语音识别、翻译及语音合成

Speech recognition, translation and speech synthesis.

python 复制代码
#语音识别、翻译及语音合成
#pip install SpeechRecognition gtts googletrans==3.1.0a0 pyaudio sounddevice soundfile keyboard

import speech_recognition as sr
from gtts import gTTS
from googletrans import Translator
import os
import time
import pyaudio
import logging
import argparse
import sounddevice as sd
import soundfile as sf
import numpy as np
import keyboard
import requests
from datetime import datetime

class SpeechTranslationApp:
    def __init__(self, source_language='en-US', target_language='zh-CN', input_type='microphone', save_transcript=False):
        """
        Initialize the Speech Translation Application
        
        :param source_language: Language of input speech
        :param target_language: Language to translate to
        :param input_type: Input method (microphone or system_sound)
        :param save_transcript: Whether to save speech recognition results
        """
        # Configure logging
        logging.basicConfig(
            level=logging.INFO, 
            format='%(asctime)s - %(levelname)s: %(message)s',
            datefmt='%Y-%m-%d %H:%M:%S'
        )
        self.logger = logging.getLogger(__name__)

        # Speech recognition setup
        self.recognizer = sr.Recognizer()
        self.translator = Translator()
        
        # Configuration
        self.source_language = source_language
        self.target_language = target_language
        self.input_type = input_type
        self.save_transcript = save_transcript

        # Audio parameters
        self.CHUNK = 1024
        self.FORMAT = pyaudio.paInt16
        self.CHANNELS = 1
        self.RATE = 44100
        self.RECORD_SECONDS = 5

        # API endpoint (replace with the actual API URL from the GitHub project)
        self.ASR_API_URL = "https://api.example.com/asr"  # Update with actual API endpoint

    def recognize_speech(self):
        """
        Recognize speech from either microphone or system sound
        
        :return: Dictionary with recognition results
        """
        result = {
            'success': False,
            'text': None,
            'error': None
        }

        try:
            if self.input_type == "microphone":
                with sr.Microphone() as source:
                    self.logger.info(f"Listening (Language: {self.source_language})...")
                    audio = self.recognizer.listen(source, timeout=5, phrase_time_limit=5)
            elif self.input_type == "system_sound":
                # Record system audio using sounddevice
                self.logger.info(f"Capturing system sound (Language: {self.source_language})...")
                recording = sd.rec(
                    int(self.RECORD_SECONDS * self.RATE), 
                    samplerate=self.RATE, 
                    channels=self.CHANNELS
                )
                sd.wait()
                
                # Save recording to temporary file
                temp_audio_file = 'temp_system_audio.wav'
                sf.write(temp_audio_file, recording, self.RATE)
                
                # Convert to speech_recognition format
                with sr.AudioFile(temp_audio_file) as source:
                    audio = self.recognizer.record(source)
                
                # Clean up temporary file
                os.remove(temp_audio_file)
            else:
                raise ValueError("Invalid input type. Choose 'microphone' or 'system_sound'")

            # Recognize speech
            text = self.recognizer.recognize_google(audio, language=self.source_language)
            
            # Send to ASR API
            self.send_to_asr_api(audio)
            
            result['success'] = True
            result['text'] = text
            self.logger.info(f"Speech Recognition Result: {text}")
            
            # Save transcript if enabled
            if self.save_transcript:
                self.save_speech_to_file(text)

        except sr.WaitTimeoutError:
            result['error'] = "Listening timed out. No speech detected."
            self.logger.warning(result['error'])
        except sr.UnknownValueError:
            result['error'] = "Could not understand the audio"
            self.logger.warning(result['error'])
        except sr.RequestError as e:
            result['error'] = f"Could not request results from Google Speech Recognition service; {e}"
            self.logger.error(result['error'])
        except Exception as e:
            result['error'] = f"An unexpected error occurred: {e}"
            self.logger.error(result['error'])
        
        return result

    def send_to_asr_api(self, audio):
        """
        Send audio to ASR API for processing
        
        :param audio: Recognized audio data
        """
        try:
            # Convert audio to a format suitable for API upload
            audio_data = audio.get_wav_data()
            
            # Prepare files for upload
            files = {'audio': ('speech.wav', audio_data, 'audio/wav')}
            
            # Send to ASR API (replace with actual API call)
            response = requests.post(self.ASR_API_URL, files=files)
            
            if response.status_code == 200:
                self.logger.info("Successfully sent audio to ASR API")
            else:
                self.logger.warning(f"ASR API request failed with status {response.status_code}")
        
        except Exception as e:
            self.logger.error(f"Error sending audio to ASR API: {e}")

    def save_speech_to_file(self, text):
        """
        Save recognized speech to a text file
        
