Create paddlespeech-deploy.md

PaddleSpeechTTS流式传输集成到xiaozhi服务
2026-07-22 07:03:53 +08:00 · 2025-08-07 16:19:06 +08:00
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+# PaddleSpeechTTS集成xiaozhi服务
+
+## 一、基础环境要求
+操作系统：Windows / Linux / WSL 2
+
+Python 版本：3.8 ~ 3.10
+
+Paddle 官方最新版本
+
+依赖管理工具：conda 或 venv
+
+前提条件：需要先根据paddle官方教程安装好PaddlePaddle   ```https://www.paddlepaddle.org.cn/install```
+
+## 二、启动paddlespeech服务
+### 1.从paddlespeech官方仓库拉取源码
+```bash 
+git clone https://github.com/PaddlePaddle/PaddleSpeech.git
+```
+### 2.建立虚拟环境
+```bash
+conda create -n paddle_env python=3.8 -y
+conda activate paddle_env
+```
+### 3.进入paddlespeech目录
+```bash
+cd PaddleSpeech
+```
+### 4.安装paddlespeech
+```bash
+pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+#以下命令使用任意一个
+pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
+pip install paddlespeech -i https://pypi.tuna.tsinghua.edu.cn/simple
+```
+### 5.使用命令自动下载语音模型
+```bash
+paddlespeech tts --input "你好，这是一次测试"
+```
+此步骤会自动下载模型缓存至本地 .paddlespeech/models 目录
+
+### 6.修改tts_online_application.yaml配置
+参考目录 ```"PaddleSpeech\demos\streaming_tts_server\conf\tts_online_application.yaml"```
+选择```tts_online_application.yaml```文件用编辑器打开，设置```protocol```为```websocket```
+
+### 7.启动服务
+```yaml
+paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
+```
+请根据你的```tts_online_application.yaml```的实际目录来启动命令
+看到如下日志即启动成功
+```
+Prefix dict has been built successfully.
+[2025-08-07 10:03:11,312] [   DEBUG] __init__.py:166 - Prefix dict has been built successfully.
+INFO:     Started server process [2298]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit)
+```
+
+## 三、修改小智的配置文件
+### 1.```main/xiaozhi-server/core/providers/tts/paddle_speech.py```
+```py
+import asyncio
+import json
+import base64
+import aiohttp
+import numpy as np
+import io
+import wave
+import websockets
+from core.providers.tts.base import TTSProviderBase
+from config.logger import setup_logging
+
+TAG = __name__
+logger = setup_logging()
+
+
+class TTSProvider(TTSProviderBase):
+    def __init__(self, config, delete_audio_file):
+        super().__init__(config, delete_audio_file)
+        self.url = config.get("url", "ws://192.168.1.10:8092/paddlespeech/tts/streaming")
+        self.protocol = config.get("protocol", "websocket")
+        self.spk_id = config.get("spk_id", 0)
+        self.sample_rate = config.get("sample_rate", 24000)
+        self.speed = config.get("speed", 1.0)
+        self.volume = config.get("volume", 1.0)
+        self.save_path = config.get("save_path", "./streaming_tts.wav")
+
+    async def pcm_to_wav(self, pcm_data: bytes, sample_rate: int = 24000, num_channels: int = 1,
+                         bits_per_sample: int = 16) -> bytes:
+        """
+        将 PCM 数据转换为 WAV 文件并返回字节数据
+        :param pcm_data: PCM 数据（原始字节流）
+        :param sample_rate: 音频采样率，默认为24000
+        :param num_channels: 声道数，默认为单声道
+        :param bits_per_sample: 每个样本的位数，默认为16
+        :return: WAV 格式的字节数据
+        """
+        byte_data = np.frombuffer(pcm_data, dtype=np.int16)  # 16位PCM
+        wav_io = io.BytesIO()
+
+        with wave.open(wav_io, "wb") as wav_file:
+            wav_file.setnchannels(num_channels)
+            wav_file.setsampwidth(bits_per_sample // 8)
+            wav_file.setframerate(sample_rate)
+            wav_file.writeframes(byte_data.tobytes())
+
+        return wav_io.getvalue()
+
+    async def text_to_speak(self, text, output_file):
+        if self.protocol == "websocket":
+            return await self.text_streaming(text, output_file)
+        elif self.protocol == "http":
+            return await self.text(text, output_file)
+        else:
+            raise ValueError("Unsupported protocol. Please use 'websocket' or 'http'.")
