156 lines
5.0 KiB
Python
156 lines
5.0 KiB
Python
import asyncio
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import json
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import uuid
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import websockets
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import os
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from queue import Queue
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from Config import Config
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from Util.TTS_Protocols import full_client_request, receive_message, MsgType, EventType
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class StreamingVolcanoTTS:
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def __init__(self, voice_type='zh_female_wanwanxiaohe_moon_bigtts', encoding='wav', max_concurrency=2):
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self.voice_type = voice_type
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self.encoding = encoding
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self.app_key = Config.HS_APP_ID
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self.access_token = Config.HS_ACCESS_TOKEN
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self.endpoint = "wss://openspeech.bytedance.com/api/v3/tts/unidirectional/stream"
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self.audio_queue = Queue()
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self.max_concurrency = max_concurrency # 最大并发数
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self.semaphore = asyncio.Semaphore(max_concurrency) # 并发控制信号量
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@staticmethod
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def get_resource_id(voice: str) -> str:
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if voice.startswith("S_"):
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return "volc.megatts.default"
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return "volc.service_type.10029"
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async def synthesize_stream(self, text_stream, audio_callback):
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"""
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流式合成语音
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Args:
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text_stream: 文本流生成器
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audio_callback: 音频数据回调函数，接收音频片段
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"""
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# 为每个文本片段创建一个WebSocket连接，但限制并发数
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tasks = []
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for text in text_stream:
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if text.strip(): # 忽略空文本
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task = asyncio.create_task(self._synthesize_single_with_semaphore(text, audio_callback))
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tasks.append(task)
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# 等待所有任务完成
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await asyncio.gather(*tasks)
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async def _synthesize_single_with_semaphore(self, text, audio_callback):
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"""使用信号量控制并发数的单个文本合成"""
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async with self.semaphore: # 获取信号量，限制并发数
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await self._synthesize_single(text, audio_callback)
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async def _synthesize_single(self, text, audio_callback):
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"""合成单个文本片段"""
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headers = {
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"X-Api-App-Key": self.app_key,
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"X-Api-Access-Key": self.access_token,
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"X-Api-Resource-Id": self.get_resource_id(self.voice_type),
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"X-Api-Connect-Id": str(uuid.uuid4()),
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}
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websocket = await websockets.connect(
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self.endpoint, additional_headers=headers, max_size=10 * 1024 * 1024
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)
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try:
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request = {
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"user": {
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"uid": str(uuid.uuid4()),
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},
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"req_params": {
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"speaker": self.voice_type,
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"audio_params": {
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"format": self.encoding,
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"sample_rate": 24000,
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"enable_timestamp": True,
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},
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"text": text,
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"additions": json.dumps({"disable_markdown_filter": False}),
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},
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}
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# 发送请求
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await full_client_request(websocket, json.dumps(request).encode())
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# 接收音频数据
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audio_data = bytearray()
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while True:
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msg = await receive_message(websocket)
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if msg.type == MsgType.FullServerResponse:
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if msg.event == EventType.SessionFinished:
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break
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elif msg.type == MsgType.AudioOnlyServer:
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audio_data.extend(msg.payload)
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else:
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raise RuntimeError(f"TTS conversion failed: {msg}")
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# 通过回调函数返回音频数据
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if audio_data:
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audio_callback(audio_data)
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finally:
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await websocket.close()
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def audio_callback(audio_data):
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"""
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音频数据回调函数，将音频数据保存到文件
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"""
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# 创建输出目录
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output_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "output")
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os.makedirs(output_dir, exist_ok=True)
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# 生成文件名
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filename = f"streaming_tts_{uuid.uuid4().hex[:8]}.wav"
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filepath = os.path.join(output_dir, filename)
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# 保存音频文件
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with open(filepath, "wb") as f:
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f.write(audio_data)
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print(f"音频片段已保存到: {filepath}")
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async def test_streaming_tts():
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"""
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测试流式TTS功能
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"""
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# 创建TTS实例
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tts = StreamingVolcanoTTS()
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# 准备测试文本流
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test_texts = [
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"你好，我是火山引擎的语音合成服务。",
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"这是一个流式语音合成的测试。",
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"我们将文本分成多个片段进行合成。",
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"这样可以减少等待时间，提高用户体验。"
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]
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print("开始测试流式TTS...")
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print(f"测试文本: {test_texts}")
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# 调用流式合成
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await tts.synthesize_stream(test_texts, audio_callback)
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print("流式TTS测试完成！")
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def main():
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"""
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主函数，运行测试
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"""
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asyncio.run(test_streaming_tts())
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if __name__ == "__main__":
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main() |