{"title":"结合语音缺失概率的语音增强算法","authors":"Ruirui Han, Ying Gao, Chen Chen","doi":"10.12677/hjwc.2018.84016","DOIUrl":null,"url":null,"abstract":"The research work of this paper is mainly on the basis of the amplitude squared spectrum least mean square estimator and proposes a new algorithm. Due to the uncertainty of the speech in the statistical model of noisy speech, the unified processing of speech signals will inevitably result in the loss of speech components, which will affect the performance of speech enhancement. Therefore, this paper mainly studies and estimates the frequency of each signal. The speech probability is then combined with the gain function of the squared spectrum least mean square error algorithm to derive a new gain function. Finally, we can see through the experimental simulation, the algorithm proposed in this paper can significantly improve the voice quality and improve the intelligibility of the voice.","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"08 1","pages":"141-147"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Speech Enhancement Algorithm Combining Speech Absence Probability\",\"authors\":\"Ruirui Han, Ying Gao, Chen Chen\",\"doi\":\"10.12677/hjwc.2018.84016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research work of this paper is mainly on the basis of the amplitude squared spectrum least mean square estimator and proposes a new algorithm. Due to the uncertainty of the speech in the statistical model of noisy speech, the unified processing of speech signals will inevitably result in the loss of speech components, which will affect the performance of speech enhancement. Therefore, this paper mainly studies and estimates the frequency of each signal. The speech probability is then combined with the gain function of the squared spectrum least mean square error algorithm to derive a new gain function. Finally, we can see through the experimental simulation, the algorithm proposed in this paper can significantly improve the voice quality and improve the intelligibility of the voice.\",\"PeriodicalId\":66606,\"journal\":{\"name\":\"无线通信\",\"volume\":\"08 1\",\"pages\":\"141-147\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"无线通信\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.12677/hjwc.2018.84016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"无线通信","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.12677/hjwc.2018.84016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speech Enhancement Algorithm Combining Speech Absence Probability
The research work of this paper is mainly on the basis of the amplitude squared spectrum least mean square estimator and proposes a new algorithm. Due to the uncertainty of the speech in the statistical model of noisy speech, the unified processing of speech signals will inevitably result in the loss of speech components, which will affect the performance of speech enhancement. Therefore, this paper mainly studies and estimates the frequency of each signal. The speech probability is then combined with the gain function of the squared spectrum least mean square error algorithm to derive a new gain function. Finally, we can see through the experimental simulation, the algorithm proposed in this paper can significantly improve the voice quality and improve the intelligibility of the voice.