Initial clean project import

2026-06-19 18:41:41 +08:00
commit a13b804c7a
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+#!/usr/bin/env python3
+"""
+FUNASR语音识别备用方案
+使用speech_recognition库进行本地语音识别
+如果speech_recognition库不可用，降级使用pydub和SpeechRecognition
+"""
+
+import json
+import sys
+import argparse
+import os
+from pathlib import Path
+from datetime import datetime
+
+def recognize_with_funasr(audio_path: str, language: str = 'zh', enable_word_timestamp: bool = True):
+    """
+    使用FUNASR本地模型进行语音识别
+    """
+    try:
+        from funasr import AutoModel
+
+        model = AutoModel(
+            model="paraformer-zh",  # 中文模型
+            vad_model="fsmn-vad",   # 语音活动检测
+            vad_kwargs={"max_single_segment_time": 30000},
+            device="cpu"  # 使用CPU，避免GPU依赖
+        )
+
+        res = model.generate(
+            input=audio_path,
+            cache={},
+            language=language,
+            merge_consecutive_texts=False
+        )
+
+        # 转换为标准格式
+        segments = []
+        current_time = 0.0
+
+        for item in res:
+            if isinstance(item, dict) and 'text' in item:
+                text = item['text']
+                # 估算时长（假设每个字0.5秒）
+                duration = len(text) * 0.5
+                segment = {
+                    'text': text,
+                    'start': current_time,
+                    'end': current_time + duration,
+                    'words': []
+                }
+
+                # 如果启用词级时间戳
+                if enable_word_timestamp and isinstance(item, dict) and 'details' in item:
+                    words = item['details']
+                    for word_info in words:
+                        word = {
+                            'word': word_info.get('text', ''),
+                            'start': word_info.get('start', 0) / 1000,  # 转换为秒
+                            'end': word_info.get('end', 0) / 1000,
+                            'confidence': word_info.get('confidence', 0.0)
+                        }
+                        segment['words'].append(word)
+
+                segments.append(segment)
+                current_time += duration
+
+        return {
+            'segments': segments,
+            'language': language,
+            'duration': current_time
+        }
+
+    except ImportError:
+        return recognize_with_speech_recognition(audio_path, language, enable_word_timestamp)
+
+
+def recognize_with_speech_recognition(audio_path: str, language: str = 'zh', enable_word_timestamp: bool = True):
+    """
+    使用SpeechRecognition库作为备用方案
+    支持Google Cloud Speech API、Sphinx等
+    """
+    try:
+        import speech_recognition as sr
+
+        recognizer = sr.Recognizer()
+
+        # 支持多种音频格式
+        if audio_path.endswith('.wav'):
+            with sr.AudioFile(audio_path) as source:
+                audio = recognizer.record(source)
+        else:
+            # 对于其他格式，首先需要转换为WAV
+            # 这里假设音频已经被转换为WAV
+            with sr.AudioFile(audio_path) as source:
+                audio = recognizer.record(source)
+
+        # 尝试使用Google Cloud Speech Recognition（需要网络）
+        try:
+            text = recognizer.recognize_google(audio, language='zh-CN' if language == 'zh' else language)
+
+            # 转换为标准格式
+            segments = [{
+                'text': text,
+                'start': 0.0,
+                'end': 5.0,  # 默认5秒
+                'words': []
+            }]
+
+            return {
+                'segments': segments,
+                'language': language,
+                'duration': 5.0
+            }
+        except sr.UnknownValueError:
+            raise Exception("无法识别音频内容")
+        except sr.RequestError as e:
+            raise Exception(f"Google Speech Recognition请求失败: {e}")
+
+    except ImportError:
+        return recognize_with_pydub(audio_path, language, enable_word_timestamp)
+
+
+def recognize_with_pydub(audio_path: str, language: str = 'zh', enable_word_timestamp: bool = True):
+    """
+    如果都不可用，提供一个有用的错误信息
+    """
+    raise Exception(
+        f"语音识别失败。需要安装以下至少一个库:\n"
+        f"1. pip install funasr torch torchaudio\n"
+        f"2. pip install SpeechRecognition pydub\n"
+        f"3. 或者配置FUNASR HTTP服务 (FUNASR_API_URL环境变量)"
+    )
+
+
+def split_audio_into_segments(audio_path: str, segment_duration: int = 30):
+    """
+    将长音频分割成短段进行识别（避免超时）
+    """
+    try:
+        from pydub import AudioSegment
+
+        audio = AudioSegment.from_file(audio_path)
+        total_duration = len(audio)  # 毫秒
+
+        segments = []
+        for i in range(0, total_duration, segment_duration * 1000):
+            segment = audio[i:i + segment_duration * 1000]
+            segments.append(segment)
+
+        return segments
+    except ImportError:
+        raise Exception("需要安装pydub库: pip install pydub")
+
+
+def main():
+    parser = argparse.ArgumentParser(description='语音识别脚本')
+    parser.add_argument('--audio', required=True, help='音频文件路径')
+    parser.add_argument('--language', default='zh', help='语言代码（zh或en）')
+    parser.add_argument('--enable-word-timestamp', default='1', help='是否启用词级时间戳')
+
+    args = parser.parse_args()
+
+    if not os.path.exists(args.audio):
+        print(json.dumps({
+            'success': False,
+            'error': f"音频文件不存在: {args.audio}"
+        }))
+        sys.exit(1)
+
+    try:
+        enable_word_timestamp = args.enable_word_timestamp == '1'
+
+        # 尝试多种识别方式
+        result = recognize_with_funasr(
+            args.audio,
+            args.language,
+            enable_word_timestamp
+        )
+
+        print(json.dumps(result))
+        sys.exit(0)
+
+    except Exception as e:
+        print(json.dumps({
+            'success': False,
+            'error': str(e),
+            'timestamp': datetime.now().isoformat()
+        }))
+        sys.exit(1)
+
+
+if __name__ == '__main__':
+    main()