Using Approximate Entropy as a speech quality measure for a speaker recognition system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we will show that Approximate Entropy (ApEn) can be used to detect high-quality speech frames in an otherwise distorted speech signal. By exploiting the property of quasi-periodicity in speech, ApEn is able to detect small aberrations in speech frames that would otherwise cause a decrease in the performance in an automatic speaker recognition (ASR) system. In addition, we obtain the statistics of ApEn values representative of clean speech and propose threshold bounds to obtain maximum recognition rates. When compared to other popular voice activity detector (VAD) algorithms, our simulation results showed that utilization of ApEn will outperform the other VADs in discerning clean speech from noisy speech. This ability to properly detect clean speech allows for a speaker recognition system to obtain a recognition rate close to 87%, which is close to the same performance of the system when noise is not present.

Original languageEnglish (US)
Title of host publication2016 50th Annual Conference on Information Systems and Sciences, CISS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages292-297
Number of pages6
ISBN (Electronic)9781467394574
DOIs
StatePublished - Apr 26 2016
Event50th Annual Conference on Information Systems and Sciences, CISS 2016 - Princeton, United States
Duration: Mar 16 2016Mar 18 2016

Other

Other50th Annual Conference on Information Systems and Sciences, CISS 2016
CountryUnited States
CityPrinceton
Period3/16/163/18/16

Fingerprint

Entropy
Aberrations
Statistics
Detectors

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Metzger, R. A., Doherty, J. F., & Jenkins, Jr., D. M. (2016). Using Approximate Entropy as a speech quality measure for a speaker recognition system. In 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016 (pp. 292-297). [7460517] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2016.7460517
Metzger, Richard A. ; Doherty, John F. ; Jenkins, Jr., David Marion. / Using Approximate Entropy as a speech quality measure for a speaker recognition system. 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 292-297
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abstract = "In this paper, we will show that Approximate Entropy (ApEn) can be used to detect high-quality speech frames in an otherwise distorted speech signal. By exploiting the property of quasi-periodicity in speech, ApEn is able to detect small aberrations in speech frames that would otherwise cause a decrease in the performance in an automatic speaker recognition (ASR) system. In addition, we obtain the statistics of ApEn values representative of clean speech and propose threshold bounds to obtain maximum recognition rates. When compared to other popular voice activity detector (VAD) algorithms, our simulation results showed that utilization of ApEn will outperform the other VADs in discerning clean speech from noisy speech. This ability to properly detect clean speech allows for a speaker recognition system to obtain a recognition rate close to 87{\%}, which is close to the same performance of the system when noise is not present.",
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Metzger, RA, Doherty, JF & Jenkins, Jr., DM 2016, Using Approximate Entropy as a speech quality measure for a speaker recognition system. in 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016., 7460517, Institute of Electrical and Electronics Engineers Inc., pp. 292-297, 50th Annual Conference on Information Systems and Sciences, CISS 2016, Princeton, United States, 3/16/16. https://doi.org/10.1109/CISS.2016.7460517

Using Approximate Entropy as a speech quality measure for a speaker recognition system. / Metzger, Richard A.; Doherty, John F.; Jenkins, Jr., David Marion.

2016 50th Annual Conference on Information Systems and Sciences, CISS 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 292-297 7460517.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Metzger RA, Doherty JF, Jenkins, Jr. DM. Using Approximate Entropy as a speech quality measure for a speaker recognition system. In 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 292-297. 7460517 https://doi.org/10.1109/CISS.2016.7460517