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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Towards an Automatic Speech-to-Text Transcription System: Amazigh Language

Author 1: Ahmed Ouhnini
Author 2: Brahim Aksasse
Author 3: Mohammed Ouanan

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2023.0140250

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 2, 2023.

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Abstract: Various studies inside the domain of research and the development of automatic speech recognition (ASR) technologies for several languages have not yet been published and thoroughly investigated. Nevertheless, the unique acoustic features of the Amazigh language, for example, Amazigh's consonant emphasis, pose many obstacles to the development of automatic speech recognition systems. In this study, we examine Amazigh language voice recognition. We treat the problem by focusing on transitions in vowel and consonant sounds and formant frequencies of phonemes. We present a hybrid strategy for phoneme separation based on energy differences. This includes analysis of consonant and vowel features, and identification methods based on formant analysis.

Keywords: Speech recognition system; Amazigh language; analyzing formants and pitch; speech corpus; artificial intelligence

Ahmed Ouhnini, Brahim Aksasse and Mohammed Ouanan, “Towards an Automatic Speech-to-Text Transcription System: Amazigh Language” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140250

@article{Ouhnini2023,
title = {Towards an Automatic Speech-to-Text Transcription System: Amazigh Language},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140250},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140250},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Ahmed Ouhnini and Brahim Aksasse and Mohammed Ouanan}
}


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