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Phonem-based isolated Turkish word recognition with subspace classifier    
Yazarlar
Dr. Öğr. Üyesi Serkan KESER Dr. Öğr. Üyesi Serkan KESER
Kırşehir Ahi Evran Üniversitesi, Türkiye
Rifat Edizkan
Türkiye
Özet
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 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.
Anahtar Kelimeler
Bildiri Türü Tebliğ/Bildiri
Bildiri Alt Türü Tam Metin Olarak Yayımlanan Tebliğ (Ulusal Kongre/Sempozyum)
Bildiri Niteliği Alanında Hakemli Ulusal Kongre/Sempozyum
Bildiri Dili Türkçe
Kongre Adı 17th Signal Processing and Communications Applications Conference
Kongre Tarihi 09-04-2009 /
Basıldığı Ülke Türkiye
Basıldığı Şehir Antalya
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
SCOPUS 4
Google Scholar 13
Phonem-based isolated Turkish word recognition with subspace classifier

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