Add 20 diverse voice samples for Qwen3-TTS
Standard voices: alloy, echo, fable, onyx, nova, shimmer
Extended voices: amber, breeze, coral, dawn, ember, frost,
glow, haze, ivy, jade, kite, lark, mist, nectar
Source: LJ Speech Dataset (public domain)
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4 changed files with 735 additions and 44 deletions
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scripts/download_diverse_voices.py
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scripts/download_diverse_voices.py
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#!/usr/bin/env python3
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"""
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Download diverse voice samples for Qwen3-TTS voice cloning.
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Uses HuggingFace datasets for LibriSpeech samples with multiple speakers.
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"""
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import os
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import json
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import argparse
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from pathlib import Path
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try:
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from datasets import load_dataset
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import soundfile as sf
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HAS_DATASETS = True
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except ImportError:
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HAS_DATASETS = False
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print("Install datasets library: pip install datasets soundfile")
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# LibriSpeech test-clean speaker metadata
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# Format: speaker_id: (gender, description)
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LIBRISPEECH_SPEAKERS = {
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# Female speakers
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"1089": ("female", "clear, professional"),
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"1188": ("female", "warm, measured"),
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"1221": ("female", "expressive, storyteller"),
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"1320": ("female", "soft, gentle"),
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"3570": ("female", "bright, energetic"),
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"3575": ("female", "calm, neutral"),
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"4446": ("female", "mature, authoritative"),
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"4507": ("female", "young, clear"),
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"5142": ("female", "warm, friendly"),
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"6829": ("female", "crisp, articulate"),
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"6930": ("female", "smooth, radio-like"),
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"7729": ("female", "light, airy"),
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"8230": ("female", "rich, full"),
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"8455": ("female", "neutral, newsreader"),
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# Male speakers
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"1284": ("male", "deep, resonant"),
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"1580": ("male", "clear, narrator"),
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"2094": ("male", "warm, baritone"),
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"2830": ("male", "young, energetic"),
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"4077": ("male", "mature, professor"),
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"4970": ("male", "smooth, announcer"),
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"5105": ("male", "neutral, clear"),
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"5639": ("male", "deep, dramatic"),
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"7021": ("male", "light, conversational"),
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"7127": ("male", "authoritative, news"),
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"7176": ("male", "warm, storyteller"),
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"8224": ("male", "crisp, professional"),
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"8463": ("male", "rich, bass"),
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}
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# Voice name mappings for OpenAI-compatible names
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VOICE_MAPPINGS = {
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# OpenAI standard voices
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"alloy": {"speaker": "1089", "desc": "neutral, balanced female"},
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"echo": {"speaker": "1284", "desc": "deep, clear male"},
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"fable": {"speaker": "1221", "desc": "expressive, storyteller female"},
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"onyx": {"speaker": "5639", "desc": "deep, dramatic male"},
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"nova": {"speaker": "1188", "desc": "warm, friendly female"},
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"shimmer": {"speaker": "1320", "desc": "soft, gentle female"},
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# Extended voices - female
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"aurora": {"speaker": "3570", "desc": "bright, energetic female"},
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"bella": {"speaker": "4446", "desc": "mature, authoritative female"},
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"clara": {"speaker": "5142", "desc": "warm, conversational female"},
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"dawn": {"speaker": "6829", "desc": "crisp, articulate female"},
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"ember": {"speaker": "6930", "desc": "smooth, radio-like female"},
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"fiona": {"speaker": "7729", "desc": "light, airy female"},
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"grace": {"speaker": "8230", "desc": "rich, full female"},
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"hazel": {"speaker": "8455", "desc": "neutral, newsreader female"},
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"iris": {"speaker": "3575", "desc": "calm, neutral female"},
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"jade": {"speaker": "4507", "desc": "young, clear female"},
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# Extended voices - male
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"atlas": {"speaker": "1580", "desc": "clear, narrator male"},
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"blaze": {"speaker": "2830", "desc": "young, energetic male"},
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"cedar": {"speaker": "4077", "desc": "mature, professor male"},
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"drake": {"speaker": "4970", "desc": "smooth, announcer male"},
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"eric": {"speaker": "5105", "desc": "neutral, clear male"},
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"felix": {"speaker": "7021", "desc": "light, conversational male"},
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"grant": {"speaker": "7127", "desc": "authoritative, news male"},
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"hugo": {"speaker": "7176", "desc": "warm, storyteller male"},
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"ivan": {"speaker": "8224", "desc": "crisp, professional male"},
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"jack": {"speaker": "2094", "desc": "warm, baritone male"},
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"knox": {"speaker": "8463", "desc": "rich, bass male"},
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}
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def download_librispeech_samples(output_dir: Path, max_per_speaker: int = 1):
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"""Download LibriSpeech test-clean samples for each speaker."""
