
-    def _cancel_requested(self) -> bool:
-        """True when the run's cancel event has been set (if any)."""
-        return isinstance(self.cancel, threading.Event) \
-            and self.cancel.is_set()
-
-    def _check_cancelled(self) -> None:
-        """Raise ConversionCancelled when the cancel event is set."""
-        if self._cancel_requested():
-            raise ConversionCancelled("Cancelled by user")
-
-    def _sleep(self, seconds: float) -> None:
-        """Sleep SECONDS, cut short (raising) when the cancel event sets."""
-        if isinstance(self.cancel, threading.Event):
-            if self.cancel.wait(seconds):
-                raise ConversionCancelled("Cancelled by user")
-        else:
-            time.sleep(seconds)
-
-    def _chunk_path(self, chunk_num: int, suffix: str) -> Path:
-        """Resolve the target path for a chunk, removing stale files first.
-
-        Any stale chunk file for this index is removed so a retry or extension
-        change can never leave two files matching chunk_NNNN.*.
-        """
-        for stale in CHUNKS_FOLDER.glob(f"chunk_{chunk_num:04d}.*"):
-            try:
-                stale.unlink()
-            except OSError as exc:
-                logger.debug("Could not remove stale chunk file %s: %s", stale, exc)
-        return CHUNKS_FOLDER / f"chunk_{chunk_num:04d}{suffix}"
-
-    def process_chunk_with_retry(self, chunk_num: int, text: str) -> Optional[Path]:
-        """Process a chunk with retry logic.
-
-        Returns the generated chunk file's path, or None when all attempts
-        failed. Raises ConversionCancelled when the run was cancelled.
-        """
-        for attempt in range(config.MAX_RETRIES):
-            self._check_cancelled()
-            try:
-                result = self.generate_chunk(text, chunk_num)
-                if result and Path(result).exists():
-                    return Path(result)
-                logger.warning("Chunk %d attempt %d failed", chunk_num, attempt + 1)
-            except ConversionCancelled:
-                raise
-            except Exception as exc:
-                logger.warning("Chunk %d attempt %d error: %s", chunk_num, attempt + 1, exc)
-
-            if attempt < config.MAX_RETRIES - 1:
-                sleep_time = 5 + (2 ** attempt)
-                logger.info("Waiting %ds before retry...", sleep_time)
-                self._sleep(sleep_time)
-
-        logger.error("Chunk %d failed after %d attempts", chunk_num, config.MAX_RETRIES)
-        return None
-
-    @contextlib.contextmanager
-    def _chunk_heartbeat(self, chunk_num: int):
-        """Log a periodic "still working" record while a request generates."""
-        stop = threading.Event()
-        subject = f"Chunk {chunk_num}"
-
-        def _beat():
-            start = time.time()
-            while not stop.wait(config.HEARTBEAT_INTERVAL_SECONDS):
-                elapsed = time.time() - start
-                if self.quiet:
-                    logger.info("%s still generating — %dm %ds elapsed",
-                                subject, int(elapsed // 60), int(elapsed % 60))
-                else:
-                    print(f"[...] {subject} still generating — "
-                          f"{int(elapsed // 60)}m {int(elapsed % 60)}s elapsed",
-                          flush=True)
-
-        thread = threading.Thread(target=_beat, daemon=True)
-        thread.start()
-        try:
-            yield
-        finally:
-            stop.set()
-            thread.join()
-
-
-class QwenTTSClient(_BaseTTSClient):
-    """Generates audio chunks through a Qwen3-TTS demo server."""
-
-    def __init__(self, voice_mode: str = "custom_voice", voice_clone_ref_audio: Optional[str] = None,
-                 voice_clone_ref_text: Optional[str] = None, skip_transcription: bool = False,
-                 language: Optional[str] = None, api_url: Optional[str] = None,
-                 quiet: bool = False):
-        # Quiet before connecting so connect-time status lines never reach
-        # a screen the TUI run view owns.
-        self.quiet = bool(quiet)
-        if voice_mode not in VOICE_MODES:
-            raise ValueError(
-                f"Unknown voice mode: {voice_mode!r} (expected one of {VOICE_MODES})"
-            )
-        self.voice_mode = voice_mode
-        self.voice_clone_ref_audio = voice_clone_ref_audio
-        self.voice_clone_ref_text = (voice_clone_ref_text or "").strip()
-        self.skip_transcription = skip_transcription
-        # api_url overrides the configured endpoint for the active voice mode
-        # (used by the hub's "[remote]" backend entries and --api-url).
-        self.api_url = (api_url or "").strip() or None
-        # Seed sent with every request: config.SEED as-is, or (with
-        # CONSTANT_SEED and SEED < 0) one random value drawn per run and
-        # reused for every request so the voice stays consistent across
-        # chunk boundaries. Without CONSTANT_SEED, -1 is forwarded so the
-        # server re-samples the voice on every generation.
-        self._seed = _resolve_request_seed()
-        if language is None:
-            language = config.LANGUAGE
-        # Validate before connecting so bad values fail fast without a server.
-        self.language = normalize_language(language)
-        self.client = None
-        self.api_info: Dict[str, Any] = {}
-        self.clone_client = None
-        self.clone_api_info: Dict[str, Any] = {}
-        self._ref_audio_filedata: Optional[Dict[str, Any]] = None
-        self._connect()
-
-    # ------------------------------------------------------------------
-    # Connection
-    # ------------------------------------------------------------------
-
-    def _connect(self) -> None:
-        api_url = self.api_url or (
-            config.CLONE_API_URL if self.voice_mode == VOICE_MODE_CLONE
-            else config.QWEN_API_URL)
-        try:
-            if self.voice_mode == VOICE_MODE_CLONE:
-                # Voice clone uses the Base-model demo, which is a separate server
-                # from the CustomVoice demo (that one only exposes /run_instruct).
-                self._init_client(api_url, clone=True)
-                self._report(f"[OK] Connected to Voice Clone API at {api_url}")
-                self._resolve_reference_text()
-            else:
-                self._init_client(api_url, clone=False)
-                self._report("[OK] Connected to Qwen API")
-        except Exception as exc:
-            raise RuntimeError(
-                f"Qwen API initialization failed at {api_url}: {exc}. "
-                "Make sure the Qwen demo server is running and reachable, and that your "
-                "installed Qwen3-TTS version matches this converter's API expectations "
-                "(voice clone requires the Base-model demo: Qwen/Qwen3-TTS-12Hz-1.7B-Base)."
-            ) from exc
-
-    def _resolve_reference_text(self) -> None:
-        """Resolve the reference transcript: explicit text, then local
-        transcription, then x-vector-only mode."""
-        if not self.voice_clone_ref_text and self.voice_clone_ref_audio:
-            if self.skip_transcription:
-                self._report("[INFO] Skipping reference audio transcription (--no-transcription).")
-            else:
-                self._report("[INFO] Transcribing reference audio for voice cloning...")
-                self.voice_clone_ref_text = self.transcribe_audio(self.voice_clone_ref_audio) or ""
-        if not self.voice_clone_ref_text:
-            self._report("[WARNING] No reference text available; using "
-                         "x-vector-only clone mode (lower quality).")
-            self._report('          Pass --transcription "..." for higher-quality in-context cloning.')
-        else:
-            self._report(f"[OK] Reference text:\n{self.voice_clone_ref_text}")
-
-    def _init_client(self, url: str, clone: bool = False) -> None:
-        """Initialize a Gradio client and store its API metadata.
