Two Methods of Automatic Evaluation of Speech Signal Enhancement Recorded in the Open-Air MRI Environment-Reference-Cited by-同舟云学术

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

Published:2017-11-22 Issue:6 Volume:17 Page:257-263
ISSN:1335-8871
Container-title:Measurement Science Review
language:en
Short-container-title:

Author:

Přibil Jiří¹,Přibilová Anna²,Frollo Ivan¹

Affiliation:

1. Institute of Measurement Science, SAS, Dúbravská cesta 9, SK-841 04 Bratislava , Slovakia

2. Institute of Electronics and Photonics, FEE&IT, SUT, Ilkovičova 3, SK-812 19 Bratislava , Slovakia

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Instrumentation,Biomedical Engineering,Control and Systems Engineering

Reference35 articles.

1. [1] Wei, J., Liu, J., Fang, Q., Lu, W., Dang, J., Honda, K. (2016). A novel method for constructing 3D geometric articulatory models. Journal of Signal Processing Systems, 82, 295-302.

2. [2] Aalto, D., Aaltonen, O., Happonen, R.-P. et al. (2014). Large scale data acquisition of simultaneous MRI and speech. Applied Acoustics, 83, 64-75. 10.1016/j.apacoust.2014.03.003

3. [3] Kuorti, J., Malinen, J., Ojalammi, A. (2018). Postprocessing speech recordings during MRI. Biomedical Signal Processing and Control, 39, 11-22. 10.1016/j.bspc.2017.07.017

4. [4] Tomasi, D., Ernst, T. (2006). A simple theory for vibration of MRI gradient coils. Brazilian Journal of Physics, 36, 34-39. 10.1590/S0103-97332006000100009

5. [5] Burdumy, M., Traser, L., Richter, B. et al. (2015). Acceleration of MRI of the vocal tract provides additional insight into articulator modifications. Journal of Magnetic Resonance Imaging, 42, 925-935.

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