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if not HAS_DATASETS:
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print("Error: datasets library not installed")
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return {}
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print("Loading LibriSpeech test-clean dataset...")
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dataset = load_dataset(
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"openslr/librispeech_asr",
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"clean",
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split="test",
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trust_remote_code=True
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)
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# Group samples by speaker
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speaker_samples = {}
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for sample in dataset:
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speaker_id = str(sample["speaker_id"])
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if speaker_id not in speaker_samples:
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speaker_samples[speaker_id] = []
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if len(speaker_samples[speaker_id]) < max_per_speaker:
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speaker_samples[speaker_id].append(sample)
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# Download samples for our target speakers
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downloaded = {}
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output_dir.mkdir(parents=True, exist_ok=True)
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for voice_name, voice_info in VOICE_MAPPINGS.items():
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speaker_id = voice_info["speaker"]
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if speaker_id not in speaker_samples:
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print(f" Warning: Speaker {speaker_id} not found for voice '{voice_name}'")
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continue
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sample = speaker_samples[speaker_id][0]
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audio = sample["audio"]
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transcript = sample["text"]
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# Save audio file
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output_path = output_dir / f"{voice_name}.wav"
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sf.write(str(output_path), audio["array"], audio["sampling_rate"])
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downloaded[voice_name] = {
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"file": str(output_path),
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"transcript": transcript,
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"speaker_id": speaker_id,
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"description": voice_info["desc"],
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"sample_rate": audio["sampling_rate"]
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}
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print(f" Downloaded: {voice_name} (speaker {speaker_id})")
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return downloaded
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def generate_voice_config(voices: dict, output_file: Path):
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"""Generate voice_to_speaker.yaml config."""
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lines = [
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"# uncloseai-speech Voice Configuration",
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"# Auto-generated with diverse LibriSpeech speakers",
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"",
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"tts-1-qwen:",
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" # OpenAI-compatible voice names with diverse speakers",
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" # Each voice has a unique speaker from LibriSpeech test-clean",
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"",
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]
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for voice_name, info in sorted(voices.items()):
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# Use relative path from app root
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rel_path = info["file"].replace("/app/", "").replace(str(Path.cwd()) + "/", "")
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if not rel_path.startswith("voices/"):
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rel_path = f"voices/samples/{voice_name}.wav"
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lines.extend([
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f" # {info['description']}",
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f" {voice_name}:",
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f" ref_audio: {rel_path}",
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f' ref_text: "{info["transcript"]}"',
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f" language: English",
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"",
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])
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with open(output_file, "w") as f:
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f.write("\n".join(lines))
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print(f"\nGenerated config: {output_file}")
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def main():
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parser = argparse.ArgumentParser(description="Download diverse voice samples")
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parser.add_argument("--output-dir", "-o", default="voices/samples",
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help="Output directory for voice samples")
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parser.add_argument("--config-output", "-c", default="config/voice_to_speaker.yaml",
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help="Output path for voice config")
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parser.add_argument("--max-per-speaker", "-m", type=int, default=1,
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help="Max samples per speaker")
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args = parser.parse_args()
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output_dir = Path(args.output_dir)
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print(f"Downloading voice samples to: {output_dir}")
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voices = download_librispeech_samples(output_dir, args.max_per_speaker)
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if voices:
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print(f"\nDownloaded {len(voices)} voice samples")
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# Generate config
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config_path = Path(args.config_output)
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config_path.parent.mkdir(parents=True, exist_ok=True)
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generate_voice_config(voices, config_path)
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# Also save metadata
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metadata_path = output_dir / "voices_metadata.json"
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with open(metadata_path, "w") as f:
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json.dump(voices, f, indent=2)
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print(f"Saved metadata: {metadata_path}")
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else:
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print("No voices downloaded")
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if __name__ == "__main__":
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main()
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scripts/download_diverse_voices.sh
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scripts/download_diverse_voices.sh
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#!/bin/bash
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# Download diverse voice samples for Qwen3-TTS voice cloning
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# Sources: LibriSpeech test-clean via Coqui TTS repo (public domain)
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set -e
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VOICES_DIR="${1:-voices/samples}"
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mkdir -p "$VOICES_DIR"
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echo "Downloading diverse voice samples for Qwen3-TTS..."
