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Experimental Analysis on Big Data in IOT-Based Architecture Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Significance of Frequency Band Selection of MFCC for Text-Independent Speaker Identification

Authors : S. B. Dhonde, S. M. Jagade

Published in: Proceedings of the International Conference on Data Engineering and Communication Technology

Publisher: Springer Singapore

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Abstract

This paper presents significance of Mel-frequency Cepstral Coefficients (MFCC) Frequency band selection for text-independent speaker identification. Recent studies have been focused on speaker specific information that may extends beyond telephonic passband. The selection of the frequency band is an important factor to effectively capture the speaker specific information present in the speech signal for speaker recognition. This paper focuses on development of a speaker identification system based on MFCC features which are modeled using vector quantization. Here, the frequency band is varied up to 7.75 kHz. Speaker identification experiments evaluated on TIMIT database consisting of 630 speaker shows that the average recognition rate achieved is 97.37 % in frequency band 0–4.85 kHz for 20 MFCC filters.

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previous chapter A New Approach to Determine Tie-Line Frequency Bias (B) in Interconnected Power System with Integral Control AGC Scheme
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Metadata
Title
Significance of Frequency Band Selection of MFCC for Text-Independent Speaker Identification
Authors
S. B. Dhonde
S. M. Jagade
Copyright Year
2017
Publisher
Springer Singapore
Book
Proceedings of the International Conference on Data Engineering and Communication Technology

Print ISBN: 978-981-10-1677-6

Electronic ISBN: 978-981-10-1678-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-1678-3_21

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