+
+    async def text(self, text, output_file):
+        request_json = {
+            "text": text,
+            "spk_id": self.spk_id,
+            "speed": self.speed,
+            "volume": self.volume,
+            "sample_rate": self.sample_rate,
+            "save_path": self.save_path
+        }
+
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(self.url, json=request_json) as resp:
+                    if resp.status == 200:
+                        resp_json = await resp.json()
+                        if resp_json.get("success"):
+                            data = resp_json["result"]
+                            audio_bytes = base64.b64decode(data["audio"])
+                            if output_file:
+                                with open(output_file, "wb") as file_to_save:
+                                    file_to_save.write(audio_bytes)
+                            else:
+                                return audio_bytes
+                        else:
+                            raise Exception(
+                                f"Error: {resp_json.get('message', 'Unknown error')} while processing text: {text}")
+                    else:
+                        raise Exception(
+                            f"HTTP Error: {resp.status} - {await resp.text()} while processing text: {text}")
+        except Exception as e:
+            raise Exception(f"Error during TTS HTTP request: {e} while processing text: {text}")
+
+    async def text_streaming(self, text, output_file):
+        try:
+            # 使用 websockets 异步连接到 WebSocket 服务器
+            async with websockets.connect(self.url) as ws:
+                # 发送开始请求
+                start_request = {
+                    "task": "tts",
+                    "signal": "start"
+                }
+                await ws.send(json.dumps(start_request))
+
+                # 接收开始响应并提取 session_id
+                start_response = await ws.recv()
+                start_response = json.loads(start_response)  # 解析 JSON 响应
+                if start_response.get("status") != 0:
+                    raise Exception(f"连接失败: {start_response.get('signal')}")
+
+                session_id = start_response.get("session")
+
+                # 发送待合成的文本数据
+                data_request = {
+                    "text": text,
+                    "spk_id": self.spk_id,
+                }
+                await ws.send(json.dumps(data_request))
+
+                audio_chunks = b""
+                timeout_seconds = 60  # 设置超时
+                try:
+                    while True:
+                        response = await asyncio.wait_for(ws.recv(), timeout=timeout_seconds)
+                        response = json.loads(response)  # 解析 JSON 响应
+                        status = response.get("status")
+
+                        if status == 2:  # 最后一个数据包
+                            break
+                        else:
+                            # 拼接音频数据（base64 编码的 PCM 数据）
+                            audio_chunks += base64.b64decode(response.get("audio"))
+                except asyncio.TimeoutError:
+                    raise Exception(f"WebSocket 超时：等待音频数据超过 {timeout_seconds} 秒")
+
+                # 将拼接后的 PCM 数据转换为 WAV 格式
+                wav_data = await self.pcm_to_wav(audio_chunks)
+
+                # 结束请求
+                end_request = {
+                    "task": "tts",
+                    "signal": "end",
+                    "session": session_id  # 会话 ID 必须与开始请求中的一致
+                }
+                await ws.send(json.dumps(end_request))
+
+                # 接收结束响应避免服务抛出异常
+                await ws.recv()
+
+                # 返回或保存音频数据
+                if output_file:
+                    with open(output_file, "wb") as file_to_save:
+                        file_to_save.write(wav_data)
+                else:
+                    return wav_data
+
+        except Exception as e:
+            raise Exception(f"Error during TTS WebSocket request: {e} while processing text: {text}")
+```
+### 2.```main/xiaozhi-server/data/.config.yaml```
+使用单模块部署
+```yaml
+selected_module:
+  TTS: PaddleSpeechTTS
+TTS:
+  PaddleSpeechTTS:
+      type: paddle_speech
+      protocol: websocket 
+      url:  ws://127.0.0.1:8092/paddlespeech/tts/streaming  # TTS 服务的 URL 地址，指向本地服务器 [websocket默认ws://127.0.0.1:8092/paddlespeech/tts/streaming]
+      spk_id: 0  # 发音人 ID，0 通常表示默认的发音人
+      sample_rate: 24000  # 采样率 [websocket默认24000，http默认0 自动选择]
+      speed: 1.0  # 语速，1.0 表示正常语速，>1 表示加快，<1 表示减慢
+      volume: 1.0  # 音量，1.0 表示正常音量，>1 表示增大，<1 表示减小
+      save_path: ./streaming_tts.wav  # 服务器生成的语音文件保存路径
+```
+### 3.启动xiaozhi服务
+```py
+python app.py
+```
+打开test目录下的test_page.html，测试连接和发送消息时paddlespeech端是否有输出日志
+
+输出日志参考：
+```b
+INFO:     127.0.0.1:44312 - "WebSocket /paddlespeech/tts/streaming" [accepted]
+INFO:     connection open
+[2025-08-07 11:16:33,355] [    INFO] - sentence: 哈哈，怎么突然找我聊天啦？
+[2025-08-07 11:16:33,356] [    INFO] - The durations of audio is: 2.4625 s
+[2025-08-07 11:16:33,356] [    INFO] - first response time: 0.1143045425415039 s
+[2025-08-07 11:16:33,356] [    INFO] - final response time: 0.4777836799621582 s
+[2025-08-07 11:16:33,356] [    INFO] - RTF: 0.19402382942625715
+[2025-08-07 11:16:33,356] [    INFO] - Other info: front time: 0.06514096260070801 s, first am infer time: 0.008037090301513672 s, first voc infer time: 0.04112648963928223 s,
+[2025-08-07 11:16:33,356] [    INFO] - Complete the synthesis of the audio streams
+INFO:     connection closed
+
+```