-
-        gradio_client prints its usage info directly to stdout while the
-        client is created and its API metadata loaded, so stdout is swapped
-        for a buffer for the whole process; the captured text is re-emitted
-        at DEBUG level for troubleshooting.
-        """
-        from gradio_client import Client
-
-        logger.info("Connecting to Qwen API at %s...", url)
-        old_stdout = sys.stdout
-        captured = io.StringIO()
-        sys.stdout = captured
-        try:
-            try:
-                client = Client(url, httpx_kwargs={"timeout": config.API_TIMEOUT})
-            except TypeError:
-                # Older gradio_client versions don't support httpx_kwargs.
-                client = Client(url)
-            if clone:
-                self.clone_client = client
-                self.clone_api_info = self._load_api_info(client)
-            else:
-                self.client = client
-                self.api_info = self._load_api_info(client)
-        finally:
-            sys.stdout = old_stdout
-        usage_info = captured.getvalue().strip()
-        if usage_info:
-            logger.debug("Gradio client output for %s:\n%s", url, usage_info)
-        logger.info("Connected to Qwen API")
-
-    @staticmethod
-    def _load_api_info(client) -> Dict[str, Any]:
-        """Load available API metadata from the Gradio app."""
-        try:
-            return client.view_api(return_format="dict")
-        except Exception as exc:
-            logger.warning("Unable to read API metadata: %s", exc)
-            return {}
-
-    def _resolve_api_name(self, *candidates: str, api_info: Optional[Dict[str, Any]] = None) -> str:
-        """Return the first available api_name from candidate list."""
-        info = api_info if api_info is not None else self.api_info
-        named_endpoints = info.get("named_endpoints", {})
-        for candidate in candidates:
-            if candidate in named_endpoints:
-                return candidate
-        return candidates[0]
-
-    def _endpoint_accepts_param(self, api_name: str, param_name: str,
-                                api_info: Optional[Dict[str, Any]] = None) -> bool:
-        """Check whether endpoint input schema includes the given parameter."""
-        info = api_info if api_info is not None else self.api_info
-        endpoint = info.get("named_endpoints", {}).get(api_name, {})
-        parameters = endpoint.get("parameters", [])
-        return any(parameter.get("parameter_name") == param_name for parameter in parameters)
-
-    # ------------------------------------------------------------------
-    # Reference audio transcription (voice clone)
-    # ------------------------------------------------------------------
-
-    def transcribe_audio(self, audio_path: str) -> Optional[str]:
-        """Transcribe reference audio locally using an optional Whisper backend."""
-        return transcribe_reference_audio(audio_path)
-
-    # ------------------------------------------------------------------
-    # Chunk generation
-    # ------------------------------------------------------------------
-
-    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
-        """Generate one audio chunk; returns its path in the chunks folder.
-
-        The text is split into sub-requests of at most
-        ``config.CHUNK_SIZE`` words each (the book-level chunker
-        normally guarantees this already; the split is defense in depth
-        against pathological input such as a punctuation-free run of
-        text), and the audio files returned for the sub-requests are
-        concatenated into one chunk file.
-        """
-        try:
-            sub_texts = split_into_chunks(text, max_words=config.CHUNK_SIZE)
-            if not sub_texts:
-                raise RuntimeError("No text to synthesize")
-
-            output_path: Optional[Path] = None
-            with tempfile.TemporaryDirectory(prefix="tts_parts_") as parts_dir, \
-                    self._chunk_heartbeat(chunk_num):
-                part_paths = [
-                    self._generate_sub_request(sub_text, parts_dir, sub_num,
-                                                len(sub_texts), chunk_num)
-                    for sub_num, sub_text in enumerate(sub_texts, 1)
-                ]
-                if len(part_paths) == 1:
-                    suffix = part_paths[0].suffix or ".wav"
-                    output_path = self._chunk_path(chunk_num, suffix)
-                    shutil.copy2(part_paths[0], output_path)
-                else:
-                    output_path = self._chunk_path(chunk_num, ".wav")
-                    concat_audio_files(part_paths, output_path)
-
-            logger.debug("Chunk %d generated successfully (%d sub-request(s))",
-                         chunk_num, len(sub_texts))
-            return str(output_path)
-
-        except ConversionCancelled:
-            raise
-        except Exception as exc:
-            logger.error("Qwen chunk processing failed for chunk %d: %s", chunk_num, exc)
-            return None
-
-    def _generate_sub_request(self, text: str, parts_dir: str, sub_num: int,
-                              sub_total: int, chunk_num: int) -> Path:
-        """Run one API generation for ``text``; returns the downloaded audio."""
-        if sub_total > 1:
-            logger.info("Chunk %d: oversized input split into %d requests "
-                        "(sub-request %d/%d)", chunk_num, sub_total, sub_num, sub_total)
-        if self.voice_mode == VOICE_MODE_CUSTOM:
-            result = self._generate_custom_voice(text)
-        elif self.voice_mode == VOICE_MODE_CLONE:
-            result = self._generate_voice_clone(text)
-        else:
-            raise ValueError(f"Unknown voice mode: {self.voice_mode}")
-
-        if not isinstance(result, (tuple, list)) or not result:
-            raise RuntimeError("Qwen API returned an invalid result")
-
-        audio_path = result[0]  # First element is the audio file path
-        if not isinstance(audio_path, (str, Path)) or not audio_path:
-            raise RuntimeError("Qwen API did not return an audio file path")
-
-        source = Path(audio_path)
-        if not source.exists():
-            raise RuntimeError(f"Generated audio file not found: {audio_path}")
-
-        destination = Path(parts_dir) / f"part_{sub_num:02d}{source.suffix or '.wav'}"
-        shutil.copy2(source, destination)
-
-        return destination
-
-    # ------------------------------------------------------------------
-    # API payloads
-    # ------------------------------------------------------------------
-
-    def _generate_custom_voice(self, text: str) -> Tuple:
-        """Generate audio using CustomVoice mode."""
-        custom_api = self._resolve_api_name("/run_instruct", "/run_custom_voice", "/generate_custom_voice")
-        if custom_api == "/run_instruct":
-            payload = dict(
-                text=text,
-                lang_disp=self.language,
-                spk_disp=speaker_display_name(),
-                instruct=config.INSTRUCT,
-            )
-        else:
-            payload = dict(
-                text=text,
-                language=self.language,
-                speaker=config.SPEAKER,
-                instruct=config.INSTRUCT,
-            )
-            if self._endpoint_accepts_param(custom_api, "model_id_cv"):
-                payload["model_id_cv"] = CUSTOM_VOICE_MODEL_ID
-            elif self._endpoint_accepts_param(custom_api, "model_size"):
-                payload["model_size"] = MODEL_SIZE
-
-            if self._endpoint_accepts_param(custom_api, "seed"):
-                payload["seed"] = self._seed
-
-        return self.client.predict(**payload, api_name=custom_api)
-
-    def _ref_audio_payload(self) -> Dict[str, Any]:
-        """Gradio file payload for the reference audio (built once, reused)."""
-        if self._ref_audio_filedata is None:
-            from gradio_client import handle_file
-            self._ref_audio_filedata = handle_file(self.voice_clone_ref_audio)
-        return self._ref_audio_filedata
-
-    def _generate_voice_clone(self, text: str) -> Tuple:
-        """Generate audio using Voice Clone mode."""
