1 files changed, 121 insertions, 0 deletions
diff --git a/tools/make_faster_voices_json.py b/tools/make_faster_voices_json.py
new file mode 100755
index 0000000..2e00f72
--- /dev/null
+++ b/tools/make_faster_voices_json.py
@@ -0,0 +1,121 @@
+#!/usr/bin/env python3
+"""Generate a voices.json file for the faster-qwen3-tts server.
+
+Scans a directory for .wav files, transcribes each with a local Whisper
+backend (faster_whisper or whisper), and writes a voices.json
+
+Usage:
+    python tools/make_faster_voices_json.py INPUT_DIR [--output PATH]
+                                               [--language LANG]
+                                               [--whisper-model NAME] [--force]
+
+The output can be passed to the faster server:
+    python examples/openai_server.py --voices voices.json --port 8000
+"""
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+# Allow running from any working directory.
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+
+from converter.tts import normalize_language, transcribe_reference_audio
+
+
+def find_wav_files(input_dir: Path) -> list:
+    """Return the .wav files in INPUT_DIR, sorted alphabetically by name."""
+    return sorted(
+        (path for path in input_dir.iterdir()
+         if path.is_file() and path.suffix.lower() == ".wav"),
+        key=lambda path: path.name.lower(),
+    )
+
+
+def prompt_overwrite(output_path: Path) -> bool:
+    """Ask whether to overwrite an existing output file."""
+    while True:
+        try:
+            answer = input(f"{output_path} already exists. Overwrite? (y/n): ").strip().lower()
+        except EOFError:
+            print("\n[WARNING] No interactive input available; keeping existing file")
+            return False
+        if answer in ("y", "yes"):
+            return True
+        if answer in ("n", "no"):
+            return False
+        print("Please answer 'y' or 'n'.")
+
+
+def build_voices(wav_files: list, language: str, whisper_model: str) -> dict:
+    """Transcribe each wav file and build the voices mapping."""
+    voices = {}
+    for wav_file in wav_files:
+        name = wav_file.stem
+        print(f"[INFO] Transcribing {wav_file.name} (voice '{name}')...")
+        text = transcribe_reference_audio(str(wav_file), model_name=whisper_model)
+        if text:
+            print(f"[OK] {name}: {text}")
+        else:
+            print(f"[WARNING] No transcript for '{name}'; the faster backend "
+                  "strongly recommends an accurate transcript — consider editing "
+                  "voices.json by hand before starting the server")
+        voices[name] = {
+            "ref_audio": str(wav_file.resolve()),
+            "ref_text": text or "",
+            "language": language,
+        }
+    return voices
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="Generate a voices.json for the faster-qwen3-tts server "
+                    "from a directory of .wav reference files.")
+    parser.add_argument("input_dir", type=Path,
+                        help="Directory containing .wav reference audio files")
+    parser.add_argument("--output", type=Path, default=None,
+                        help="Output path for voices.json "
+                             "(default: INPUT_DIR/voices.json)")
+    parser.add_argument("--language", type=str, default="English",
+                        help="Language for all voices, as passed to the TTS model "
+                             "(default: English; names and short codes accepted)")
+    parser.add_argument("--whisper-model", type=str, default="base",
+                        help="Whisper model size for transcription "
+                             "(default: base)")
+    parser.add_argument("--force", action="store_true",
+                        help="Overwrite the output file without prompting")
+    args = parser.parse_args()
+
+    try:
+        language = normalize_language(args.language)
+    except ValueError as exc:
+        parser.error(str(exc))
+
+    if not args.input_dir.is_dir():
+        parser.error(f"Input directory not found: {args.input_dir}")
+
+    wav_files = find_wav_files(args.input_dir)
+    if not wav_files:
+        parser.error(f"No .wav files found in {args.input_dir}")
+
+    output_path = args.output if args.output is not None \
+        else args.input_dir / "voices.json"
+    if output_path.exists() and not args.force and not prompt_overwrite(output_path):
+        print("[INFO] Aborted; existing voices.json kept")
+        return 1
+
+    voices = build_voices(wav_files, language, args.whisper_model)
+
+    with output_path.open("w", encoding="utf-8") as handle:
+        json.dump(voices, handle, indent=4, ensure_ascii=False)
+        handle.write("\n")
+
+    print(f"[OK] Wrote {output_path} with {len(voices)} voice(s): "
+          f"{', '.join(voices)}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())