        :param text: Recognized text
        """
        try:
            # Create transcripts directory if it doesn't exist
            os.makedirs('transcripts', exist_ok=True)
            
            # Generate filename with timestamp
            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
            filename = f"transcripts/speech_transcript_{timestamp}.txt"
            
            with open(filename, 'w', encoding='utf-8') as f:
                f.write(text)
            
            self.logger.info(f"Transcript saved to {filename}")
        
        except Exception as e:
            self.logger.error(f"Error saving transcript: {e}")

    def translate_text(self, text):
        """
        Translate text to target language
        
        :param text: Text to translate
        :return: Translated text
        """
        try:
            translation = self.translator.translate(text, dest=self.target_language)
            self.logger.info(f"Translation Result: {translation.text}")
            return translation.text
        except Exception as e:
            self.logger.error(f"Translation error: {e}")
            return None

    def speak_text(self, text):
        """
        Convert text to speech and play
        
        :param text: Text to convert to speech
        """
        try:
            tts = gTTS(text=text, lang=self.target_language)
            output_file = "translation_output.mp3"
            tts.save(output_file)
            
            # Cross-platform audio playback
            if os.name == 'nt':  # Windows
                os.system(f"start {output_file}")
            elif os.name == 'posix':  # macOS and Linux
                os.system(f"mpg123 {output_file}")
            
            # Remove temporary file after playback
            time.sleep(2)  # Give time for playback
            os.remove(output_file)
        except Exception as e:
            self.logger.error(f"Text-to-speech error: {e}")

    def run(self):
        """
        Main application loop
        """
        self.logger.info("Speech Translation App Started")
        
        print("Press 'Esc' to exit the application")
        
        try:
            while not keyboard.is_pressed('esc'):
                # Recognize speech
                recognition_result = self.recognize_speech()
                
                if recognition_result['success']:
                    # Translate recognized text
                    translated_text = self.translate_text(recognition_result['text'])
                    
                    if translated_text:
                        # Speak translated text
                        self.speak_text(translated_text)
                else:
                    # Log or handle unsuccessful recognition
                    if recognition_result['error']:
                        print(f"Recognition error: {recognition_result['error']}")
                
                # Pause to prevent excessive processing
                time.sleep(2)
        
        except KeyboardInterrupt:
            self.logger.info("Application stopped by user")
        finally:
            print("Speech Translation App Closed")

def main():
    """
    Parse command-line arguments and start the application
    """
    parser = argparse.ArgumentParser(description='Speech Translation Application')
    parser.add_argument('--source_lang', default='en-US', help='Source language code')
    parser.add_argument('--target_lang', default='zh-CN', help='Target language code')
    parser.add_argument('--input', choices=['microphone', 'system_sound'], default='microphone', help='Input method')
    parser.add_argument('--save_transcript', action='store_true', help='Save speech transcripts')
    
    args = parser.parse_args()
    
    app = SpeechTranslationApp(
        source_language=args.source_lang, 
        target_language=args.target_lang, 
        input_type=args.input,
        save_transcript=args.save_transcript
    )
    
    app.run()

if __name__ == "__main__":
    main()
相关推荐
毕设源码-钟学长12 分钟前
【开题答辩全过程】以 基于Python的车辆管理系统为例,包含答辩的问题和答案
开发语言·python
CCPC不拿奖不改名32 分钟前
数据处理与分析:数据可视化的面试习题
开发语言·python·信息可视化·面试·职场和发展
液态不合群34 分钟前
线程池和高并发
开发语言·python
旦莫1 小时前
Pytest教程:Pytest与主流测试框架对比
人工智能·python·pytest
数据大魔方1 小时前
【期货量化实战】螺纹钢量化交易指南:品种特性与策略实战(TqSdk完整方案)
python·算法·github·程序员创富·期货程序化·期货量化·交易策略实战
旻璿gg1 小时前
paddleocr、paddleocrvl、ppocrv5
python
清水白石0081 小时前
手写超速 CSV 解析器:利用 multiprocessing 与 mmap 实现 10 倍 Pandas 加速
python·pandas
Corleo2 小时前
记录一次复杂的 ONNX 到 TensorRT 动态 Shape 转换排错过程
python·ai
shughui2 小时前
Python基础面试题:语言定位+数据类型+核心操作+算法实战(含代码实例)
开发语言·python·算法
No0d1es2 小时前
2025年12月电子学会青少年软件编程Python六级等级考试真题试卷
开发语言·python·青少年编程·等级考试·电子学会