Files
xiaozhi-esp32-server/main/xiaozhi-server/core/providers/asr/base.py
T

140 lines
5.0 KiB
Python

import os
import wave
import copy
import uuid
import queue
import asyncio
import traceback
import threading
import opuslib_next
from abc import ABC, abstractmethod
from config.logger import setup_logging
from typing import Optional, Tuple, List
from core.handle.receiveAudioHandle import startToChat
from core.handle.reportHandle import enqueue_asr_report
from core.utils.util import remove_punctuation_and_length
from core.handle.receiveAudioHandle import handleAudioMessage
TAG = __name__
logger = setup_logging()
class ASRProviderBase(ABC):
def __init__(self):
pass
# 打开音频通道
# 这里默认是非流式的处理方式
# 流式处理方式请在子类中重写
async def open_audio_channels(self, conn):
# tts 消化线程
conn.asr_priority_thread = threading.Thread(
target=self.asr_text_priority_thread, args=(conn,), daemon=True
)
conn.asr_priority_thread.start()
# 有序处理ASR音频
def asr_text_priority_thread(self, conn):
while not conn.stop_event.is_set():
try:
message = conn.asr_audio_queue.get(timeout=1)
future = asyncio.run_coroutine_threadsafe(
handleAudioMessage(conn, message),
conn.loop,
)
future.result()
except queue.Empty:
continue
except Exception as e:
logger.bind(tag=TAG).error(
f"处理ASR文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
)
continue
# 接收音频
# 这里默认是非流式的处理方式
# 流式处理方式请在子类中重写
async def receive_audio(self, conn, audio, audio_have_voice):
if conn.client_listen_mode == "auto" or conn.client_listen_mode == "realtime":
have_voice = audio_have_voice
else:
have_voice = conn.client_have_voice
# 如果本次没有声音,本段也没声音,就把声音丢弃了
conn.asr_audio.append(audio)
if have_voice == False and conn.client_have_voice == False:
conn.asr_audio = conn.asr_audio[-10:]
return
# 如果本段有声音,且已经停止了
if conn.client_voice_stop:
asr_audio_task = copy.deepcopy(conn.asr_audio)
conn.asr_audio.clear()
# 音频太短了,无法识别
conn.reset_vad_states()
if len(asr_audio_task) > 15:
await self.handle_voice_stop(conn, asr_audio_task)
# 处理语音停止
async def handle_voice_stop(self, conn, asr_audio_task):
raw_text, _ = await self.speech_to_text(
asr_audio_task, conn.session_id, conn.audio_format
) # 确保ASR模块返回原始文本
conn.logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
text_len, _ = remove_punctuation_and_length(raw_text)
self.stop_ws_connection()
if text_len > 0:
# 使用自定义模块进行上报
await startToChat(conn, raw_text)
enqueue_asr_report(conn, raw_text, asr_audio_task)
def stop_ws_connection(self):
pass
def save_audio_to_file(self, pcm_data: List[bytes], session_id: str) -> str:
"""PCM数据保存为WAV文件"""
module_name = __name__.split(".")[-1]
file_name = f"asr_{module_name}_{session_id}_{uuid.uuid4()}.wav"
file_path = os.path.join(self.output_dir, file_name)
with wave.open(file_path, "wb") as wf:
wf.setnchannels(1)
wf.setsampwidth(2) # 2 bytes = 16-bit
wf.setframerate(16000)
wf.writeframes(b"".join(pcm_data))
return file_path
@abstractmethod
async def speech_to_text(
self, opus_data: List[bytes], session_id: str, audio_format="opus"
) -> Tuple[Optional[str], Optional[str]]:
"""将语音数据转换为文本"""
pass
@staticmethod
def decode_opus(opus_data: List[bytes]) -> bytes:
"""将Opus音频数据解码为PCM数据"""
try:
decoder = opuslib_next.Decoder(16000, 1) # 16kHz, 单声道
pcm_data = []
buffer_size = 960 # 每次处理960个采样点
for opus_packet in opus_data:
try:
# 使用较小的缓冲区大小进行处理
pcm_frame = decoder.decode(opus_packet, buffer_size)
if pcm_frame:
pcm_data.append(pcm_frame)
except opuslib_next.OpusError as e:
logger.bind(tag=TAG).warning(f"Opus解码错误,跳过当前数据包: {e}")
continue
except Exception as e:
logger.bind(tag=TAG).error(f"音频处理错误: {e}", exc_info=True)
continue
return pcm_data
except Exception as e:
logger.bind(tag=TAG).error(f"音频解码过程发生错误: {e}", exc_info=True)
return []