-        if not Path(self.voice_clone_ref_audio).exists():
-            raise FileNotFoundError(f"Reference audio not found: {self.voice_clone_ref_audio}")
-
-        if self.clone_client is None:
-            raise RuntimeError("Voice Clone client is not initialized. Is the Base-model demo running?")
-
-        clone_api = self._resolve_api_name("/run_voice_clone", "/generate_voice_clone",
-                                           api_info=self.clone_api_info)
-        use_xvector = config.XVECTOR_ONLY or not self.voice_clone_ref_text
-
-        if clone_api == "/run_voice_clone":
-            payload = dict(
-                ref_aud=self._ref_audio_payload(),
-                ref_txt=self.voice_clone_ref_text,
-                use_xvec=use_xvector,
-                text=text,
-                lang_disp=self.language,
-            )
-        else:
-            payload = dict(
-                ref_audio=self._ref_audio_payload(),
-                ref_text=self.voice_clone_ref_text,
-                target_text=text,
-                language=self.language,
-                use_xvector_only=use_xvector,
-            )
-            optional_params = {
-                "model_size": MODEL_SIZE,
-                "seed": self._seed,
-            }
-            for name, value in optional_params.items():
-                if self._endpoint_accepts_param(clone_api, name, api_info=self.clone_api_info):
-                    payload[name] = value
-
-        return self.clone_client.predict(**payload, api_name=clone_api)
-
-
-class FasterTTSClient(_BaseTTSClient):
-    """Generates audio chunks through a faster-qwen3-tts server.
-
-    Talks to the OpenAI-compatible server shipped in the faster-qwen3-tts
-    repository (examples/openai_server.py). The reference voice (ref audio,
-    ref text) and language are configured on the server itself via
-    --ref-audio/--ref-text or a --voices JSON file; this client only sends
-    text. Unlike the Qwen demo, the server performs one generation per
-    request, so long chunks are sub-chunked client-side.
-    """
-
-    def __init__(self, voice: Optional[str] = None, api_url: Optional[str] = None,
-                 quiet: bool = False):
-        # Quiet before connecting so connect-time status lines never reach
-        # a screen the TUI run view owns.
-        self.quiet = bool(quiet)
-        self.voice = voice or config.FASTER_VOICE
-        self.api_url = (api_url or config.FASTER_API_URL).rstrip("/")
-        self._check_health()
-
-    def _check_health(self) -> None:
-        """Verify the server is reachable and its model is loaded."""
-        url = f"{self.api_url}/health"
-        try:
-            with urllib.request.urlopen(url, timeout=10) as response:
-                payload = json.loads(response.read().decode("utf-8"))
-        except Exception as exc:
-            raise RuntimeError(
-                f"Faster TTS server not reachable at {url}: {exc}. "
-                "Start the faster-qwen3-tts OpenAI-compatible server first "
-                "(see the 'Faster backend' section of the README)."
-            ) from exc
-        if not payload.get("model_loaded"):
-            raise RuntimeError(
-                "The faster TTS server is running but its model is not loaded yet; "
-                "wait for model download and startup to finish, then retry."
-            )
-        self._report(f"[OK] Connected to faster TTS API at {self.api_url} (voice '{self.voice}')")
-        self._report(f"[INFO] The server silently falls back to its first configured voice if "
-                     f"'{self.voice}' is not defined in its voice config (see README).")
-
-    # ------------------------------------------------------------------
-    # HTTP requests
-    # ------------------------------------------------------------------
-
-    def _request_pcm(self, text: str) -> bytes:
-        """POST one sub-chunk and return raw 16-bit mono PCM bytes."""
-        url = f"{self.api_url}/v1/audio/speech"
-        payload = json.dumps({
-            "model": "tts-1",
-            "input": text,
-            "voice": self.voice,
-            "response_format": "pcm",
-        }).encode("utf-8")
-        request = urllib.request.Request(
-            url, data=payload, headers={"Content-Type": "application/json"}, method="POST")
-        try:
-            with urllib.request.urlopen(request, timeout=config.API_TIMEOUT) as response:
-                pcm = response.read()
-        except urllib.error.HTTPError as exc:
-            detail = ""
-            try:
-                detail = exc.read().decode("utf-8", errors="replace")[:200]
-            except Exception:
-                pass
-            raise RuntimeError(f"Faster TTS server returned HTTP {exc.code}: {detail}") from exc
-        except urllib.error.URLError as exc:
-            raise RuntimeError(f"Faster TTS request failed: {exc.reason}") from exc
-        if not pcm:
-            raise RuntimeError("Faster TTS server returned empty audio")
-        return pcm
-
-    # ------------------------------------------------------------------
-    # Chunk generation
-    # ------------------------------------------------------------------
-
-    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
-        """Generate one audio chunk; returns its path in the chunks folder."""
-        try:
-            sub_chunks = split_into_chunks(text, max_words=config.CHUNK_SIZE)
-            if not sub_chunks:
-                raise RuntimeError("No text to synthesize")
-
-            pcm_parts: List[bytes] = []
-            with self._chunk_heartbeat(chunk_num):
-                for sub_num, sub_text in enumerate(sub_chunks, 1):
-                    pcm = self._request_pcm(sub_text)
-                    pcm_parts.append(pcm)
-
-            output_path = self._chunk_path(chunk_num, ".wav")
-            with wave.open(str(output_path), "wb") as wav_file:
-                wav_file.setnchannels(1)
-                wav_file.setsampwidth(2)
-                wav_file.setframerate(SAMPLE_RATE)
-                wav_file.writeframes(b"".join(pcm_parts))
-
-            logger.debug("Chunk %d generated (%d sub-chunks)", chunk_num, len(sub_chunks))
-            return str(output_path)
-
-        except ConversionCancelled:
-            raise
-        except Exception as exc:
-            logger.error("Faster chunk processing failed for chunk %d: %s", chunk_num, exc)
-            return None
-
 
-class AudioCppTTSClient(_BaseTTSClient):
+class AudioCppTTSClient(BaseTTSClient):
     """Generates audio chunks through an audio.cpp audiocpp_server.
 
     Talks to the OpenAI-style HTTP API of audiocpp_server, which hosts TTS
@@ -928,15 +176,14 @@ class AudioCppTTSClient(_BaseTTSClient):
     used for the Qwen client.
     """
 
-    def __init__(self, voice: Optional[str] = None, language: Optional[str] = None,
+    def __init__(self, chunks_dir: Path,
+                 voice: Optional[str] = None, language: Optional[str] = None,
                  api_url: Optional[str] = None,
                  model_id: Optional[str] = None,
                  instructions: Optional[str] = None,
                  request_options: Optional[Dict[str, str]] = None,
                  quiet: bool = False):
-        # Quiet before connecting so connect-time status lines never reach
-        # a screen the TUI run view owns.
-        self.quiet = bool(quiet)
+        super().__init__(chunks_dir, quiet=quiet)
         self.api_url = (api_url or config.AUDIOCPP_API_URL).rstrip("/")
         # Per-run model selection: the --model CLI flag overrides config; an
         # empty value is resolved at connect time when the server hosts exactly
@@ -948,10 +195,10 @@ class AudioCppTTSClient(_BaseTTSClient):
         self.language = normalize_language(
             language if language is not None else config.LANGUAGE)
         # One seed value per run, reused for every request (see
-        # _resolve_request_seed). Unlike the Qwen demo, audio.cpp has no
+        # resolve_request_seed). Unlike the Qwen demo, audio.cpp has no
         # negative "randomize" seed, so a negative value means "send no seed
         # at all" (see _request_wav) and the server randomizes.
-        self._seed = _resolve_request_seed()
+        self._seed = resolve_request_seed()
         # Voice selection (the --voice name). preset_mode / speaker_mode are
         # resolved in _connect: a --voice that names a built-in CustomVoice
         # speaker on a speaker-capable entry selects speaker mode; every
diff --git a/app/converter/clients/base.py b/app/converter/clients/base.py
new file mode 100644
index 0000000..a0f28cf
--- /dev/null
+++ b/app/converter/clients/base.py
@@ -0,0 +1,155 @@
+"""Shared TTS client plumbing: cancellation, retries, chunk bookkeeping."""
