Open AccessA REVIEW: METHODS OF AUTOMATIC SPEECH SEGMENTATION
Author(s) -
Alexandr Pak,
A. Zhumageldikyzy,
N. Ermekova
Publication year - 2021
Publication title -
ķazaķstan-britan tehnikalyķ universitetìnìņ habaršysy
Language(s) - English
Resource type - Journals
eISSN - 2959-8109
pISSN - 1998-6688
DOI - 10.55452/1998-6688-2021-18-3-89-94
Subject(s) - segmentation , speech segmentation , computer science , speech recognition , hidden markov model , speech processing , artificial intelligence , wavelet , process (computing) , pattern recognition (psychology) , natural language processing , operating system
Segmentation is a process of dividing a speech signal into the basic units of language. Segmentation of the speech signals is one of the most important tasks in automatic speech processing systems. This paper proposes a review of methods of automatic speech segmentation. Moreover, methods of wavelet and Hilbert- Huang transformations and techniques based on hidden Markov models are considered.