Vowel and consonant recognition in Turkish using neural networks toward continuous speech recognition

Autor:	T. Cakici, O. Parlaktuna, Hakan Tora, A. Barkana
Rok vydání:	2002
Předmět:	Consonant Sequence Artificial neural network Turkish Computer science Speech recognition Vowel Mid vowel language language.human_language Word (computer architecture) Electronic mail
Zdroj:	Proceedings of MELECON '94. Mediterranean Electrotechnical Conference.
DOI:	10.1109/melcon.1994.381146
Popis:	This paper describes an artificial neural network that recognizes vowels and consonants in Turkish when a word or word sequence is uttered. The recognition is performed by three groups of connected nets. Inputs of the nets are the magnitudes of the short time spectrum at 16 mel-scaled frequency points in the range of 240 to 4500 Hz. The first net differentiates the input as being a vowel or a consonant. The outputs of this net as well as the magnitudes of the short time spectrum are used as inputs to the nets for vowel and consonant recognition. Consonant-vowel (CV) or vowel-consonant (VC) fragments of 11 speakers were used for training the different nets, and fragments from 7 more speakers were used for testing. >
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5d4655eb05f52543d65f41bcd02f09cf https://doi.org/10.1109/melcon.1994.381146 Zobrazit plný text záznamu