{"title":"基于音素的土耳其孤立词子空间分类器识别","authors":"Serkan Keser, R. Edizkan","doi":"10.1109/SIU.2009.5136340","DOIUrl":null,"url":null,"abstract":"In this study, phoneme-based isolated Turkish word recognition with Common Vector Approach (CVA) has been performed. CVA has been used to classify phonemes. The phoneme sequence obtained from the classification is decoded into the word using redundant hash addressing (RHA). The phoneme-based speech recognition is more suitable than the word-based speech recognition for implementing applications that use different words in their dictionaries. For that reason, in this study the CVA is evaluated to see whether it could be used in phoneme-based word recognition or not. In the experimental study we obtained the word recognition rates 70–80% from randomly selected words in METU database. It might be possible to obtain higher recognition rates by improving the CVA and by using different word decoding techniques.","PeriodicalId":219938,"journal":{"name":"2009 IEEE 17th Signal Processing and Communications Applications Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Phonem-based isolated Turkish word recognition with subspace classifier\",\"authors\":\"Serkan Keser, R. Edizkan\",\"doi\":\"10.1109/SIU.2009.5136340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, phoneme-based isolated Turkish word recognition with Common Vector Approach (CVA) has been performed. CVA has been used to classify phonemes. The phoneme sequence obtained from the classification is decoded into the word using redundant hash addressing (RHA). The phoneme-based speech recognition is more suitable than the word-based speech recognition for implementing applications that use different words in their dictionaries. For that reason, in this study the CVA is evaluated to see whether it could be used in phoneme-based word recognition or not. In the experimental study we obtained the word recognition rates 70–80% from randomly selected words in METU database. It might be possible to obtain higher recognition rates by improving the CVA and by using different word decoding techniques.\",\"PeriodicalId\":219938,\"journal\":{\"name\":\"2009 IEEE 17th Signal Processing and Communications Applications Conference\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE 17th Signal Processing and Communications Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2009.5136340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE 17th Signal Processing and Communications Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2009.5136340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Phonem-based isolated Turkish word recognition with subspace classifier
In this study, phoneme-based isolated Turkish word recognition with Common Vector Approach (CVA) has been performed. CVA has been used to classify phonemes. The phoneme sequence obtained from the classification is decoded into the word using redundant hash addressing (RHA). The phoneme-based speech recognition is more suitable than the word-based speech recognition for implementing applications that use different words in their dictionaries. For that reason, in this study the CVA is evaluated to see whether it could be used in phoneme-based word recognition or not. In the experimental study we obtained the word recognition rates 70–80% from randomly selected words in METU database. It might be possible to obtain higher recognition rates by improving the CVA and by using different word decoding techniques.
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