guoyu/Test/python/speech_server.py

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
PaddleSpeech 语音识别服务
Windows 版本
"""
from flask import Flask, request, jsonify
from flask_cors import CORS
import os
import time
from difflib import SequenceMatcher
app = Flask(__name__)
CORS(app) # 允许跨域
# 全局变量
asr_model = None
model_loaded = False
def init_model():
"""初始化语音识别模型"""
global asr_model, model_loaded
print("正在加载 PaddleSpeech 模型...")
try:
from paddlespeech.cli.asr.infer import ASRExecutor
asr_model = ASRExecutor()
model_loaded = True
print("✓ 模型加载成功!")
return True
except Exception as e:
print(f"✗ 模型加载失败: {str(e)}")
print("提示:首次运行会自动下载模型,需要等待...")
model_loaded = False
return False
def calculate_similarity(text1, text2):
"""计算文本相似度0-100分"""
if not text1 or not text2:
return 0
# 去除空格和标点
text1 = ''.join(filter(str.isalnum, text1))
text2 = ''.join(filter(str.isalnum, text2))
if not text1 or not text2:
return 0
# 计算相似度
similarity = SequenceMatcher(None, text1, text2).ratio()
return round(similarity * 100, 2)
@app.route('/api/speech/recognize', methods=['POST'])
def recognize():
"""语音识别接口"""
try:
# 检查模型是否加载
if not model_loaded:
return jsonify({
'code': 500,
'msg': '模型未加载,请稍后重试'
}), 500
# 检查文件
if 'audio' not in request.files:
return jsonify({
'code': 400,
'msg': '未上传音频文件'
}), 400
audio_file = request.files['audio']
reference_text = request.form.get('referenceText', '')
# 保存临时文件
temp_dir = './temp_audio'
if not os.path.exists(temp_dir):
os.makedirs(temp_dir)
timestamp = str(int(time.time() * 1000))
temp_path = os.path.join(temp_dir, f'audio_{timestamp}.wav')
audio_file.save(temp_path)
print(f"收到音频文件: {temp_path}")
print(f"参考文本: {reference_text}")
# 识别音频
try:
result = asr_model(audio_input=temp_path, force_yes=True)
recognized_text = result if isinstance(result, str) else str(result)
print(f"识别结果: {recognized_text}")
# 计算相似度
score = calculate_similarity(recognized_text, reference_text)
# 简单的发音和流利度评分(可以后续优化)
pronunciation_score = max(0, score - 5)
fluency_score = max(0, score - 3)
# 删除临时文件
try:
os.remove(temp_path)
except:
pass
return jsonify({
'code': 200,
'msg': '成功',
'data': {
'recognizedText': recognized_text,
'score': score,
'pronunciationScore': pronunciation_score,
'fluencyScore': fluency_score,
'status': 'completed'
}
})
except Exception as e:
print(f"识别失败: {str(e)}")
try:
os.remove(temp_path)
except:
pass
return jsonify({
'code': 500,
'msg': f'识别失败: {str(e)}'
}), 500
except Exception as e:
print(f"处理错误: {str(e)}")
return jsonify({
'code': 500,
'msg': f'处理失败: {str(e)}'
}), 500
@app.route('/api/speech/health', methods=['GET'])
def health():
"""健康检查"""
return jsonify({
'code': 200,
'msg': '服务正常',
'data': {
'model_loaded': model_loaded
}
})
if __name__ == '__main__':
print("=" * 50)
print("PaddleSpeech 语音识别服务")
print("=" * 50)
print("")
# 初始化模型(首次会下载,需要时间)
init_model()
print("")
print("=" * 50)
print("服务启动成功!")
print("访问地址: http://localhost:5000")
print("健康检查: http://localhost:5000/api/speech/health")
print("=" * 50)
print("")
# 启动服务
app.run(host='0.0.0.0', port=5000, debug=False)