大数据分析和语音识别的机器同步智能英语翻译系统  

Machine⁃synchronized intelligent English translation system for big data analysis and speech recognition

作　　者：宋洪玲 SONG Hongling(Harbin Medical University(Daqing),Daqing 163319,China)

机构地区：[1]哈尔滨医科大学大庆分校,黑龙江大庆163319

出　　处：《电子设计工程》2025年第9期43-47,共5页Electronic Design Engineering

摘　　要：在跨语言交流中,为了实现更加顺畅的无障碍交流,设计了基于大数据分析和语音识别的机器同步智能英语翻译系统。语音识别模块、翻译模块以及语音合成模块构成同步智能英语翻译系统,结合Mel频率倒谱系数(Mel Frequency Cepstrum Coefficient,MFCC)对语音数据信号进行特征提取,同时结合LSTM循环神经网络与词性向量进行语音翻译,以期使机器同步智能英语翻译系统快速准确地运行。经过实验验证,研究系统的匹配率平均达到94.7%,同时语言识别时间相较其他系统显著缩短,语音翻译及时高效。In cross-language communication,to achieve smoother and barrier-free interaction,a machine-synchronized intelligent English translation system based on big data analysis and speech recognition has been designed.The speech recognition module,translation module and speech synthesis module are used to form a synchronous intelligent English translation system,combined with Mel Frequency Cepstrum Coefficient(Mel Frequency Cepstrum Coefficient,MFCC)to extract the features of speech data signals,and combined with LSTM recurrent neural network and part-of-speech vector for speech translation,in order to make the machine synchronous intelligent English translation system fast and accurate.After experimental verification,the matching rate of the research system reaches 94.7%on average,and the language recognition time is significantly shorter than that of other systems,and the speech translation is timely and efficient.

关 键 词：语音识别 LSTM神经网络 同步翻译 数据特征处理 隐马尔可夫模型 

分 类 号：TN919.34[电子电信—通信与信息系统]