{"title":"基于上下文的CD-DNN-HMM连续语音关键字识别","authors":"Hinda Dridi, K. Ouni","doi":"10.1109/ATSIP.2017.8075541","DOIUrl":null,"url":null,"abstract":"In this paper we describe a systematic procedure to implement two-stage based keywords spotting system (KWS). In first stage, a phonetic decoding of continuous speech is obtained using a CD-DNN-HMM model built with the Kaldi toolkit. In second stage, these results of phonetic transcriptions will serve to construct a system to search the keywords embedded in continuous speech using the classification and regression tree (CART) implemented with the software MATLAB. The work will be done using the TIMIT data base.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hybrid context dependent CD-DNN-HMM keywords spotting on continuous speech\",\"authors\":\"Hinda Dridi, K. Ouni\",\"doi\":\"10.1109/ATSIP.2017.8075541\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we describe a systematic procedure to implement two-stage based keywords spotting system (KWS). In first stage, a phonetic decoding of continuous speech is obtained using a CD-DNN-HMM model built with the Kaldi toolkit. In second stage, these results of phonetic transcriptions will serve to construct a system to search the keywords embedded in continuous speech using the classification and regression tree (CART) implemented with the software MATLAB. The work will be done using the TIMIT data base.\",\"PeriodicalId\":259951,\"journal\":{\"name\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATSIP.2017.8075541\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP.2017.8075541","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid context dependent CD-DNN-HMM keywords spotting on continuous speech
In this paper we describe a systematic procedure to implement two-stage based keywords spotting system (KWS). In first stage, a phonetic decoding of continuous speech is obtained using a CD-DNN-HMM model built with the Kaldi toolkit. In second stage, these results of phonetic transcriptions will serve to construct a system to search the keywords embedded in continuous speech using the classification and regression tree (CART) implemented with the software MATLAB. The work will be done using the TIMIT data base.
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