mARTin-B78
295de3059d
- generate_voices.py: scan /config/speakers and /voices recursively, support .ogg and .m4a (M4A auto-converted via ffmpeg), sanitise voice IDs - auto_transcribe.py: scan both host paths recursively, support all formats, use parakeet-asr on port 8010 - docker-compose.yml: mount /home/sparky/Projekte/TTS_Voices/speakers as /voices, add faster-qwen3-tts-voicedesign service on port 8021 - run_voicedesign_server.py: OpenAI-compatible server for VoiceDesign model - voicedesign_voices.json: 8 British/German VoiceDesign voices Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
import os
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import requests
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import json
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# Host-side paths (this script runs on the host, not inside the container)
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SCAN_DIRS = [
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"/home/sparky/Docker/faster-qwen3-tts/config/speakers",
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"/home/sparky/Projekte/TTS_Voices/speakers",
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]
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AUDIO_EXTS = (".wav", ".mp3", ".ogg", ".m4a")
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SKIP_DIRS = {"originals_backup", "xtts_multi_voice_sets", "txt"}
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whisper_api_url = "http://localhost:8010/v1/audio/transcriptions"
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for scan_dir in SCAN_DIRS:
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if not os.path.exists(scan_dir):
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print(f"Skipping {scan_dir} (not found)")
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continue
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print(f"\nScanning {scan_dir} for missing transcripts...")
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for root, dirs, files in os.walk(scan_dir):
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dirs[:] = sorted(d for d in dirs if d not in SKIP_DIRS)
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for filename in sorted(files):
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if not filename.lower().endswith(AUDIO_EXTS):
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continue
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base_name = os.path.splitext(filename)[0]
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ref_txt_path = os.path.join(root, f"{base_name}.reference.txt")
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audio_path = os.path.join(root, filename)
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if os.path.exists(ref_txt_path):
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continue
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print(f"Transcribing: {os.path.relpath(audio_path, scan_dir)}")
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try:
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with open(audio_path, "rb") as audio_file:
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response = requests.post(
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whisper_api_url,
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files={"file": (filename, audio_file)},
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data={"model": "large-v3", "response_format": "text"},
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)
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if response.status_code == 200:
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transcript = response.text.strip()
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if transcript.startswith("{"):
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try:
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transcript = json.loads(transcript).get("text", transcript).strip()
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except json.JSONDecodeError:
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pass
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with open(ref_txt_path, "w", encoding="utf-8") as f:
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f.write(transcript)
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print(f" ✓ {transcript[:80]}")
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else:
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print(f" ✗ API error {response.status_code}: {response.text}")
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except requests.exceptions.ConnectionError:
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print(f" ✗ Cannot reach Whisper API at {whisper_api_url}")
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raise SystemExit(1)
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except Exception as e:
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print(f" ✗ Error on {filename}: {e}")
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print("\nBatch transcription complete.")
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