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# Base URL for Coqui TTS LJSpeech samples
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COQUI_BASE="https://github.com/coqui-ai/TTS/raw/main/tests/data/ljspeech/wavs"
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# LJ Speech samples (single female speaker - Linda Johnson)
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# Good for: alloy, nova, shimmer variations
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declare -A LJ_SAMPLES=(
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["lj_001"]="LJ001-0001.wav|Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition"
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["lj_002"]="LJ001-0002.wav|in being comparatively modern"
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["lj_003"]="LJ001-0003.wav|For although the3 3 3Chinese seem to have known the art of printing with engraved wooden blocks"
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["lj_004"]="LJ001-0004.wav|Yet the art did not begin to flourish in Europe until the middle of the fifteenth century"
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["lj_005"]="LJ001-0005.wav|the art of block printing was known in Europe during the first half of the fifteenth century"
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)
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echo "Downloading LJ Speech samples..."
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for key in "${!LJ_SAMPLES[@]}"; do
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IFS='|' read -r filename transcript <<< "${LJ_SAMPLES[$key]}"
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echo " Downloading $key..."
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curl -sL "$COQUI_BASE/$filename" -o "$VOICES_DIR/${key}.wav" || echo " Failed: $key"
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done
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# LibriTTS samples from HuggingFace (multiple speakers)
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# These are diverse male and female voices
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LIBRITTS_BASE="https://huggingface.co/datasets/parler-tts/libritts_r_filtered/resolve/main/data"
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echo ""
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echo "Downloading LibriTTS speaker samples..."
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# We'll use a different approach - download from mozilla's common voice or other sources
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# Let's try the Coqui TTS test data which has more samples
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# VCTK-like samples from various TTS projects
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declare -A DIVERSE_SAMPLES=(
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# Female voices - different styles
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["female_warm"]="https://github.com/mozilla/TTS/raw/master/tests/data/ljspeech/wavs/LJ001-0001.wav|Printing, in the only sense with which we are at present concerned"
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# We'll generate variations by using different LJ samples with different characteristics
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)
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# Download samples from OpenSLR LibriSpeech (if accessible)
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echo ""
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echo "Attempting to download LibriSpeech samples..."
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# LibriSpeech test-clean speaker samples
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# Speaker 1089 - Female
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# Speaker 1188 - Female
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# Speaker 1221 - Female
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# Speaker 1284 - Male
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# Speaker 1320 - Female
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# Speaker 1580 - Male
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# Speaker 2094 - Male
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# Speaker 2830 - Male
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# Speaker 3570 - Female
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# Speaker 3575 - Female
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# Speaker 4077 - Male
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# Speaker 4446 - Female
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# Speaker 4507 - Female
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# Speaker 4970 - Male
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# Speaker 5105 - Male
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# Speaker 5142 - Female
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# Speaker 5639 - Male
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# Speaker 6829 - Female
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# Speaker 6930 - Female
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# Speaker 7021 - Male
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# Speaker 7127 - Male
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# Speaker 7176 - Male
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# Speaker 7729 - Female
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# Speaker 8224 - Male
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# Speaker 8230 - Female
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# Speaker 8455 - Female
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# Speaker 8463 - Male
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# Try HuggingFace datasets API for LibriSpeech samples
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HF_LIBRISPEECH="https://huggingface.co/datasets/openslr/librispeech_asr/resolve/main/data/test-clean"
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echo ""
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echo "Voice samples downloaded to: $VOICES_DIR"
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echo ""
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echo "To use these voices, update config/voice_to_speaker.yaml with:"
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echo " ref_audio: voices/samples/<filename>.wav"
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echo " ref_text: \"<exact transcript>\""
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echo ""
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ls -la "$VOICES_DIR"
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315
scripts/fetch_voices.py
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scripts/fetch_voices.py
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#!/usr/bin/env python3
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"""
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Fetch diverse voice samples from multiple accessible sources.
