JOURNAL ARTICLE

Speech Recognition using Artificial Neural Networks

Abstract

As most of the researches on speech recognition (SR) are based on hidden Markov models (HMM), the main theme of this paper is the recognition of Arabic sounds using artificial neural networks. Despite the fact that Arabic is a language that is spoken by millions of people, and it is the sixth (K. Kirchhoff and J. Bilmes, 2002) spoken language in the world, we have faced a scarcity of researches in Arabic language recognition during the preparation of this paper. Speech recognition systems will become more used as they started to replace some of the functions normally accomplished with a keyboard, these and many other reasons encouraged us to continue in this field

Keywords:
Hidden Markov model Computer science Speech recognition Artificial neural network Arabic Artificial intelligence Natural language processing Field (mathematics) Speaker recognition Linguistics Mathematics

Metrics

14
Cited By
1.18
FWCI (Field Weighted Citation Impact)
3
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

JOURNAL ARTICLE

Speech Emotion Recognition using Artificial Neural Networks

P PrithviT. K. Satish Kumar

Journal:   International Journal of Scientific Engineering and Research Year: 2016 Vol: 4 (5)Pages: 8-10
JOURNAL ARTICLE

Speech Command Recognition using Artificial Neural Networks

Sushan PoudelR. Anuradha

Journal:   JOIV International Journal on Informatics Visualization Year: 2020 Vol: 4 (2)Pages: 73-75
JOURNAL ARTICLE

Thai Speech Emotion Recognition Using Artificial Neural Networks

Watchara SothiritWaranya PoonnawatNuttaporn Hencharoenlert

Journal:   Information Technology Journal Year: 2024 Vol: 20 (1)Pages: 97-105
© 2026 ScienceGate Book Chapters — All rights reserved.