Dimensionality Reduction of Speech Signals using Singular Value Decomposition and Karhunen-Loeve

Domy Kristomo, Yudhi Kusnanto

2019

Abstract

The design of speech recognition system requires the reliable feature in order to improve the performance of speech recognition system. Thus it requires the efficient feature in order to minimizing computational time and to obtaining the optimal classification result. This paper proposes the combined method of various time-frequency feature extraction techniques with singular value decomposition (SVD) for extracting, selecting, and classifying the Indonesian stop consonants in initial position of Consonant-Vowel (CV) syllables as well as the word of stop consonant. The results of the study are divided into two parts, first: the implementation of the extraction method and selection of features based on Singular Value Decomposition (SVD) on stop consonant data, second: the implementation of the extraction method and selection of features based on Singular Value Decomposition (SVD) on word sound data formed by stop consonants. The experimental result shows that SVD gives improved the classification scores. The classification of stop consonants is more difficult than classifying of word of stop consonants.

Paper Citation

in Harvard Style

Kristomo D. and Kusnanto Y. (2019). Dimensionality Reduction of Speech Signals using Singular Value Decomposition and Karhunen-Loeve.In Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST, ISBN 978-989-758-453-4, pages 78-84. DOI: 10.5220/0009432200780084

in Bibtex Style

@conference{conrist19,
author={Domy Kristomo and Yudhi Kusnanto},
title={Dimensionality Reduction of Speech Signals using Singular Value Decomposition and Karhunen-Loeve},
booktitle={Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,},
year={2019},
pages={78-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009432200780084},
isbn={978-989-758-453-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,
TI - Dimensionality Reduction of Speech Signals using Singular Value Decomposition and Karhunen-Loeve
SN - 978-989-758-453-4
AU - Kristomo D.
AU - Kusnanto Y.
PY - 2019
SP - 78
EP - 84
DO - 10.5220/0009432200780084