Isolated Pali Word (IPW) Feature Extraction using MFCC & KNN Based on ASR
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2018, Vol 20, Issue 6
Abstract
Speech is most prominent & primary mode of Communication among human being. Past after years of research and development & the accuracy of automatic speech recognition remains the important challenges in research. The design of Speech Recognition system require careful attentions the following issues: Definition of various types of speech classes, speech representation, feature extraction techniques, speech classifier, and database and performance evaluation. The problems are existing in ASR and the various techniques to solve these problems constructed by various research work have been presented in a chronological order. The objective of this research paper is to summarize and compare some of the well-known methods used in various stages of speech recognition system and to identify research topic and applications which is front of this exciting and challenging field. In this paper is computed acoustic features using MFCC on ‘IPW’ Isolated Pali Word Database which contain collection of isolated number (0-10) and isolated month (Jan-Dec) words of 20 speakers. The performance of the isolated digit and month’s words based on MFCC and KNN classification were 80.36% and 81.83% respectively.
Authors and Affiliations
Siddharth S More, Prashant kumar L. Borde, Sunil S Nimbhore
Keywords
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- EP ID EP423562
- DOI 10.9790/0661-2006026974.
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