<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The paper focuses on two methods of evaluation of successfulness of speech signal enhancement recorded in the open-air magnetic resonance imager during phonation for the 3D human vocal tract modeling. The first approach enables to obtain a comparison based on statistical analysis by ANOVA and hypothesis tests. The second method is based on classification by Gaussian mixture models (GMM). The performed experiments have confirmed that the proposed ANOVA and GMM classifiers for automatic evaluation of the speech quality are functional and produce fully comparable results with the standard evaluation based on the listening test method.</p></abstract>

The paper focuses on two methods of evaluation of successfulness of speech signal enhancement recorded in the open-air magnetic resonance imager during phonation for the 3D human vocal tract modeling. The first approach enables to obtain a comparison based on statistical analysis by ANOVA and hypothesis tests. The second method is based on classification by Gaussian mixture models (GMM). The performed experiments have confirmed that the proposed ANOVA and GMM classifiers for automatic evaluation of the speech quality are functional and produce fully comparable results with the standard evaluation based on the listening test method.

Two Methods of Automatic Evaluation of Speech Signal Enhancement Recorded in the Open-Air MRI Environment

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The paper focuses on two methods of evaluation of successfulness of speech signal enhancement recorded in the open-air magnetic resonance imager during...

Two Methods of Automatic Evaluation of Speech Signal Enhancement Recorded in the Open-Air MRI Environment

Online veröffentlicht: 22. Nov. 2017

Seitenbereich: 257 - 263

Eingereicht: 27. Juli 2017

Akzeptiert: 12. Nov. 2017

DOI: https://doi.org/10.1515/msr-2017-0031

Schlüsselwörter
Acoustic noise suppression, magnetic resonance imaging, speech processing, statistical analysis

© by Jiří Přibil

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Two Methods of Automatic Evaluation of Speech Signal Enhancement Recorded in the Open-Air MRI Environment

Online veröffentlicht: 22. Nov. 2017

Seitenbereich: 257 - 263

Eingereicht: 27. Juli 2017

Akzeptiert: 12. Nov. 2017

DOI: https://doi.org/10.1515/msr-2017-0031

SchlüsselwörterAcoustic noise suppression, magnetic resonance imaging, speech processing, statistical analysis

© by Jiří Přibil

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Acoustic noise suppression, magnetic resonance imaging, speech processing, statistical analysis