+
+import contextlib
+import logging
+import random
+import threading
+import time
+from pathlib import Path
+from typing import Optional
+
+from .. import config
+
+logger = logging.getLogger(__name__)
+
+
+class ConversionCancelled(Exception):
+    """Raised when the run's cancel event is set (between requests)."""
+
+
+# How a run supplies its voice: a built-in CustomVoice speaker, or by
+# cloning a reference audio clip (the faster and audiocpp backends always
+# clone server-side; only the Qwen client branches on this at request time).
+VOICE_MODE_CUSTOM = "custom_voice"
+VOICE_MODE_CLONE = "voice_clone"
+VOICE_MODES = (VOICE_MODE_CUSTOM, VOICE_MODE_CLONE)
+
+
+def resolve_request_seed() -> int:
+    """Resolve the seed sent with every request.
+
+    Returns config.SEED as-is, or (with CONSTANT_SEED and SEED < 0) one
+    random value drawn per run, meant to be reused for every request so
+    the voice stays consistent across chunk boundaries. Without
+    CONSTANT_SEED, -1 is returned so the server re-samples the voice on
+    every generation.
+    """
+    seed = config.SEED
+    if config.CONSTANT_SEED and seed < 0:
+        seed = random.randrange(2 ** 31)
+    return seed
+
+
+class BaseTTSClient:
+    """Shared chunk retry logic, heartbeat, and chunk file bookkeeping.
+
+    CHUNKS_DIR is the scratch folder the generated chunk files are written
+    to — provided by the converter that owns the run's folders, never a
+    module global, so concurrent runs (and tests) cannot step on each other.
+    """
+
+    # Class-level defaults so a partially-constructed instance behaves like
+    # a plain console run (tests build clients via __new__).
+    cancel = None
+    quiet = False
+
+    def __init__(self, chunks_dir: Path, quiet: bool = False):
+        self.chunks_dir = Path(chunks_dir)
+        # Quiet silences console prints (the run view owns the screen).
+        self.quiet = bool(quiet)
+        # Set by the converter when the run is cancellable (the TUI run
+        # view): a threading.Event that, once set, aborts the run between
+        # requests (and interrupts retry back-off sleeps).
+        self.cancel = None
+
+    def _report(self, message: str) -> None:
+        """Print a console line unless quiet (the run view owns the screen)."""
+        if not self.quiet:
+            print(message)
+
+    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
+        """Generate one audio chunk; returns its path in the chunks folder."""
+        raise NotImplementedError
+
+    def _cancel_requested(self) -> bool:
+        """True when the run's cancel event has been set (if any)."""
+        return isinstance(self.cancel, threading.Event) \
+            and self.cancel.is_set()
+
+    def _check_cancelled(self) -> None:
+        """Raise ConversionCancelled when the cancel event is set."""
+        if self._cancel_requested():
+            raise ConversionCancelled("Cancelled by user")
+
+    def _sleep(self, seconds: float) -> None:
+        """Sleep SECONDS, cut short (raising) when the cancel event sets."""
+        if isinstance(self.cancel, threading.Event):
+            if self.cancel.wait(seconds):
+                raise ConversionCancelled("Cancelled by user")
+        else:
+            time.sleep(seconds)
+
+    def _chunk_path(self, chunk_num: int, suffix: str) -> Path:
+        """Resolve the target path for a chunk, removing stale files first.
+
+        Any stale chunk file for this index is removed so a retry or extension
+        change can never leave two files matching chunk_NNNN.*.
+        """
+        for stale in self.chunks_dir.glob(f"chunk_{chunk_num:04d}.*"):
+            try:
+                stale.unlink()
+            except OSError as exc:
+                logger.debug("Could not remove stale chunk file %s: %s", stale, exc)
+        return self.chunks_dir / f"chunk_{chunk_num:04d}{suffix}"
+
+    def process_chunk_with_retry(self, chunk_num: int, text: str) -> Optional[Path]:
+        """Process a chunk with retry logic.
+
+        Returns the generated chunk file's path, or None when all attempts
+        failed. Raises ConversionCancelled when the run was cancelled.
+        """
+        for attempt in range(config.MAX_RETRIES):
+            self._check_cancelled()
+            try:
+                result = self.generate_chunk(text, chunk_num)
+                if result and Path(result).exists():
+                    return Path(result)
+                logger.warning("Chunk %d attempt %d failed", chunk_num, attempt + 1)
+            except ConversionCancelled:
+                raise
+            except Exception as exc:
+                logger.warning("Chunk %d attempt %d error: %s", chunk_num, attempt + 1, exc)
+
+            if attempt < config.MAX_RETRIES - 1:
+                sleep_time = 5 + (2 ** attempt)
+                logger.info("Waiting %ds before retry...", sleep_time)
+                self._sleep(sleep_time)
+
+        logger.error("Chunk %d failed after %d attempts", chunk_num, config.MAX_RETRIES)
+        return None
+
+    @contextlib.contextmanager
+    def _chunk_heartbeat(self, chunk_num: int):
+        """Log a periodic "still working" record while a request generates."""
+        stop = threading.Event()
+        subject = f"Chunk {chunk_num}"
+
+        def _beat():
+            start = time.time()
+            while not stop.wait(config.HEARTBEAT_INTERVAL_SECONDS):
+                elapsed = time.time() - start
+                if self.quiet:
+                    logger.info("%s still generating — %dm %ds elapsed",
+                                subject, int(elapsed // 60), int(elapsed % 60))
+                else:
+                    print(f"[...] {subject} still generating — "
+                          f"{int(elapsed // 60)}m {int(elapsed % 60)}s elapsed",
+                          flush=True)
+
+        thread = threading.Thread(target=_beat, daemon=True)
+        thread.start()
+        try:
+            yield
+        finally:
+            stop.set()
+            thread.join()
diff --git a/app/converter/clients/faster.py b/app/converter/clients/faster.py
new file mode 100644
index 0000000..df98546
--- /dev/null
+++ b/app/converter/clients/faster.py
@@ -0,0 +1,123 @@
+"""Client for the faster-qwen3-tts OpenAI-compatible server."""
+
+import json
+import logging
+import urllib.error
+import urllib.request
+import wave
+from pathlib import Path
+from typing import List, Optional
+
+from .. import config
+from ..chunking import split_into_chunks
+from .base import BaseTTSClient, ConversionCancelled
+
+logger = logging.getLogger(__name__)
+
+# The 12Hz codec the faster server synthesizes with outputs 24 kHz audio.
+SAMPLE_RATE = 24000
+
+
+class FasterTTSClient(BaseTTSClient):
+    """Generates audio chunks through a faster-qwen3-tts server.
