Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech

Sudarsana Reddy Kadiri; Paavo Alku

doi:10.21437/Interspeech.2019-2863

Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech

Sudarsana Reddy Kadiri, Paavo Alku

Speech Communication Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

12 Citations (Scopus)

400 Downloads (Pure)

Abstract

Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms for classification of phonation types in speech. The cepstral coefficients are computed using two source waveforms: (1) glottal flow waveforms estimated by the quasi-closed phase (QCP) glottal inverse filtering method and (2) approximate voice source waveforms obtained using the zero frequency filtering (ZFF) method. QCP estimates voice source waveforms based on the source-filter decomposition while ZFF yields source waveforms without explicitly computing the source-filter decomposition. Experiments using MFCCs computed from the two source waveforms show improved accuracy in classification of phonation types compared to the existing voice source features and conventional MFCC features. Further, it is observed that the proposed features have complimentary information to the existing features.

Original language	English
Title of host publication	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publisher	International Speech Communication Association (ISCA)
Pages	2508-2512
Number of pages	5
Volume	2019-September
DOIs	https://doi.org/10.21437/Interspeech.2019-2863
Publication status	Published - 1 Jan 2019
MoE publication type	A4 Conference publication
Event	Interspeech - Graz, Austria Duration: 15 Sept 2019 → 19 Sept 2019 https://www.interspeech2019.org/

Publication series

Name	Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH
ISSN (Electronic)	2308-457X

Conference

Conference	Interspeech
Country/Territory	Austria
City	Graz
Period	15/09/2019 → 19/09/2019
Internet address	https://www.interspeech2019.org/

Keywords

Glottal inverse filtering
Phonation type
Speech analysis
Voice quality
Voice source
Zero frequency filtering

Access to Document

10.21437/Interspeech.2019-2863

ELEC_Kadiri_Mel-frequency_cepstral_INTERSPEECHFinal published version, 700 KB

Cite this

Kadiri, S. R., & Alku, P. (2019). Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH (Vol. 2019-September, pp. 2508-2512). (Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH). International Speech Communication Association (ISCA). https://doi.org/10.21437/Interspeech.2019-2863

Kadiri, Sudarsana Reddy ; Alku, Paavo. / Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Vol. 2019-September International Speech Communication Association (ISCA), 2019. pp. 2508-2512 (Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH).

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title = "Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech",

abstract = "Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms for classification of phonation types in speech. The cepstral coefficients are computed using two source waveforms: (1) glottal flow waveforms estimated by the quasi-closed phase (QCP) glottal inverse filtering method and (2) approximate voice source waveforms obtained using the zero frequency filtering (ZFF) method. QCP estimates voice source waveforms based on the source-filter decomposition while ZFF yields source waveforms without explicitly computing the source-filter decomposition. Experiments using MFCCs computed from the two source waveforms show improved accuracy in classification of phonation types compared to the existing voice source features and conventional MFCC features. Further, it is observed that the proposed features have complimentary information to the existing features.",

keywords = "Glottal inverse filtering, Phonation type, Speech analysis, Voice quality, Voice source, Zero frequency filtering",

author = "Kadiri, {Sudarsana Reddy} and Paavo Alku",

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doi = "10.21437/Interspeech.2019-2863",

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Kadiri, SR & Alku, P 2019, Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech. in Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. vol. 2019-September, Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH, International Speech Communication Association (ISCA), pp. 2508-2512, Interspeech, Graz, Austria, 15/09/2019. https://doi.org/10.21437/Interspeech.2019-2863

Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech. / Kadiri, Sudarsana Reddy; Alku, Paavo.
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Vol. 2019-September International Speech Communication Association (ISCA), 2019. p. 2508-2512 (Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Alku, Paavo

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N2 - Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms for classification of phonation types in speech. The cepstral coefficients are computed using two source waveforms: (1) glottal flow waveforms estimated by the quasi-closed phase (QCP) glottal inverse filtering method and (2) approximate voice source waveforms obtained using the zero frequency filtering (ZFF) method. QCP estimates voice source waveforms based on the source-filter decomposition while ZFF yields source waveforms without explicitly computing the source-filter decomposition. Experiments using MFCCs computed from the two source waveforms show improved accuracy in classification of phonation types compared to the existing voice source features and conventional MFCC features. Further, it is observed that the proposed features have complimentary information to the existing features.

AB - Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms for classification of phonation types in speech. The cepstral coefficients are computed using two source waveforms: (1) glottal flow waveforms estimated by the quasi-closed phase (QCP) glottal inverse filtering method and (2) approximate voice source waveforms obtained using the zero frequency filtering (ZFF) method. QCP estimates voice source waveforms based on the source-filter decomposition while ZFF yields source waveforms without explicitly computing the source-filter decomposition. Experiments using MFCCs computed from the two source waveforms show improved accuracy in classification of phonation types compared to the existing voice source features and conventional MFCC features. Further, it is observed that the proposed features have complimentary information to the existing features.

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ER -

Kadiri SR, Alku P. Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Vol. 2019-September. International Speech Communication Association (ISCA). 2019. p. 2508-2512. (Interspeech - Annual Conference of the International Speech Communication Association, INTERSPEECH). doi: 10.21437/Interspeech.2019-2863

Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Interdisciplinary research on statistical parametric speech synthesis

Cite this

Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Interdisciplinary research on statistical parametric speech synthesis

Cite this