Novel VTEO based Mel cepstral features for classification of normal and pathological voices

Hemant A. Patil; Pallavi N. Baljekar

Novel VTEO based Mel cepstral features for classification of normal and pathological voices

Hemant A. Patil, Pallavi N. Baljekar

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, novel Variable length Teager Energy Operator (VTEO) based Mel cepstral features, viz., VTMFCC are proposed for automatic classification of normal and pathological voices. Experiments have been carried out using this proposed feature set, MFCC and their score-level fusion. Classification was performed using a 2 ^nd order polynomial classifier on a subset of the MEEI database. The equal error rate (EER) on fusion was 3.2% less than EER of MFCC alone which was used as the baseline. Effectiveness of the proposed feature-set was also investigated under degraded conditions using the NOISEX-92 database for babble and high frequency channel noise.

Original language	English
Pages (from-to)	509-512
Number of pages	4
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication status	Published - 01-12-2011
Externally published	Yes
Event	12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: 27-08-2011 → 31-08-2011

All Science Journal Classification (ASJC) codes

Language and Linguistics
Human-Computer Interaction
Signal Processing
Software
Modelling and Simulation

Cite this

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title = "Novel VTEO based Mel cepstral features for classification of normal and pathological voices",

abstract = "In this paper, novel Variable length Teager Energy Operator (VTEO) based Mel cepstral features, viz., VTMFCC are proposed for automatic classification of normal and pathological voices. Experiments have been carried out using this proposed feature set, MFCC and their score-level fusion. Classification was performed using a 2 nd order polynomial classifier on a subset of the MEEI database. The equal error rate (EER) on fusion was 3.2% less than EER of MFCC alone which was used as the baseline. Effectiveness of the proposed feature-set was also investigated under degraded conditions using the NOISEX-92 database for babble and high frequency channel noise.",

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year = "2011",

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language = "English",

pages = "509--512",

journal = "Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",

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T1 - Novel VTEO based Mel cepstral features for classification of normal and pathological voices

AU - Patil, Hemant A.

AU - Baljekar, Pallavi N.

PY - 2011/12/1

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N2 - In this paper, novel Variable length Teager Energy Operator (VTEO) based Mel cepstral features, viz., VTMFCC are proposed for automatic classification of normal and pathological voices. Experiments have been carried out using this proposed feature set, MFCC and their score-level fusion. Classification was performed using a 2 nd order polynomial classifier on a subset of the MEEI database. The equal error rate (EER) on fusion was 3.2% less than EER of MFCC alone which was used as the baseline. Effectiveness of the proposed feature-set was also investigated under degraded conditions using the NOISEX-92 database for babble and high frequency channel noise.

AB - In this paper, novel Variable length Teager Energy Operator (VTEO) based Mel cepstral features, viz., VTMFCC are proposed for automatic classification of normal and pathological voices. Experiments have been carried out using this proposed feature set, MFCC and their score-level fusion. Classification was performed using a 2 nd order polynomial classifier on a subset of the MEEI database. The equal error rate (EER) on fusion was 3.2% less than EER of MFCC alone which was used as the baseline. Effectiveness of the proposed feature-set was also investigated under degraded conditions using the NOISEX-92 database for babble and high frequency channel noise.

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AN - SCOPUS:84865772534

SN - 1990-9772

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EP - 512

JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

T2 - 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011

Y2 - 27 August 2011 through 31 August 2011

ER -

Novel VTEO based Mel cepstral features for classification of normal and pathological voices

Abstract

All Science Journal Classification (ASJC) codes

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