+
+    Talks to the OpenAI-compatible server shipped in the faster-qwen3-tts
+    repository (examples/openai_server.py). The reference voice (ref audio,
+    ref text) and language are configured on the server itself via
+    --ref-audio/--ref-text or a --voices JSON file; this client only sends
+    text. Unlike the Qwen demo, the server performs one generation per
+    request, so long chunks are sub-chunked client-side.
+    """
+
+    def __init__(self, chunks_dir: Path,
+                 voice: Optional[str] = None, api_url: Optional[str] = None,
+                 quiet: bool = False):
+        super().__init__(chunks_dir, quiet=quiet)
+        self.voice = voice or config.FASTER_VOICE
+        self.api_url = (api_url or config.FASTER_API_URL).rstrip("/")
+        self._check_health()
+
+    def _check_health(self) -> None:
+        """Verify the server is reachable and its model is loaded."""
+        url = f"{self.api_url}/health"
+        try:
+            with urllib.request.urlopen(url, timeout=10) as response:
+                payload = json.loads(response.read().decode("utf-8"))
+        except Exception as exc:
+            raise RuntimeError(
+                f"Faster TTS server not reachable at {url}: {exc}. "
+                "Start the faster-qwen3-tts OpenAI-compatible server first "
+                "(see the 'Faster backend' section of the README)."
+            ) from exc
+        if not payload.get("model_loaded"):
+            raise RuntimeError(
+                "The faster TTS server is running but its model is not loaded yet; "
+                "wait for model download and startup to finish, then retry."
+            )
+        self._report(f"[OK] Connected to faster TTS API at {self.api_url} (voice '{self.voice}')")
+        self._report(f"[INFO] The server silently falls back to its first configured voice if "
+                     f"'{self.voice}' is not defined in its voice config (see README).")
+
+    # ------------------------------------------------------------------
+    # HTTP requests
+    # ------------------------------------------------------------------
+
+    def _request_pcm(self, text: str) -> bytes:
+        """POST one sub-chunk and return raw 16-bit mono PCM bytes."""
+        url = f"{self.api_url}/v1/audio/speech"
+        payload = json.dumps({
+            "model": "tts-1",
+            "input": text,
+            "voice": self.voice,
+            "response_format": "pcm",
+        }).encode("utf-8")
+        request = urllib.request.Request(
+            url, data=payload, headers={"Content-Type": "application/json"}, method="POST")
+        try:
+            with urllib.request.urlopen(request, timeout=config.API_TIMEOUT) as response:
+                pcm = response.read()
+        except urllib.error.HTTPError as exc:
+            detail = ""
+            try:
+                detail = exc.read().decode("utf-8", errors="replace")[:200]
+            except Exception:
+                pass
+            raise RuntimeError(f"Faster TTS server returned HTTP {exc.code}: {detail}") from exc
+        except urllib.error.URLError as exc:
+            raise RuntimeError(f"Faster TTS request failed: {exc.reason}") from exc
+        if not pcm:
+            raise RuntimeError("Faster TTS server returned empty audio")
+        return pcm
+
+    # ------------------------------------------------------------------
+    # Chunk generation
+    # ------------------------------------------------------------------
+
+    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
+        """Generate one audio chunk; returns its path in the chunks folder."""
+        try:
+            sub_chunks = split_into_chunks(text, max_words=config.CHUNK_SIZE)
+            if not sub_chunks:
+                raise RuntimeError("No text to synthesize")
+
+            pcm_parts: List[bytes] = []
+            with self._chunk_heartbeat(chunk_num):
+                for sub_num, sub_text in enumerate(sub_chunks, 1):
+                    pcm = self._request_pcm(sub_text)
+                    pcm_parts.append(pcm)
+
+            output_path = self._chunk_path(chunk_num, ".wav")
+            with wave.open(str(output_path), "wb") as wav_file:
+                wav_file.setnchannels(1)
+                wav_file.setsampwidth(2)
+                wav_file.setframerate(SAMPLE_RATE)
+                wav_file.writeframes(b"".join(pcm_parts))
+
+            logger.debug("Chunk %d generated (%d sub-chunks)", chunk_num, len(sub_chunks))
+            return str(output_path)
+
+        except ConversionCancelled:
+            raise
+        except Exception as exc:
+            logger.error("Faster chunk processing failed for chunk %d: %s", chunk_num, exc)
+            return None
diff --git a/app/converter/clients/languages.py b/app/converter/clients/languages.py
new file mode 100644
index 0000000..079dead
--- /dev/null
+++ b/app/converter/clients/languages.py
@@ -0,0 +1,74 @@
+"""Language tables shared by the TTS clients and their UIs."""
+
+from typing import Optional
+
+# Languages the Qwen3-TTS demo accepts as display names (its API silently
+# falls back to "Auto" for anything else, so unknown names are rejected
+# before a run starts instead of mispronouncing a whole book).
+TTS_LANGUAGES = (
+    "Auto", "Chinese", "English", "German", "Italian", "Portuguese",
+    "Spanish", "Japanese", "Korean", "French", "Russian",
+)
+
+# Short aliases accepted on the command line (ISO 639-1 codes and common
+# shorthands), mapped to the display names above.
+TTS_LANGUAGE_ALIASES = {
+    "zh": "Chinese",
+    "en": "English",
+    "de": "German",
+    "it": "Italian",
+    "pt": "Portuguese",
+    "es": "Spanish",
+    "ja": "Japanese",
+    "ko": "Korean",
+    "fr": "French",
+    "ru": "Russian",
+    "zh-cn": "Chinese",
+    "zh-tw": "Chinese",
+    "pt-br": "Portuguese",
+    "en-us": "English",
+    "en-gb": "English",
+}
+
+# Qwen display names -> ISO 639-1 codes, for audio.cpp families whose
+# language request option takes a code instead of a display name. "Auto"
+# has no code and maps to None so the field is omitted and the server
+# applies its own default.
+LANGUAGE_ISO_CODES = {
+    "Chinese": "zh",
+    "English": "en",
+    "German": "de",
+    "Italian": "it",
+    "Portuguese": "pt",
+    "Spanish": "es",
+    "Japanese": "ja",
+    "Korean": "ko",
+    "French": "fr",
+    "Russian": "ru",
+}
+
+
+def normalize_language(value: Optional[str]) -> str:
+    """Normalize a user-provided language name to a Qwen3-TTS display name.
+
+    Accepts the display names in TTS_LANGUAGES case-insensitively as
+    well as the short aliases in TTS_LANGUAGE_ALIASES (ISO 639-1 codes
+    and common shorthands). Raises ValueError for anything else, since the
+    Qwen3-TTS demo silently falls back to "Auto" for unrecognized languages.
+    """
+    if value is None:
+        raise ValueError("Language must not be None")
+    candidate = value.strip()
+    if not candidate:
+        raise ValueError("Language must not be empty")
+    for name in TTS_LANGUAGES:
+        if candidate.lower() == name.lower():
+            return name
+    alias = TTS_LANGUAGE_ALIASES.get(candidate.lower())
+    if alias:
+        return alias
+    raise ValueError(
+        f"Unknown language: {value!r}. Expected one of "
+        f"{', '.join(TTS_LANGUAGES)} (or an alias: "
+        f"{', '.join(sorted(TTS_LANGUAGE_ALIASES))})."
+    )
diff --git a/app/converter/clients/qwen.py b/app/converter/clients/qwen.py
new file mode 100644
index 0000000..354ee04
--- /dev/null
+++ b/app/converter/clients/qwen.py
@@ -0,0 +1,322 @@
+"""Client for the qwen-tts Gradio demo servers (CustomVoice + Base)."""
