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Analysis of Speech and its Fluency Disorders

Monica Mundada, Sangramsing N. Kayte. Published in Signal Processing

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Monica Mundada, Sangramsing N. Kayte
10.5120/ijais2016451484
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  1. Monica Mundada and Sangramsing N Kayte. Article: Analysis of Speech and its Fluency Disorders. International Journal of Applied Information Systems 10(4):10-12, January 2016. BibTeX

    @article{key:article,
    	author = "Monica Mundada and Sangramsing N. Kayte",
    	title = "Article: Analysis of Speech and its Fluency Disorders",
    	journal = "International Journal of Applied Information Systems",
    	year = 2016,
    	volume = 10,
    	number = 4,
    	pages = "10-12",
    	month = "January",
    	note = "Published by Foundation of Computer Science (FCS), NY, USA"
    }
    

Abstract

The oldest way of communication and information exchange between human beings is speech. It is the most prominent and natural form of communication between humans. Speech has potential of being important mode of interaction with computer. The communication among human and computer is called human computer interaction. Man machine interface have always proved a challenging area in natural language processing and in speech recognition research. The primary aim of the study is to distinguish the difference between normal and abnormal speech. It aims to prepare a layout of factors for different types of speech and voices and its core production system. The speech disorders like misarticulation and stammering are studied with its features and associated existing therapies. The distinction is experimented with various techniques such as MFCC, DTW and K-means. The mean value of MFCC coefficients are explored for speech disorders and normal speech samples. The Euclidean distance measure is calculated between normal and abnormal speech and the variations lying in them are studied further. t-test is also experimented to justify the classification result.

Reference

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  11. Sangramsing N.kayte “Marathi Isolated-Word Automatic Speech Recognition System based on Vector Quantization (VQ) approach” 101th Indian Science Congress Jammu University 03th Feb to 07 Feb 2014.
  12. Monica Mundada, Sangramsing Kayte “Classification of speech and its related fluency disorders Using KNN” ISSN2231-0096 Volume-4 Number-3 Sept 2014
  13. Monica Mundada, Sangramsing Kayte, Dr. Bharti Gawali "Classification of Fluent and Dysfluent Speech Using KNN Classifier" International Journal of Advanced Research in Computer Science and Software Engineering Volume 4, Issue 9, September 2014
  14. Monica Mundada, Bharti Gawali, Sangramsing Kayte "Recognition and classification of speech and its related fluency disorders" International Journal of Computer Science and Information Technologies (IJCSIT)

Keywords

MFCC, DTW, K-Clustering