PENGENALAN SUARA KE TEKS MENGGUNAKAN HIDDEN MARKOV MODEL

KURNIAWAN, IRVAN and Kurniati, Rizki and Arsalan, Osvari (2023) PENGENALAN SUARA KE TEKS MENGGUNAKAN HIDDEN MARKOV MODEL. Undergraduate thesis, Sriwijaya University.

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Abstract

Learning new words can be difficult, it helps if it’s possible to look up the new word in a dictionary, however, a word in English often sounds alike to another word, therefore a speech to text system can help searching a word in dictionary. The use of Mel-Frequency Cepstral Coefficient in feature extraction and Hidden Markov Model in recognizing speech to text was chosen because MFCC and Hidden Markov Model has better performance compared to other speech recognition machine learning methods thus in this research, an application for text to speech was developed using the combination of MFCC and Hidden Markov Model method. There are 3 HMM model that were developed by using 3 different datasets and using same configuration. The best model acquired 100% accuracy which came from second dataset that has strong and stable voice signal, clear pronunciation, and not lot of testing data.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ilmu Komputer, Teknik Informatika
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Irvan Kurniawan
Date Deposited:	12 Apr 2023 02:31
Last Modified:	12 Apr 2023 02:31
URI:	http://repository.unsri.ac.id/id/eprint/95623

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