mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-25 00:23:53 +08:00
107 lines
3.5 KiB
Python
107 lines
3.5 KiB
Python
import base64
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import hashlib
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import hmac
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import json
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import time
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from datetime import datetime, timezone
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import os
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import uuid
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from typing import Optional, Tuple, List
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import wave
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import opuslib_next
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from aip import AipSpeech
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from core.providers.asr.base import ASRProviderBase
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from config.logger import setup_logging
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TAG = __name__
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logger = setup_logging()
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class ASRProvider(ASRProviderBase):
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def __init__(self, config: dict, delete_audio_file: bool = True):
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super().__init__()
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self.app_id = config.get("app_id")
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self.api_key = config.get("api_key")
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self.secret_key = config.get("secret_key")
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dev_pid = config.get("dev_pid", "1537")
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self.dev_pid = int(dev_pid) if dev_pid else 1537
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self.output_dir = config.get("output_dir")
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self.delete_audio_file = delete_audio_file
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self.client = AipSpeech(str(self.app_id), self.api_key, self.secret_key)
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# 确保输出目录存在
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os.makedirs(self.output_dir, exist_ok=True)
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def save_audio_to_file(self, pcm_data: List[bytes], session_id: str) -> str:
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"""PCM数据保存为WAV文件"""
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module_name = __name__.split(".")[-1]
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file_name = f"asr_{module_name}_{session_id}_{uuid.uuid4()}.wav"
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file_path = os.path.join(self.output_dir, file_name)
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with wave.open(file_path, "wb") as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2) # 2 bytes = 16-bit
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wf.setframerate(16000)
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wf.writeframes(b"".join(pcm_data))
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return file_path
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async def speech_to_text(
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self, opus_data: List[bytes], session_id: str
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) -> Tuple[Optional[str], Optional[str]]:
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"""将语音数据转换为文本"""
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if not opus_data:
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logger.bind(tag=TAG).warning("音频数据为空！")
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return None, None
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file_path = None
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try:
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# 检查配置是否已设置
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if not self.app_id or not self.api_key or not self.secret_key:
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logger.bind(tag=TAG).error("百度语音识别配置未设置，无法进行识别")
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return None, file_path
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# 将Opus音频数据解码为PCM
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if self.audio_format == "pcm":
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pcm_data = opus_data
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else:
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pcm_data = self.decode_opus(opus_data)
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combined_pcm_data = b"".join(pcm_data)
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# 判断是否保存为WAV文件
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if self.delete_audio_file:
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pass
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else:
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self.save_audio_to_file(pcm_data, session_id)
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start_time = time.time()
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# 识别本地文件
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result = self.client.asr(
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combined_pcm_data,
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"pcm",
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16000,
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{
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"dev_pid": str(self.dev_pid),
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},
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)
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if result and result["err_no"] == 0:
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logger.bind(tag=TAG).debug(
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f"百度语音识别耗时: {time.time() - start_time:.3f}s | 结果: {result}"
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)
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result = result["result"][0]
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return result, file_path
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else:
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raise Exception(
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f"百度语音识别失败，错误码: {result['err_no']}，错误信息: {result['err_msg']}"
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)
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return None, file_path
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except Exception as e:
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logger.bind(tag=TAG).error(f"处理音频时发生错误！{e}", exc_info=True)
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return None, file_path
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