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dc.contributor.authorKeser S.
dc.contributor.authorEdizkan R.
dc.date.accessioned2019-11-24T21:00:38Z
dc.date.available2019-11-24T21:00:38Z
dc.date.issued2009
dc.identifier.isbn978142444-4366
dc.identifier.urihttps://dx.doi.org/10.1109/SIU.2009.5136340
dc.identifier.urihttps://hdl.handle.net/20.500.12513/3434
dc.description2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 --9 April 2009 through 11 April 2009 --Antalya --77539en_US
dc.description.abstractIn 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 classfication 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. ©2009 IEEE.en_US
dc.language.isoturen_US
dc.relation.isversionof10.1109/SIU.2009.5136340en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titlePhonem-based isolated Turkish word recognition with subspace classifier [Altuzay siniflama ile sesbirim temelli türkçe yalitik kelime tanima]en_US
dc.typeconferenceObjecten_US
dc.relation.journal2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009en_US
dc.contributor.departmentKırşehir Ahi Evran Üniversitesi, Teknik Bilimler Meslek Yüksekokulu, Elektrik ve Otomasyon Bölümüen_US
dc.identifier.startpage93en_US
dc.identifier.endpage96en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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