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Dimension Compactness in Speaker Identification

Author:

Soumen KanrarAuthors Info & Claims

ICIA-16: Proceedings of the International Conference on Informatics and Analytics

Article No.: 18, Pages 1 - 6

https://doi.org/10.1145/2980258.2980296

Published: 25 August 2016 Publication History

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Abstract

The automatic speaker identification procedure is used to extract features that help to identify the components of the acoustic signal by discarding all the other stuff like background noise, emotion, hesitation, etc. The acoustic signal is generated by a human that is filtered by the shape of the vocal tract, including tongue, teeth, etc. The shape of the vocal tract determines and produced, what signal comes out in real time. The analytically develops shape of the vocal tract, which exhibits envelop for the short time power spectrum. The ASR needs efficient way of extracting features from the acoustic signal that is used effectively to makes the shape of the individual vocal tract. To identify any acoustic signal in the large collection of acoustic signal i.e. corpora, it needs dimension compactness of total variability space by using the GMM mean supervector. This work presents the efficient way to implement dimension compactness in total variability space and using cosine distance scoring to predict a fast output score for small size utterance.

References

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Digital Library

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Cited By

Verma GKanrar S(2023)Secure digital documents sharing using blockchain and attribute-based cryptosystemMultiagent and Grid Systems10.3233/MGS-22136118:3-4(365-379)Online publication date: 3-Feb-2023
https://doi.org/10.3233/MGS-221361
Verma GKanrar S(2022)A novel model to enhance the data security in cloud environmentMultiagent and Grid Systems10.3233/MGS-22036118:1(45-63)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/MGS-220361
Kanrar S(2022)Robust Threshold Selection for Environment Specific Voice in Speaker RecognitionWireless Personal Communications: An International Journal10.1007/s11277-022-09852-2126:4(3071-3092)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11277-022-09852-2
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ICIA-16: Proceedings of the International Conference on Informatics and Analytics

August 2016

868 pages

ISBN:9781450347563

DOI:10.1145/2980258

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 August 2016

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ICIA-16: International Conference on Informatics and Analytics

August 25 - 26, 2016

Pondicherry, India

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Cited By

Verma GKanrar S(2023)Secure digital documents sharing using blockchain and attribute-based cryptosystemMultiagent and Grid Systems10.3233/MGS-22136118:3-4(365-379)Online publication date: 3-Feb-2023
https://doi.org/10.3233/MGS-221361
Verma GKanrar S(2022)A novel model to enhance the data security in cloud environmentMultiagent and Grid Systems10.3233/MGS-22036118:1(45-63)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/MGS-220361
Kanrar S(2022)Robust Threshold Selection for Environment Specific Voice in Speaker RecognitionWireless Personal Communications: An International Journal10.1007/s11277-022-09852-2126:4(3071-3092)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11277-022-09852-2
Kanrar SAgrawal SSharma A(2021)Vehicle Detection and Count in the Captured Stream Video Using Machine LearningMachine Learning Approaches for Urban Computing10.1007/978-981-16-0935-0_5(79-112)Online publication date: 29-Apr-2021
https://doi.org/10.1007/978-981-16-0935-0_5
Kanrar SDawar KPundir A(2020)Pedestrian localisation in the typical indoor environmentsMultimedia Tools and Applications10.1007/s11042-020-09291-w79:37-38(27833-27866)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s11042-020-09291-w
Kanrar S(2016)Fast load balancing approach for growing clusters by Bioinformatics2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)10.1109/SCOPES.2016.7955857(382-385)Online publication date: Oct-2016
https://doi.org/10.1109/SCOPES.2016.7955857

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