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python/extract_voice_embedding.py
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#!/usr/bin/env python3
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"""从参考音频提取 192 维音色 embedding(宿主侧,torch + 官方 S3Gen.speaker_encoder)。
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本 AXMODEL 以 192 维 xvector 作为音色条件(embedding 级克隆/音色迁移)。
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完整官方克隆还含 10s 参考 prompt 条件,当前板端 AXMODEL 未导出该路径。
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用法:
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python3 extract_voice_embedding.py --wav ref.wav --ckpt-dir /path/to/chatterbox_models \
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--out ref_embedding.npy
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(ckpt-dir 需含 s3gen.safetensors;参考音频建议 6-10s 清晰人声。)
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然后调用板端 OpenAI 服务时带上 voice.embedding:
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curl -X POST http://<board>:8000/v1/audio/speech \
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-H 'Content-Type: application/json' \
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-d '{"input":[12,34,56],"voice":{"embedding":[...192 个 float...]},"response_format":"wav"}'
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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import librosa
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import numpy as np
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def main():
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p = argparse.ArgumentParser(description="提取参考音频的 192 维音色 embedding")
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p.add_argument("--wav", required=True, help="参考音频(任意采样率,内部重采样到 16k)")
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p.add_argument("--ckpt-dir", required=True, help="Chatterbox 模型目录(含 ve.safetensors)")
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p.add_argument("--out", default="voice_embedding.npy")
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args = p.parse_args()
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import torch
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from chatterbox.models.s3gen import S3Gen, S3GEN_SR
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from safetensors.torch import load_file
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s3gen = S3Gen()
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s3gen.load_state_dict(load_file(Path(args.ckpt_dir) / "s3gen.safetensors"), strict=False)
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s3gen.eval()
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wav, sr = librosa.load(args.wav, sr=S3GEN_SR, mono=True)
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with torch.inference_mode():
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ref_dict = s3gen.embed_ref(wav, S3GEN_SR, device="cpu")
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emb = ref_dict["embedding"].numpy().astype(np.float32) # (1,192)
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np.save(args.out, emb)
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print(f"OK: embedding {emb.shape} -> {args.out}")
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print("板端 OpenAI 调用示例:")
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print(
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" curl -X POST http://<board>:8000/v1/audio/speech -H 'Content-Type: application/json' "
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"-d " + json.dumps({"input": [12, 34, 56], "voice": {"embedding": emb.reshape(-1).tolist()},
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"response_format": "wav"})[:160] + " ..."
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)
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if __name__ == "__main__":
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main()
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