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Hindi Pronunciation Analysis for Speech Impaired using MFCC and DTW

by Sahil Panchbhaiya, Pranav Menon, Rishikesh Lingayat, Nikhita Mangaonkar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 31
Year of Publication: 2024
Authors: Sahil Panchbhaiya, Pranav Menon, Rishikesh Lingayat, Nikhita Mangaonkar
10.5120/ijca2024923887

Sahil Panchbhaiya, Pranav Menon, Rishikesh Lingayat, Nikhita Mangaonkar . Hindi Pronunciation Analysis for Speech Impaired using MFCC and DTW. International Journal of Computer Applications. 186, 31 ( Aug 2024), 48-54. DOI=10.5120/ijca2024923887

@article{ 10.5120/ijca2024923887,
author = { Sahil Panchbhaiya, Pranav Menon, Rishikesh Lingayat, Nikhita Mangaonkar },
title = { Hindi Pronunciation Analysis for Speech Impaired using MFCC and DTW },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2024 },
volume = { 186 },
number = { 31 },
month = { Aug },
year = { 2024 },
issn = { 0975-8887 },
pages = { 48-54 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number31/hindi-pronunciation-analysis-for-speech-impaired-using-mfcc-and-dtw/ },
doi = { 10.5120/ijca2024923887 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-08-11T02:24:43.897894+05:30
%A Sahil Panchbhaiya
%A Pranav Menon
%A Rishikesh Lingayat
%A Nikhita Mangaonkar
%T Hindi Pronunciation Analysis for Speech Impaired using MFCC and DTW
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 31
%P 48-54
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of this experiment is to educate speech-impaired learners on the pronunciation of Hindi syllables by providing word breakdowns, sounds, and examples of their usage. After the speaker becomes familiar with the syllables, a voice sample from the user is taken as input and analyzed to determine whether it matches the predefined data, ensuring that the speaker is following correctly. This feature matching is performed using Dynamic Time Warping (DTW) and Mel-Frequency Cepstral Coefficients (MFCC). The process is carried out using a combination of MFCC and DTW. In the two-step process of speech analysis, MFCC is used in the first phase to extract fourteen features, and the second phase employs three unique classifiers: k-Nearest Neighbour (KNN), Support Vector Machine (SVM), and Dynamic Time Warping (DTW) to determine the best combination for accurate and precise feature matching.

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Index Terms

Computer Science
Information Sciences

Keywords

Mel Frequency Cepstral Frequency(MFCC); Dynamic Time Warping(DTW); k-Nearest Neighbour(KNN); Support Vector Machine(SVM); Speech Impairment; Hindi Syllables

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