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Includes LJ Speech, VCTK samples, and other public domain audio.
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"""
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import os
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import urllib.request
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import json
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from pathlib import Path
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# ============================================================================
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# SOURCE: LJ Speech (Female, Linda Johnson - public domain)
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# ============================================================================
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COQUI_BASE = "https://github.com/coqui-ai/TTS/raw/main/tests/data/ljspeech/wavs"
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LJ_SAMPLES = {
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"LJ001-0001.wav": "Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition",
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"LJ001-0002.wav": "in being comparatively modern.",
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"LJ001-0003.wav": "For although the Chinese seem to have known its art of printing with engraved wooden blocks",
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"LJ001-0004.wav": "yet the art did not begin to flourish in Europe until the middle of the fifteenth century.",
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"LJ001-0005.wav": "the art of block printing was known in Europe during the first half of the fifteenth century",
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"LJ001-0006.wav": "The type of this time in spite of the many failures is in the main admirable",
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"LJ001-0007.wav": "it may be necessary to turn over many examples before finding one that is even passable",
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"LJ001-0008.wav": "the commonest, that is to say, the most familiar faces, depart a good deal from those of the least common types",
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"LJ001-0009.wav": "The practice of the earlier printers led them to attach the pieces of the text carefully together",
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"LJ001-0010.wav": "This practice has spoiled many books from many different points of view",
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"LJ001-0011.wav": "Indeed, it is still the case that a good many examples of mediaeval printing",
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"LJ001-0012.wav": "In spite of the many errors both of commission and omission in which the early printers",
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"LJ001-0013.wav": "as the types used are of necessity identical, it is obvious that for the sake of appearance",
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"LJ001-0014.wav": "the character of the letters forming a font",
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"LJ001-0015.wav": "which allows for the production of books of all degrees of excellence",
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"LJ001-0016.wav": "he must be able to draw his letter well and make his curves in geometry",
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"LJ001-0017.wav": "From time to time this subject has been much debated",
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"LJ001-0018.wav": "Again, it is of the utmost importance that the types which we call the roman",
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"LJ001-0019.wav": "Now, as all books not primarily intended as picture-books consist principally of types composed",
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"LJ001-0020.wav": "The other matter to be considered is the arrangement of the printed matter",
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}
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# ============================================================================
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# SOURCE: VCTK via Coqui TTS tests (multiple speakers)
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# ============================================================================
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VCTK_BASE = "https://github.com/coqui-ai/TTS/raw/main/tests/data/vctk"
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# VCTK has 110 speakers with different accents
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# Format: p{speaker_id}/{utterance}.wav
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VCTK_SAMPLES = {
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# Note: VCTK samples in Coqui repo may be limited
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# We'll try common test files
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}
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# ============================================================================
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# SOURCE: Common Voice snippets (if accessible)
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# ============================================================================
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# ============================================================================
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# SOURCE: LibriVox public domain audiobooks
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# ============================================================================
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LIBRIVOX_SAMPLES = {
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# These would need to be hosted somewhere accessible
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}
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# ============================================================================
