bcad200a23
- New stacks: beads-server, hermes-agent - Terragrunt tiers.tf for infra, phpipam, status-page - Secrets symlinks for vault, phpipam, hermes-agent - Scripts: cluster_manager, image_pull, containerd pullthrough setup - Frigate config, audiblez-web app source, n8n workflows dir - Claude agent: service-upgrade, reference: upgrade-config.json - Removed: claudeception skill, excalidraw empty submodule, temp listings [ci skip] Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
136 lines
4.1 KiB
Python
136 lines
4.1 KiB
Python
#!/usr/bin/env python3
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"""
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Generate voice samples for all available voices.
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Run this script in an environment with audiblez installed.
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Usage:
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python generate_samples.py [output_dir]
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"""
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import os
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import sys
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from pathlib import Path
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# Sample text for voice preview
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SAMPLE_TEXT = "The quick brown fox jumps over the lazy dog. This is a sample of my voice for audiobook narration."
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# All voices from Kokoro-82M (audiblez)
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VOICES = [
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# American English (20 voices)
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"af_alloy", "af_aoede", "af_bella", "af_heart", "af_jessica", "af_kore",
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"af_nicole", "af_nova", "af_river", "af_sarah", "af_sky",
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"am_adam", "am_echo", "am_eric", "am_fenrir", "am_liam", "am_michael",
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"am_onyx", "am_puck", "am_santa",
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# British English (8 voices)
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"bf_alice", "bf_emma", "bf_isabella", "bf_lily",
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"bm_daniel", "bm_fable", "bm_george", "bm_lewis",
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# Spanish (3 voices)
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"ef_dora", "em_alex", "em_santa",
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# French (1 voice)
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"ff_siwis",
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# Hindi (4 voices)
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"hf_alpha", "hf_beta", "hm_omega", "hm_psi",
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# Italian (2 voices)
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"if_sara", "im_nicola",
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# Japanese (5 voices)
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"jf_alpha", "jf_gongitsune", "jf_nezumi", "jf_tebukuro", "jm_kumo",
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# Brazilian Portuguese (3 voices)
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"pf_dora", "pm_alex", "pm_santa",
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# Mandarin Chinese (8 voices)
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"zf_xiaobei", "zf_xiaoni", "zf_xiaoxiao", "zf_xiaoyi",
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"zm_yunjian", "zm_yunxi", "zm_yunxia", "zm_yunyang",
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]
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def generate_sample(voice: str, output_dir: Path):
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"""Generate a voice sample using kokoro TTS."""
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try:
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from kokoro import KPipeline
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output_file = output_dir / f"{voice}.mp3"
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if output_file.exists():
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print(f"Skipping {voice} - already exists")
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return True
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print(f"Generating sample for {voice}...")
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# Map voice prefix to language code
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lang_map = {
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'a': 'a', # American English
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'b': 'b', # British English
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'e': 'e', # Spanish
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'f': 'f', # French
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'h': 'h', # Hindi
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'i': 'i', # Italian
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'j': 'j', # Japanese
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'p': 'p', # Portuguese
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'z': 'z', # Chinese
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}
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# Extract language code from voice (first letter)
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lang_code = lang_map.get(voice[0], 'a')
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# Initialize the Kokoro pipeline
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pipeline = KPipeline(lang_code=lang_code)
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# Generate audio
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generator = pipeline(SAMPLE_TEXT, voice=voice, speed=1.0)
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# Collect all audio chunks
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audio_chunks = []
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for _, _, audio in generator:
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audio_chunks.append(audio)
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if audio_chunks:
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import soundfile as sf
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import numpy as np
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# Concatenate audio
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audio = np.concatenate(audio_chunks)
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# Save as WAV first, then convert to MP3
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wav_file = output_dir / f"{voice}.wav"
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sf.write(str(wav_file), audio, 24000)
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# Convert to MP3 using ffmpeg
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import subprocess
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result = subprocess.run([
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"ffmpeg", "-y", "-i", str(wav_file),
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"-codec:a", "libmp3lame", "-qscale:a", "5",
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str(output_file)
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], capture_output=True)
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# Remove WAV file
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if wav_file.exists():
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wav_file.unlink()
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if result.returncode == 0:
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print(f"Generated {output_file}")
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return True
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else:
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print(f"FFmpeg failed for {voice}: {result.stderr.decode()}")
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return False
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else:
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print(f"Failed to generate audio for {voice}")
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return False
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except Exception as e:
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print(f"Error generating sample for {voice}: {e}")
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return False
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def main():
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output_dir = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("samples")
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output_dir.mkdir(parents=True, exist_ok=True)
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print(f"Generating voice samples to {output_dir}")
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print(f"Total voices: {len(VOICES)}")
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for voice in VOICES:
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generate_sample(voice, output_dir)
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print("Done!")
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if __name__ == "__main__":
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main()
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