Kadazandusun speech recognition: a case study

Currently, there is no existing system that provides common information and utilities for Kadazandusun’s speech recognition since Kadazandusun speech has different features that are not available in other languages. This paper presents a preliminary experiment using one of the famous feature extract...

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Bibliographic Details
Main Authors: Samry @ Mohd Shamrie Sainin, Mohd Hanafie Haris
Format: Article
Language:en
en
Published: UniSE Press 2021
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/33171/1/Kadazandusun%20speech%20recognition_%20a%20case%20study.pdf
https://eprints.ums.edu.my/id/eprint/33171/3/Kadazandusun%20speech%20recognition_%20a%20case%20study%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33171/
http://tost.unise.org/pdfs/vol8/no3-3/ToST-CoFA2020-560-567-OA.pdf
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Summary:Currently, there is no existing system that provides common information and utilities for Kadazandusun’s speech recognition since Kadazandusun speech has different features that are not available in other languages. This paper presents a preliminary experiment using one of the famous feature extraction methods which is Linear Prediction Cepstral Coefficients (LPCC). Further investigation on the speech data is using several classifier algorithms to investigate the recognition rate of Kadazandusun words. There are 6 words of Kadazandusun collected as an individual speech to test the feature extraction and the classifiers. The objectives of this study are to investigate LPCC feature extraction and to propose a suitable classifier algorithm for Kadazandusun speech data.