@Article{csse.2018.33.429,
AUTHOR = {Erdem Yavuz, Vedat Topuz},
TITLE = {A Phoneme-Based Approach for Eliminating Out-of-vocabulary Problem Turkish Speech Recognition Using Hidden Markov Model},
JOURNAL = {Computer Systems Science and Engineering},
VOLUME = {33},
YEAR = {2018},
NUMBER = {6},
PAGES = {429--445},
URL = {http://www.techscience.com/csse/v33n6/39995},
ISSN = {},
ABSTRACT = {Since Turkish is a morphologically productive language, it is almost impossible for a word-based recognition system to be realized to completely model
Turkish language. Due to the fact that it is difficult for the system to recognize words not introduced to it in a word-based recognition system, recognition
success rate drops considerably caused by out-of-vocabulary words. In this study, a speaker-dependent, phoneme-based word recognition system has been
designed and implemented for Turkish Language to overcome the problem. An algorithm for finding phoneme-boundaries has been devised in order to
segment the word into its phonemes. After the segmentation of words into phonemes, each phoneme is separated into different sub-groups according to its
position and neighboring phonemes in that word. Generated sub-groups are represented by Hidden Markov Model, which is a statistical technique, using
Mel-frequency cepstral coefficients as feature vector. Since phoneme-based approach is adopted in this study, it has been successfully achieved that many
out of vocabulary words could be recognized.},
DOI = {10.32604/csse.2018.33.429}
}