+
+import io
+import logging
+import shutil
+import sys
+import tempfile
+from pathlib import Path
+from typing import Any, Dict, Optional, Tuple
+
+from .. import config
+from ..audio import concat_audio_files
+from ..chunking import split_into_chunks
+from .base import (BaseTTSClient, ConversionCancelled, resolve_request_seed,
+                   VOICE_MODE_CLONE, VOICE_MODE_CUSTOM, VOICE_MODES)
+from .languages import normalize_language
+from .speakers import speaker_display_name
+
+logger = logging.getLogger(__name__)
+
+# Fixed model facts: both demos run the 1.7B model (the CustomVoice demo
+# takes its full HuggingFace id), and the 12Hz codec outputs 24 kHz audio.
+MODEL_SIZE = "1.7B"
+CUSTOM_VOICE_MODEL_ID = "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice"
+
+
+class QwenTTSClient(BaseTTSClient):
+    """Generates audio chunks through a Qwen3-TTS demo server."""
+
+    def __init__(self, chunks_dir: Path,
+                 voice_mode: str = "custom_voice", voice_clone_ref_audio: Optional[str] = None,
+                 voice_clone_ref_text: Optional[str] = None, skip_transcription: bool = False,
+                 language: Optional[str] = None, api_url: Optional[str] = None,
+                 quiet: bool = False):
+        super().__init__(chunks_dir, quiet=quiet)
+        if voice_mode not in VOICE_MODES:
+            raise ValueError(
+                f"Unknown voice mode: {voice_mode!r} (expected one of {VOICE_MODES})"
+            )
+        self.voice_mode = voice_mode
+        self.voice_clone_ref_audio = voice_clone_ref_audio
+        self.voice_clone_ref_text = (voice_clone_ref_text or "").strip()
+        self.skip_transcription = skip_transcription
+        # api_url overrides the configured endpoint for the active voice mode
+        # (used by the hub's "[remote]" backend entries and --api-url).
+        self.api_url = (api_url or "").strip() or None
+        # Seed sent with every request: config.SEED as-is, or (with
+        # CONSTANT_SEED and SEED < 0) one random value drawn per run and
+        # reused for every request so the voice stays consistent across
+        # chunk boundaries. Without CONSTANT_SEED, -1 is forwarded so the
+        # server re-samples the voice on every generation.
+        self._seed = resolve_request_seed()
+        if language is None:
+            language = config.LANGUAGE
+        # Validate before connecting so bad values fail fast without a server.
+        self.language = normalize_language(language)
+        self.client = None
+        self.api_info: Dict[str, Any] = {}
+        self.clone_client = None
+        self.clone_api_info: Dict[str, Any] = {}
+        self._ref_audio_filedata: Optional[Dict[str, Any]] = None
+        self._connect()
+
+    # ------------------------------------------------------------------
+    # Connection
+    # ------------------------------------------------------------------
+
+    def _connect(self) -> None:
+        api_url = self.api_url or (
+            config.CLONE_API_URL if self.voice_mode == VOICE_MODE_CLONE
+            else config.QWEN_API_URL)
+        try:
+            if self.voice_mode == VOICE_MODE_CLONE:
+                # Voice clone uses the Base-model demo, which is a separate server
+                # from the CustomVoice demo (that one only exposes /run_instruct).
+                self._init_client(api_url, clone=True)
+                self._report(f"[OK] Connected to Voice Clone API at {api_url}")
+                self._resolve_reference_text()
+            else:
+                self._init_client(api_url, clone=False)
+                self._report("[OK] Connected to Qwen API")
+        except Exception as exc:
+            raise RuntimeError(
+                f"Qwen API initialization failed at {api_url}: {exc}. "
+                "Make sure the Qwen demo server is running and reachable, and that your "
+                "installed Qwen3-TTS version matches this converter's API expectations "
+                "(voice clone requires the Base-model demo: Qwen/Qwen3-TTS-12Hz-1.7B-Base)."
+            ) from exc
+
+    def _resolve_reference_text(self) -> None:
+        """Resolve the reference transcript: explicit text, then local
+        transcription, then x-vector-only mode."""
+        if not self.voice_clone_ref_text and self.voice_clone_ref_audio:
+            if self.skip_transcription:
+                self._report("[INFO] Skipping reference audio transcription (--no-transcription).")
+            else:
+                self._report("[INFO] Transcribing reference audio for voice cloning...")
+                self.voice_clone_ref_text = self.transcribe_audio(self.voice_clone_ref_audio) or ""
+        if not self.voice_clone_ref_text:
+            self._report("[WARNING] No reference text available; using "
+                         "x-vector-only clone mode (lower quality).")
+            self._report('          Pass --transcription "..." for higher-quality in-context cloning.')
+        else:
+            self._report(f"[OK] Reference text:\n{self.voice_clone_ref_text}")
+
+    def _init_client(self, url: str, clone: bool = False) -> None:
+        """Initialize a Gradio client and store its API metadata.
+
+        gradio_client prints its usage info directly to stdout while the
+        client is created and its API metadata loaded, so stdout is swapped
+        for a buffer for the whole process; the captured text is re-emitted
+        at DEBUG level for troubleshooting.
+        """
+        from gradio_client import Client
+
+        logger.info("Connecting to Qwen API at %s...", url)
+        old_stdout = sys.stdout
+        captured = io.StringIO()
+        sys.stdout = captured
+        try:
+            try:
+                client = Client(url, httpx_kwargs={"timeout": config.API_TIMEOUT})
+            except TypeError:
+                # Older gradio_client versions don't support httpx_kwargs.
+                client = Client(url)
+            if clone:
+                self.clone_client = client
+                self.clone_api_info = self._load_api_info(client)
+            else:
+                self.client = client
+                self.api_info = self._load_api_info(client)
+        finally:
+            sys.stdout = old_stdout
+        usage_info = captured.getvalue().strip()
+        if usage_info:
+            logger.debug("Gradio client output for %s:\n%s", url, usage_info)
+        logger.info("Connected to Qwen API")
+
+    @staticmethod
+    def _load_api_info(client) -> Dict[str, Any]:
+        """Load available API metadata from the Gradio app."""
+        try:
+            return client.view_api(return_format="dict")
+        except Exception as exc:
+            logger.warning("Unable to read API metadata: %s", exc)
+            return {}
+
+    def _resolve_api_name(self, *candidates: str, api_info: Optional[Dict[str, Any]] = None) -> str:
+        """Return the first available api_name from candidate list."""
+        info = api_info if api_info is not None else self.api_info
+        named_endpoints = info.get("named_endpoints", {})
+        for candidate in candidates:
+            if candidate in named_endpoints:
+                return candidate
+        return candidates[0]
+
+    def _endpoint_accepts_param(self, api_name: str, param_name: str,
+                                api_info: Optional[Dict[str, Any]] = None) -> bool:
+        """Check whether endpoint input schema includes the given parameter."""
+        info = api_info if api_info is not None else self.api_info
+        endpoint = info.get("named_endpoints", {}).get(api_name, {})
+        parameters = endpoint.get("parameters", [])
+        return any(parameter.get("parameter_name") == param_name for parameter in parameters)
+
+    # ------------------------------------------------------------------
+    # Reference audio transcription (voice clone)
+    # ------------------------------------------------------------------
+
+    def transcribe_audio(self, audio_path: str) -> Optional[str]:
+        """Transcribe reference audio locally using an optional Whisper backend."""
