KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ
Speaker recognition can be considered as a subset of the more general area known as pattern recognition, which may be viewed basically in three stages as: feature selection and extraction, classification, and pattern matching. Extensive research in the past has been directed towards finding effectiv...
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| Format: | Article |
| Language: | English |
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Pamukkale University
2001-01-01
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| Series: | Pamukkale University Journal of Engineering Sciences |
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| Online Access: | http://dergipark.ulakbim.gov.tr/pajes/article/view/5000089841 |
| _version_ | 1797909635700621312 |
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| author | Figen ERTAŞ |
| author_facet | Figen ERTAŞ |
| author_sort | Figen ERTAŞ |
| collection | DOAJ |
| description | Speaker recognition can be considered as a subset of the more general area known as pattern recognition, which may be viewed basically in three stages as: feature selection and extraction, classification, and pattern matching. Extensive research in the past has been directed towards finding effective speech characteristics for speaker recognition. But, so far, no feature set is found to be known to allow perfect discrimination for all conditions. As the performance of features depends on the nature of application, the selection of salient features is a key step in the recognition process. In this paper, we present a general view of speech features and well known classifiers originally developed for text-independent speaker recognition systems. A comparative discussion on choice of suitable speech features and classification techniques is also given. |
| first_indexed | 2024-04-10T11:11:25Z |
| format | Article |
| id | doaj.art-a57ff6fae7794c0f8b7295d39988c79c |
| institution | Directory Open Access Journal |
| issn | 1300-7009 2147-5881 |
| language | English |
| last_indexed | 2024-04-10T11:11:25Z |
| publishDate | 2001-01-01 |
| publisher | Pamukkale University |
| record_format | Article |
| series | Pamukkale University Journal of Engineering Sciences |
| spelling | doaj.art-a57ff6fae7794c0f8b7295d39988c79c2023-02-15T16:19:02ZengPamukkale UniversityPamukkale University Journal of Engineering Sciences1300-70092147-58812001-01-017147545000083909KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİFigen ERTAŞSpeaker recognition can be considered as a subset of the more general area known as pattern recognition, which may be viewed basically in three stages as: feature selection and extraction, classification, and pattern matching. Extensive research in the past has been directed towards finding effective speech characteristics for speaker recognition. But, so far, no feature set is found to be known to allow perfect discrimination for all conditions. As the performance of features depends on the nature of application, the selection of salient features is a key step in the recognition process. In this paper, we present a general view of speech features and well known classifiers originally developed for text-independent speaker recognition systems. A comparative discussion on choice of suitable speech features and classification techniques is also given.http://dergipark.ulakbim.gov.tr/pajes/article/view/5000089841Özellik, Sınıflandırma, Doğrusal öngörülü kodlama, Gizli, Markov modeli, Karma Gaussian modeli |
| spellingShingle | Figen ERTAŞ KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ Pamukkale University Journal of Engineering Sciences Özellik, Sınıflandırma, Doğrusal öngörülü kodlama, Gizli, Markov modeli, Karma Gaussian modeli |
| title | KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ |
| title_full | KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ |
| title_fullStr | KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ |
| title_full_unstemmed | KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ |
| title_short | KONUŞMACI TANIMA İÇİN ÖZELLİK SEÇİMİ VE SINIFLANDIRMA TEKNİKLERİ |
| title_sort | konusmaci tanima icin ozellik secimi ve siniflandirma teknikleri |
| topic | Özellik, Sınıflandırma, Doğrusal öngörülü kodlama, Gizli, Markov modeli, Karma Gaussian modeli |
| url | http://dergipark.ulakbim.gov.tr/pajes/article/view/5000089841 |
| work_keys_str_mv | AT figenertas konusmacitanimaicinozelliksecimivesiniflandirmateknikleri |