{"title":"小波变换在语音信号处理中的优势","authors":"Sayora Ibragimova","doi":"10.26739/2181-9696-2021-3-6","DOIUrl":null,"url":null,"abstract":"This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform","PeriodicalId":41669,"journal":{"name":"Archives for Technical Sciences","volume":"59 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS\",\"authors\":\"Sayora Ibragimova\",\"doi\":\"10.26739/2181-9696-2021-3-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform\",\"PeriodicalId\":41669,\"journal\":{\"name\":\"Archives for Technical Sciences\",\"volume\":\"59 1\",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2021-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives for Technical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26739/2181-9696-2021-3-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, GEOLOGICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives for Technical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26739/2181-9696-2021-3-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS
This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform