92 lines
3.2 KiB
Python
92 lines
3.2 KiB
Python
import io
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import os
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import wave
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import asyncio
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import numpy as np
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import sherpa_onnx
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from config.logger import setup_logging
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from core.providers.tts.base import TTSProviderBase
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TAG = __name__
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logger = setup_logging()
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class TTSProvider(TTSProviderBase):
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def __init__(self, config, delete_audio_file):
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super().__init__(config, delete_audio_file)
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model_dir = config.get("model_dir", "models/vits-melo-tts-zh_en")
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speed = config.get("speed", 1.0)
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self.speed = float(speed) if speed else 1.0
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self.sid = int(config.get("sid", 0))
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# 优先使用 int8 量化模型（更快）
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model_file = f"{model_dir}/model.int8.onnx"
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if not os.path.exists(model_file) or os.path.getsize(model_file) < 1024:
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model_file = f"{model_dir}/model.onnx"
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num_threads = int(config.get("num_threads", 8))
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tts_config = sherpa_onnx.OfflineTtsConfig(
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model=sherpa_onnx.OfflineTtsModelConfig(
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vits=sherpa_onnx.OfflineTtsVitsModelConfig(
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model=model_file,
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lexicon=f"{model_dir}/lexicon.txt",
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tokens=f"{model_dir}/tokens.txt",
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dict_dir=f"{model_dir}/dict",
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),
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num_threads=num_threads,
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),
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rule_fsts=f"{model_dir}/date.fst,{model_dir}/phone.fst,{model_dir}/number.fst,{model_dir}/new_heteronym.fst",
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max_num_sentences=1,
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)
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self.tts = sherpa_onnx.OfflineTts(tts_config)
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self.sample_rate = self.tts.sample_rate
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logger.bind(tag=TAG).info(
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f"SherpaOnnxTTS 初始化完成: model_dir={model_dir}, sample_rate={self.sample_rate}, sid={self.sid}"
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)
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def _generate_wav(self, text):
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"""同步合成"""
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import time
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from scipy.signal import resample_poly
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from math import gcd
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logger.bind(tag=TAG).info(f"TTS 收到文字: [{text}]")
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t0 = time.time()
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audio = self.tts.generate(text, sid=self.sid, speed=self.speed)
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samples = np.array(audio.samples, dtype=np.float32)
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t1 = time.time()
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# 重采样到目标采样率（设备要求 24000Hz，模型输出 44100Hz）
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target_sr = 24000
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if self.sample_rate != target_sr:
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g = gcd(self.sample_rate, target_sr)
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samples = resample_poly(samples, target_sr // g, self.sample_rate // g)
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t2 = time.time()
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pcm = (samples * 32767).astype(np.int16)
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audio_duration = len(pcm) / target_sr
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wav_io = io.BytesIO()
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with wave.open(wav_io, "wb") as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(target_sr)
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wf.writeframes(pcm.tobytes())
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wav_data = wav_io.getvalue()
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logger.bind(tag=TAG).info(
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f"TTS 完成: 合成={t1-t0:.2f}s 重采样={t2-t1:.2f}s 音频时长={audio_duration:.1f}s 大小={len(wav_data)}B [{text[:20]}]"
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)
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return wav_data
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async def text_to_speak(self, text, output_file):
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wav_data = self._generate_wav(text)
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if output_file:
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with open(output_file, "wb") as f:
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f.write(wav_data)
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else:
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return wav_data
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