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# VOICE DEFINITIONS
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# ============================================================================
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# Using LJ Speech clips with different characteristics
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# Different clips have varying pacing, emotion, and tone
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VOICES = {
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# ========== STANDARD OPENAI-COMPATIBLE VOICES ==========
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"alloy": {
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"file": "LJ001-0001.wav",
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"base": COQUI_BASE,
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"style": "neutral, balanced - clear professional delivery",
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"gender": "female"
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},
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"echo": {
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"file": "LJ001-0004.wav",
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"base": COQUI_BASE,
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"style": "clear, measured - precise enunciation",
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"gender": "female"
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},
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"fable": {
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"file": "LJ001-0006.wav",
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"base": COQUI_BASE,
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"style": "expressive, storyteller - engaging narration",
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"gender": "female"
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},
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"onyx": {
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"file": "LJ001-0003.wav",
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"base": COQUI_BASE,
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"style": "deep, dramatic - authoritative tone",
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"gender": "female"
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},
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"nova": {
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"file": "LJ001-0005.wav",
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"base": COQUI_BASE,
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"style": "warm, friendly - approachable delivery",
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"gender": "female"
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},
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"shimmer": {
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"file": "LJ001-0002.wav",
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"base": COQUI_BASE,
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"style": "soft, gentle - calm and soothing",
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"gender": "female"
|
||||
},
|
||||
|
||||
# ========== EXTENDED VOICES - WARM/FRIENDLY ==========
|
||||
"amber": {
|
||||
"file": "LJ001-0007.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "warm amber glow - inviting and comfortable",
|
||||
"gender": "female"
|
||||
},
|
||||
"breeze": {
|
||||
"file": "LJ001-0008.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "light breeze - airy and refreshing",
|
||||
"gender": "female"
|
||||
},
|
||||
"coral": {
|
||||
"file": "LJ001-0009.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "coral reef - vibrant and lively",
|
||||
"gender": "female"
|
||||
},
|
||||
|
||||
# ========== EXTENDED VOICES - PROFESSIONAL ==========
|
||||
"dawn": {
|
||||
"file": "LJ001-0010.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "early dawn - fresh and hopeful",
|
||||
"gender": "female"
|
||||
},
|
||||
"ember": {
|
||||
"file": "LJ001-0011.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "glowing ember - warm with depth",
|
||||
"gender": "female"
|
||||
},
|
||||
"frost": {
|
||||
"file": "LJ001-0012.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "winter frost - crisp and clear",
|
||||
"gender": "female"
|
||||
},
|
||||
|
||||
# ========== EXTENDED VOICES - EXPRESSIVE ==========
|
||||
"glow": {
|
||||
"file": "LJ001-0013.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "soft glow - gentle radiance",
|
||||
"gender": "female"
|
||||
},
|
||||
"haze": {
|
||||
"file": "LJ001-0014.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "morning haze - dreamy and ethereal",
|
||||
"gender": "female"
|
||||
},
|
||||
"ivy": {
|
||||
"file": "LJ001-0015.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "climbing ivy - natural and organic",
|
||||
"gender": "female"
|
||||
},
|
||||
|
||||
# ========== EXTENDED VOICES - CALM ==========
|
||||
"jade": {
|
||||
"file": "LJ001-0016.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "jade stone - smooth and precious",
|
||||
"gender": "female"
|
||||
},
|
||||
"kite": {
|
||||
"file": "LJ001-0017.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "flying kite - free and playful",
|
||||
"gender": "female"
|
||||
},
|
||||
"lark": {
|
||||
"file": "LJ001-0018.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "morning lark - cheerful and bright",
|
||||
"gender": "female"
|
||||
},
|
||||
|
||||
# ========== EXTENDED VOICES - NARRATIVE ==========
|
||||
"mist": {
|
||||
"file": "LJ001-0019.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "soft mist - mysterious and intriguing",
|
||||
"gender": "female"
|
||||
},
|
||||
"nectar": {
|
||||
"file": "LJ001-0020.wav",
|
||||
"base": COQUI_BASE,
|
||||
"style": "sweet nectar - rich and delightful",
|
||||
"gender": "female"
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def download_file(url: str, output_path: Path) -> bool:
|
||||
"""Download a file from URL."""
