Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features

Akanksha Kalia; Shikar Sharma; Saurabh Kumar Pandey; Vinay Kumar Jadoun; Madhulika Das

doi:10.1007/978-981-15-0214-9_82

Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features

Akanksha Kalia, Shikar Sharma, Saurabh Kumar Pandey, Vinay Kumar Jadoun, Madhulika Das

Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.

Original language	English
Title of host publication	Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018
Editors	Akhtar Kalam, Khaleequr Rehman Niazi, Amit Soni, Shahbaz Ahmed Siddiqui, Ankit Mundra
Publisher	Springer Paris
Pages	781-787
Number of pages	7
ISBN (Print)	9789811502132
DOIs	https://doi.org/10.1007/978-981-15-0214-9_82
Publication status	Published - 01-01-2020
Event	1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018 - Jaipur, India Duration: 22-12-2018 → 23-12-2018

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	607
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018
Country/Territory	India
City	Jaipur
Period	22-12-18 → 23-12-18

All Science Journal Classification (ASJC) codes

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-15-0214-9_82

Cite this

Kalia, A., Sharma, S., Pandey, S. K., Jadoun, V. K., & Das, M. (2020). Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features. In A. Kalam, K. R. Niazi, A. Soni, S. A. Siddiqui, & A. Mundra (Eds.), Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018 (pp. 781-787). (Lecture Notes in Electrical Engineering; Vol. 607). Springer Paris. https://doi.org/10.1007/978-981-15-0214-9_82

Kalia, Akanksha ; Sharma, Shikar ; Pandey, Saurabh Kumar et al. / Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features. Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018. editor / Akhtar Kalam ; Khaleequr Rehman Niazi ; Amit Soni ; Shahbaz Ahmed Siddiqui ; Ankit Mundra. Springer Paris, 2020. pp. 781-787 (Lecture Notes in Electrical Engineering).

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title = "Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features",

abstract = "Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.",

author = "Akanksha Kalia and Shikar Sharma and Pandey, {Saurabh Kumar} and Jadoun, {Vinay Kumar} and Madhulika Das",

year = "2020",

month = jan,

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doi = "10.1007/978-981-15-0214-9_82",

language = "English",

isbn = "9789811502132",

series = "Lecture Notes in Electrical Engineering",

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editor = "Akhtar Kalam and Niazi, {Khaleequr Rehman} and Amit Soni and Siddiqui, {Shahbaz Ahmed} and Ankit Mundra",

booktitle = "Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018",

address = "France",

note = "1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018 ; Conference date: 22-12-2018 Through 23-12-2018",

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Kalia, A, Sharma, S, Pandey, SK, Jadoun, VK & Das, M 2020, Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features. in A Kalam, KR Niazi, A Soni, SA Siddiqui & A Mundra (eds), Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018. Lecture Notes in Electrical Engineering, vol. 607, Springer Paris, pp. 781-787, 1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018, Jaipur, India, 22-12-18. https://doi.org/10.1007/978-981-15-0214-9_82

Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features. / Kalia, Akanksha; Sharma, Shikar; Pandey, Saurabh Kumar et al.
Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018. ed. / Akhtar Kalam; Khaleequr Rehman Niazi; Amit Soni; Shahbaz Ahmed Siddiqui; Ankit Mundra. Springer Paris, 2020. p. 781-787 (Lecture Notes in Electrical Engineering; Vol. 607).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Kalia, Akanksha

AU - Sharma, Shikar

AU - Pandey, Saurabh Kumar

AU - Jadoun, Vinay Kumar

AU - Das, Madhulika

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N2 - Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.

AB - Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.

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Kalia A, Sharma S, Pandey SK, Jadoun VK, Das M. Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features. In Kalam A, Niazi KR, Soni A, Siddiqui SA, Mundra A, editors, Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018. Springer Paris. 2020. p. 781-787. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-15-0214-9_82

Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features

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