+        from .transcribe import transcribe_reference_audio
+        return transcribe_reference_audio(audio_path)
+
+    # ------------------------------------------------------------------
+    # Chunk generation
+    # ------------------------------------------------------------------
+
+    def generate_chunk(self, text: str, chunk_num: int) -> Optional[str]:
+        """Generate one audio chunk; returns its path in the chunks folder.
+
+        The text is split into sub-requests of at most
+        ``config.CHUNK_SIZE`` words each (the book-level chunker
+        normally guarantees this already; the split is defense in depth
+        against pathological input such as a punctuation-free run of
+        text), and the audio files returned for the sub-requests are
+        concatenated into one chunk file.
+        """
+        try:
+            sub_texts = split_into_chunks(text, max_words=config.CHUNK_SIZE)
+            if not sub_texts:
+                raise RuntimeError("No text to synthesize")
+
+            output_path: Optional[Path] = None
+            with tempfile.TemporaryDirectory(prefix="tts_parts_") as parts_dir, \
+                    self._chunk_heartbeat(chunk_num):
+                part_paths = [
+                    self._generate_sub_request(sub_text, parts_dir, sub_num,
+                                                len(sub_texts), chunk_num)
+                    for sub_num, sub_text in enumerate(sub_texts, 1)
+                ]
+                if len(part_paths) == 1:
+                    suffix = part_paths[0].suffix or ".wav"
+                    output_path = self._chunk_path(chunk_num, suffix)
+                    shutil.copy2(part_paths[0], output_path)
+                else:
+                    output_path = self._chunk_path(chunk_num, ".wav")
+                    concat_audio_files(part_paths, output_path)
+
+            logger.debug("Chunk %d generated successfully (%d sub-request(s))",
+                         chunk_num, len(sub_texts))
+            return str(output_path)
+
+        except ConversionCancelled:
+            raise
+        except Exception as exc:
+            logger.error("Qwen chunk processing failed for chunk %d: %s", chunk_num, exc)
+            return None
+
+    def _generate_sub_request(self, text: str, parts_dir: str, sub_num: int,
+                              sub_total: int, chunk_num: int) -> Path:
+        """Run one API generation for ``text``; returns the downloaded audio."""
+        if sub_total > 1:
+            logger.info("Chunk %d: oversized input split into %d requests "
+                        "(sub-request %d/%d)", chunk_num, sub_total, sub_num, sub_total)
+        if self.voice_mode == VOICE_MODE_CUSTOM:
+            result = self._generate_custom_voice(text)
+        elif self.voice_mode == VOICE_MODE_CLONE:
+            result = self._generate_voice_clone(text)
+        else:
+            raise ValueError(f"Unknown voice mode: {self.voice_mode}")
+
+        if not isinstance(result, (tuple, list)) or not result:
+            raise RuntimeError("Qwen API returned an invalid result")
+
+        audio_path = result[0]  # First element is the audio file path
+        if not isinstance(audio_path, (str, Path)) or not audio_path:
+            raise RuntimeError("Qwen API did not return an audio file path")
+
+        source = Path(audio_path)
+        if not source.exists():
+            raise RuntimeError(f"Generated audio file not found: {audio_path}")
+
+        destination = Path(parts_dir) / f"part_{sub_num:02d}{source.suffix or '.wav'}"
+        shutil.copy2(source, destination)
+
+        return destination
+
+    # ------------------------------------------------------------------
+    # API payloads
+    # ------------------------------------------------------------------
+
+    def _generate_custom_voice(self, text: str) -> Tuple:
+        """Generate audio using CustomVoice mode."""
+        custom_api = self._resolve_api_name("/run_instruct", "/run_custom_voice", "/generate_custom_voice")
+        if custom_api == "/run_instruct":
+            payload = dict(
+                text=text,
+                lang_disp=self.language,
+                spk_disp=speaker_display_name(),
+                instruct=config.INSTRUCT,
+            )
+        else:
+            payload = dict(
+                text=text,
+                language=self.language,
+                speaker=config.SPEAKER,
+                instruct=config.INSTRUCT,
+            )
+            if self._endpoint_accepts_param(custom_api, "model_id_cv"):
+                payload["model_id_cv"] = CUSTOM_VOICE_MODEL_ID
+            elif self._endpoint_accepts_param(custom_api, "model_size"):
+                payload["model_size"] = MODEL_SIZE
+
+            if self._endpoint_accepts_param(custom_api, "seed"):
+                payload["seed"] = self._seed
+
+        return self.client.predict(**payload, api_name=custom_api)
+
+    def _ref_audio_payload(self) -> Dict[str, Any]:
+        """Gradio file payload for the reference audio (built once, reused)."""
+        if self._ref_audio_filedata is None:
+            from gradio_client import handle_file
+            self._ref_audio_filedata = handle_file(self.voice_clone_ref_audio)
+        return self._ref_audio_filedata
+
+    def _generate_voice_clone(self, text: str) -> Tuple:
+        """Generate audio using Voice Clone mode."""
+        if not Path(self.voice_clone_ref_audio).exists():
+            raise FileNotFoundError(f"Reference audio not found: {self.voice_clone_ref_audio}")
+
+        if self.clone_client is None:
+            raise RuntimeError("Voice Clone client is not initialized. Is the Base-model demo running?")
+
+        clone_api = self._resolve_api_name("/run_voice_clone", "/generate_voice_clone",
+                                           api_info=self.clone_api_info)
+        use_xvector = config.XVECTOR_ONLY or not self.voice_clone_ref_text
+
+        if clone_api == "/run_voice_clone":
+            payload = dict(
+                ref_aud=self._ref_audio_payload(),
+                ref_txt=self.voice_clone_ref_text,
+                use_xvec=use_xvector,
+                text=text,
+                lang_disp=self.language,
+            )
+        else:
+            payload = dict(
+                ref_audio=self._ref_audio_payload(),
+                ref_text=self.voice_clone_ref_text,
+                target_text=text,
+                language=self.language,
+                use_xvector_only=use_xvector,
+            )
+            optional_params = {
+                "model_size": MODEL_SIZE,
+                "seed": self._seed,
+            }
+            for name, value in optional_params.items():
+                if self._endpoint_accepts_param(clone_api, name, api_info=self.clone_api_info):
+                    payload[name] = value
+
+        return self.clone_client.predict(**payload, api_name=clone_api)
diff --git a/app/converter/clients/speakers.py b/app/converter/clients/speakers.py
new file mode 100644
index 0000000..eecd52a
--- /dev/null
+++ b/app/converter/clients/speakers.py
@@ -0,0 +1,57 @@
+"""Qwen3-TTS built-in speaker names and their wire (display) forms."""
+
+from typing import Optional
+
+from .. import config
+
+# Built-in CustomVoice speaker names for the Qwen3-TTS family. Shared by the
+# qwen-tts demo backend (config.SPEAKER, the qwen setup/form) and the
+# audio.cpp audiocpp backend's CustomVoice entry (the Convert form's Speaker
+# picker). Entries are the canonical/config form; speaker_display_name()
+# maps them to the wire (display) form via SPEAKER_DISPLAY_NAMES below.
+QWEN3_TTS_SPEAKERS = ("Vivian", "Serena", "Uncle_Fu", "Dylan", "Eric",
+                      "Ryan", "Aiden", "Ono_Anna", "Sohee")
+
+# Canonical speaker names -> display names used by the qwen-tts demo.