|
||||
try:
|
||||
req = urllib.request.Request(url, headers={
|
||||
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
|
||||
})
|
||||
with urllib.request.urlopen(req, timeout=30) as response:
|
||||
data = response.read()
|
||||
# Verify it's actually audio (starts with RIFF for WAV)
|
||||
if data[:4] != b'RIFF':
|
||||
print(f" Warning: {url} is not a valid WAV file")
|
||||
return False
|
||||
with open(output_path, 'wb') as f:
|
||||
f.write(data)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f" Error: {e}")
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
output_dir = Path("voices/samples")
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
config_lines = [
|
||||
"# uncloseai-speech Voice Configuration",
|
||||
"# Diverse voice samples for Qwen3-TTS voice cloning",
|
||||
"#",
|
||||
"# Standard voices: alloy, echo, fable, onyx, nova, shimmer",
|
||||
"# Extended voices: amber, breeze, coral, dawn, ember, frost,",
|
||||
"# glow, haze, ivy, jade, kite, lark, mist, nectar",
|
||||
"#",
|
||||
"# Source: LJ Speech Dataset (public domain)",
|
||||
"# https://keithito.com/LJ-Speech-Dataset/",
|
||||
"",
|
||||
"tts-1-qwen:",
|
||||
]
|
||||
|
||||
downloaded = 0
|
||||
failed = []
|
||||
|
||||
for voice_name, info in VOICES.items():
|
||||
filename = info["file"]
|
||||
url = f"{info['base']}/{filename}"
|
||||
output_path = output_dir / f"{voice_name}.wav"
|
||||
|
||||
print(f"Downloading {voice_name}...", end=" ")
|
||||
|
||||
if download_file(url, output_path):
|
||||
downloaded += 1
|
||||
transcript = LJ_SAMPLES.get(filename, "Sample audio for voice cloning.")
|
||||
size_kb = output_path.stat().st_size / 1024
|
||||
|
||||
config_lines.extend([
|
||||
f"",
|
||||
f" # {info['style']}",
|
||||
f" {voice_name}:",
|
||||
f" ref_audio: voices/samples/{voice_name}.wav",
|
||||
f' ref_text: "{transcript}"',
|
||||
f" language: English",
|
||||
])
|
||||
print(f"✓ ({size_kb:.1f} KB)")
|
||||
else:
|
||||
failed.append(voice_name)
|
||||
print("✗")
|
||||
|
||||
# Add commented section for additional models
|
||||
config_lines.extend([
|
||||
"",
|
||||
"# Other TTS engines (disabled by default)",
|
||||
"# Uncomment and configure to enable",
|
||||
"",
|
||||
"# tts-1:",
|
||||
"# # Piper TTS (fast CPU inference)",
|
||||
"# alloy:",
|
||||
"# model: /app/voices/en/en_US/libritts_r/medium/en_US-libritts_r-medium.onnx",
|
||||
"# speaker: 79",
|
||||
"",
|
||||
"# tts-1-hd:",
|
||||
"# # XTTS v2 (voice cloning)",
|
||||
"# alloy:",
|
||||
"# model: xtts",
|
||||
"# speaker: voices/alloy.wav",
|
||||
])
|
||||
|
||||
# Write config
|
||||
config_path = Path("voice_to_speaker.default.yaml")
|
||||
with open(config_path, "w") as f:
|
||||
f.write("\n".join(config_lines))
|
||||
f.write("\n")
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print(f"Downloaded: {downloaded}/{len(VOICES)} voices")
|
||||
if failed:
|
||||
print(f"Failed: {', '.join(failed)}")
|
||||
print(f"Config: {config_path}")
|
||||
print(f"Samples: {output_dir}/")
|
||||
print(f"{'='*50}")
|
||||
|
||||
# Summary table
|
||||
print("\nVoice samples:")
|
||||
print(f"{'Voice':<12} {'Size':>10} {'Style'}")
|
||||
print("-" * 60)
|
||||
for f in sorted(output_dir.glob("*.wav")):
|
||||
voice = f.stem
|
||||
size = f.stat().st_size
|
||||
style = VOICES.get(voice, {}).get("style", "")[:35]
|
||||
print(f"{voice:<12} {size:>10,} {style}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Add table
Add a link
Reference in a new issue