Development and Research of a System for Automatic Recognition of the Digits Yemeni Dialect of Arabic Speech Using Neural Networks-Reference-Cited by-同舟云学术

Development and Research of a System for Automatic Recognition of the Digits Yemeni Dialect of Arabic Speech Using Neural Networks

Published:2023-11-14 Issue:5 Volume:9 Page:35-42
ISSN:2712-8830
Container-title:Proceedings of Telecommunication Universities
language:
Short-container-title:jour

Author:

Radan N.H.¹^ORCID,Sidorov K.¹^ORCID

Affiliation:

1. Tver State Technical University

Abstract

The article describes the results of research on the development and testing of an automatic speech recognition system (SAR) in Arabic numerals using artificial neural networks. Sound recordings (speech signals) of the Arabic Yemeni dialect recorded in the Republic of Yemen were used for the research. SAR is an isolated system of recognition of whole words, it is implemented in two modes: "speaker-dependent system" (the same speakers are used for training and testing the system) and "speaker-independent system" (the speakers used for training the system differ from those used for testing it). In the process of speech recognition, the speech signal is cleared of noise using filters, then the signal is pre-localized, processed and analyzed by the Hamming window (a time alignment algorithm is used to compensate for differences in pronunciation). Informative features are extracted from the speech signal using mel-frequency cepstral coefficients. The developed SAR provides high accuracy of the recognition of Arabic numerals of the Yemeni dialect – 96.2 % (for a speaker-dependent system) and 98.8 % (for a speaker-independent system).

Publisher

Bonch-Bruevich State University of Telecommunications

Reference12 articles.

1. Al-Zabibi M. An acoustic-phonetic approach in automatic Arabic speech recognition. Loughborough University. Doctoral Thesis. 1990. URL: https://hdl.handle.net/2134/6949 [Accessed 02.10.2023]

2. Alkhouli M. Alaswaat Alaghawaiyah. Daar Alfalah, Jordan. 1990 (in Arabic)

3. Deller J., Hansen J., Proakis J. Discrete-Time Processing of Speech Signal. 1993. DOI:10.1109/9780470544402

4. Elshafei M. Toward an Arabic Text-to-Speech System. The Arabian Journal for Science and Engineering. 1991;16(4B):565‒583.

5. Hagos E. Implementation of an Isolated Word Recognition System. M.Sc. Thesis. King Fahd University of Petroleum & Minerals Dhahran, Saudi Arabia. 1985.