mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 15:13:55 +08:00
111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
import time
|
|
import wave
|
|
import os
|
|
import sys
|
|
import io
|
|
from config.logger import setup_logging
|
|
from typing import Optional, Tuple, List
|
|
import uuid
|
|
import opuslib_next
|
|
from core.providers.asr.base import ASRProviderBase
|
|
|
|
from funasr import AutoModel
|
|
from funasr.utils.postprocess_utils import rich_transcription_postprocess
|
|
|
|
TAG = __name__
|
|
logger = setup_logging()
|
|
|
|
|
|
# 捕获标准输出
|
|
class CaptureOutput:
|
|
def __enter__(self):
|
|
self._output = io.StringIO()
|
|
self._original_stdout = sys.stdout
|
|
sys.stdout = self._output
|
|
|
|
def __exit__(self, exc_type, exc_value, traceback):
|
|
sys.stdout = self._original_stdout
|
|
self.output = self._output.getvalue()
|
|
self._output.close()
|
|
|
|
# 将捕获到的内容通过 logger 输出
|
|
if self.output:
|
|
logger.bind(tag=TAG).info(self.output.strip())
|
|
|
|
|
|
class ASRProvider(ASRProviderBase):
|
|
def __init__(self, config: dict, delete_audio_file: bool):
|
|
self.model_dir = config.get("model_dir")
|
|
self.output_dir = config.get("output_dir") # 修正配置键名
|
|
self.delete_audio_file = delete_audio_file
|
|
|
|
# 确保输出目录存在
|
|
os.makedirs(self.output_dir, exist_ok=True)
|
|
with CaptureOutput():
|
|
self.model = AutoModel(
|
|
model=self.model_dir,
|
|
vad_kwargs={"max_single_segment_time": 30000},
|
|
disable_update=True,
|
|
hub="hf"
|
|
# device="cuda:0", # 启用GPU加速
|
|
)
|
|
|
|
def save_audio_to_file(self, opus_data: List[bytes], session_id: str) -> str:
|
|
"""将Opus音频数据解码并保存为WAV文件"""
|
|
file_name = f"asr_{session_id}_{uuid.uuid4()}.wav"
|
|
file_path = os.path.join(self.output_dir, file_name)
|
|
|
|
decoder = opuslib_next.Decoder(16000, 1) # 16kHz, 单声道
|
|
pcm_data = []
|
|
|
|
for opus_packet in opus_data:
|
|
try:
|
|
pcm_frame = decoder.decode(opus_packet, 960) # 960 samples = 60ms
|
|
pcm_data.append(pcm_frame)
|
|
except opuslib_next.OpusError as e:
|
|
logger.bind(tag=TAG).error(f"Opus解码错误: {e}", exc_info=True)
|
|
|
|
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
|
|
|
|
async def speech_to_text(self, opus_data: List[bytes], session_id: str) -> Tuple[Optional[str], Optional[str]]:
|
|
"""语音转文本主处理逻辑"""
|
|
file_path = None
|
|
try:
|
|
# 保存音频文件
|
|
start_time = time.time()
|
|
file_path = self.save_audio_to_file(opus_data, session_id)
|
|
logger.bind(tag=TAG).debug(f"音频文件保存耗时: {time.time() - start_time:.3f}s | 路径: {file_path}")
|
|
|
|
# 语音识别
|
|
start_time = time.time()
|
|
result = self.model.generate(
|
|
input=file_path,
|
|
cache={},
|
|
language="auto",
|
|
use_itn=True,
|
|
batch_size_s=60,
|
|
)
|
|
text = rich_transcription_postprocess(result[0]["text"])
|
|
logger.bind(tag=TAG).debug(f"语音识别耗时: {time.time() - start_time:.3f}s | 结果: {text}")
|
|
|
|
return text, file_path
|
|
|
|
except Exception as e:
|
|
logger.bind(tag=TAG).error(f"语音识别失败: {e}", exc_info=True)
|
|
return "", None
|
|
|
|
finally:
|
|
# 文件清理逻辑
|
|
if self.delete_audio_file and file_path and os.path.exists(file_path):
|
|
try:
|
|
os.remove(file_path)
|
|
logger.bind(tag=TAG).debug(f"已删除临时音频文件: {file_path}")
|
|
except Exception as e:
|
|
logger.bind(tag=TAG).error(f"文件删除失败: {file_path} | 错误: {e}")
|