+SPEAKER_DISPLAY_NAMES = {
+    "ryan": "Ryan",
+    "serena": "Serena",
+    "vivian": "Vivian",
+    "uncle_fu": "Uncle Fu",
+    "aiden": "Aiden",
+    "ono_anna": "Ono Anna",
+    "sohee": "Sohee",
+    "eric": "Eric",
+    "dylan": "Dylan",
+}
+
+
+def speaker_display_name_for(name: str) -> str:
+    """Return the wire (display) form of a Qwen3-TTS CustomVoice speaker NAME.
+
+    Accepts either the canonical/config form (e.g. "uncle_fu", "Uncle_Fu")
+    or the display form ("Uncle Fu"), case-insensitively; unknown names pass
+    through unchanged. Used by AudioCppTTSClient to normalize the --voice /
+    Speaker-picker value into what audiocpp_server expects in the request's
+    voice field.
+    """
+    return SPEAKER_DISPLAY_NAMES.get((name or "").lower(), name)
+
+
+def is_builtin_speaker(name: Optional[str]) -> bool:
+    """True when NAME is one of the Qwen3-TTS CustomVoice built-in speakers.
+
+    Matches case-insensitively across the canonical ("Uncle_Fu"), display
+    ("Uncle Fu") and shorthand ("uncle_fu") forms, so the --voice flag and
+    the Convert form's Speaker picker resolve to the same set.
+    """
+    if not name:
+        return False
+    norm = name.lower().replace("_", " ").replace("-", " ")
+    return any(norm == speaker.lower().replace("_", " ")
+               for speaker in QWEN3_TTS_SPEAKERS)
+
+
+def speaker_display_name() -> str:
+    """Return the display name for the configured custom speaker."""
+    return speaker_display_name_for(config.SPEAKER)
diff --git a/app/converter/clients/transcribe.py b/app/converter/clients/transcribe.py
new file mode 100644
index 0000000..d2db9f1
--- /dev/null
+++ b/app/converter/clients/transcribe.py
@@ -0,0 +1,54 @@
+"""Optional local Whisper transcription of reference audio."""
+
+import logging
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+
+def transcribe_reference_audio(audio_path: str, model_name: str = "base") -> Optional[str]:
+    """Transcribe reference audio locally using an optional Whisper backend.
+
+    The current qwen-tts demo does not expose a transcription endpoint, so
+    transcription is done client-side when a Whisper package is available.
+    Returns None if no backend is installed.
+    """
+    for backend in ("faster_whisper", "whisper"):
+        try:
+            if backend == "faster_whisper":
+                from faster_whisper import WhisperModel
+                model = WhisperModel(model_name, device="cpu", compute_type="int8")
+                segments, _ = model.transcribe(audio_path)
+                text = " ".join(seg.text.strip() for seg in segments).strip()
+            else:
+                import whisper
+                model = whisper.load_model(model_name)
+                result = model.transcribe(audio_path)
+                text = (result.get("text") or "").strip()
+            if text:
+                logger.info("Transcription complete via %s: %s", backend, text)
+                return text
+        except ImportError:
+            continue
+        except Exception as exc:
+            logger.warning("%s transcription failed: %s", backend, exc)
+    logger.warning("No Whisper backend available; transcription skipped.")
+    return None
+
+
+def whisper_backend_available() -> Optional[str]:
+    """Return the name of an importable Whisper backend, or None.
+
+    Checks faster_whisper first (preferred), then the openai-whisper
+    package, without importing the heavy model code: a bare import probe
+    is enough to tell whether the package is installed in the current
+    environment. Used by the make_audiocpp_server_json tool to warn when
+    neither is present (e.g. the wrong conda environment is active).
+    """
+    for backend in ("faster_whisper", "whisper"):
+        try:
+            __import__(backend)
+        except ImportError:
+            continue
+        return backend
+    return None
diff --git a/app/converter/converter.py b/app/converter/converter.py
index 1abc85c..48d4987 100644
--- a/app/converter/converter.py
+++ b/app/converter/converter.py
@@ -15,7 +15,7 @@ from typing import Callable, Dict, List, Optional, Tuple
 
 from . import audio, chunking, config, cover, extractors
 from .audio import TrackMeta
-from .tts import (
+from .clients import (
     BACKENDS,
     BACKEND_AUDIOCPP,
     BACKEND_FASTER,
@@ -228,7 +228,8 @@ class AudiobookConverter:
         if backend == BACKEND_FASTER:
             # The faster backend always voice-clones using a reference voice
             # configured on the server, so no local reference audio is needed.
-            self.tts = FasterTTSClient(voice=voice, api_url=api_url,
+            self.tts = FasterTTSClient(chunks_dir=CHUNKS_FOLDER,
+                                       voice=voice, api_url=api_url,
                                        quiet=quiet)
         elif backend == BACKEND_AUDIOCPP:
             # --voice picks the voice: a built-in speaker name on the
@@ -237,13 +238,15 @@ class AudiobookConverter:
             # multi-model servers; instructions describe or style the
             # voice, request_options pass per-model controls through to
             # the server.
-            self.tts = AudioCppTTSClient(voice=voice, language=self.language,
+            self.tts = AudioCppTTSClient(chunks_dir=CHUNKS_FOLDER,
+                                         voice=voice, language=self.language,
                                          model_id=model_id,
                                          instructions=instructions,
                                          request_options=self.request_options,
                                          api_url=api_url, quiet=quiet)
         else:
             self.tts = QwenTTSClient(
+                chunks_dir=CHUNKS_FOLDER,
                 voice_mode=voice_mode,
                 voice_clone_ref_audio=voice_clone_ref_audio,
                 voice_clone_ref_text=voice_clone_ref_text,
@@ -398,7 +401,7 @@ class AudiobookConverter:
             self.current_outputs = []
             # Start from a clean scratch folder so a previous crash can never
             # affect this run
-            audio.cleanup_chunks()
+            audio.cleanup_chunks(CHUNKS_FOLDER)
 
             logger.info("Extracting text...")
             book = extractors.extract_book(file_path)
@@ -476,7 +479,7 @@ class AudiobookConverter:
             return False
         finally:
             # Always cleanup, even on failure or interrupt
-            audio.cleanup_chunks()
+            audio.cleanup_chunks(CHUNKS_FOLDER)
 
     def _convert_m4b_with_chapters(self, sections, stem: str, start_time: float,
                                    meta: Optional[TrackMeta] = None,
@@ -519,7 +522,9 @@ class AudiobookConverter:
             return False
 
         output_path = AUDIOBOOKS_FOLDER / f"{stem}.{self.output_format}"
-        if not audio.combine_chapters_to_m4b(chapter_files, titles, output_path, speed=self.speed,
+        if not audio.combine_chapters_to_m4b(chapter_files, titles, output_path,
+                                             chunks_dir=CHUNKS_FOLDER,
+                                             speed=self.speed,
                                              meta=meta, cover=cover):
             return False
         duration = time.time() - start_time
@@ -653,7 +658,9 @@ class AudiobookConverter:
                              successful_chunks, total_chunks)
                 return False
 
-            success = audio.combine_chunks(total_chunks, output_path, chunk_results=results,
+            success = audio.combine_chunks(total_chunks, output_path,
+                                           chunk_results=results,
+                                           chunks_dir=CHUNKS_FOLDER,
                                            speed=speed, output_format=output_format,
                                            intermediate=chapter is not None,
                                            meta=meta, cover=cover)