{"title":"使用神经网络的语音识别","authors":"S. Khan, G. Sharma, P. Rao","doi":"10.1109/ICIT.2000.854165","DOIUrl":null,"url":null,"abstract":"The paper presents a continuous speech recognition system based on a neural network concept. An articulatory-phonetic feature extraction network (APFEN) is used for extracting articulatory-phonetic features. This is followed by a coarticulation network for reducing the effect of coarticulation present in the continuous speech. Algorithms for segmentation and then identification of phonemes are given.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Speech recognition using neural networks\",\"authors\":\"S. Khan, G. Sharma, P. Rao\",\"doi\":\"10.1109/ICIT.2000.854165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a continuous speech recognition system based on a neural network concept. An articulatory-phonetic feature extraction network (APFEN) is used for extracting articulatory-phonetic features. This is followed by a coarticulation network for reducing the effect of coarticulation present in the continuous speech. Algorithms for segmentation and then identification of phonemes are given.\",\"PeriodicalId\":405648,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2000.854165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2000.854165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper presents a continuous speech recognition system based on a neural network concept. An articulatory-phonetic feature extraction network (APFEN) is used for extracting articulatory-phonetic features. This is followed by a coarticulation network for reducing the effect of coarticulation present in the continuous speech. Algorithms for segmentation and then identification of phonemes are given.
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