Visualization of Intelligibility Measured by Language-Independent Features

Haderlein T, Middag C, Maier A, Martens JP, Döllinger M, Nöth E (2014)

Publication Type: Conference contribution

Publication year: 2014

Publisher: Springer

Edited Volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Series: Lecture Notes in Artificial Intelligence

City/Town: Cham, Heidelberg, New York, Dordrecht, London

Book Volume: 8655

Pages Range: 547-554

Conference Proceedings Title: Proc. Text, Speech and Dialogue; 17th International Conference, TSD 2014

Event location: Brno, Czech Republic CZ

ISBN: 978-3-319-10815-5

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2014/Haderlein14-VOI.pdf

DOI: 10.1007/978-3-319-10816-2

Abstract

Automatic intelligibility assessment using automatic speech recognition is usually language-specific. In this study, a language-independent approach based on alignment-free phonological and phonemic features is proposed. It utilizes models that are trained with Flemish speech, and it is applied to assess dysphonic German speakers. In order to visualize the results, two techniques were tested: a plain selection of most relevant features emerging from Ensemble Linear Regression involving feature selection, and a Sammon transform of all the features to a 3-D space. The test data comprised recordings of 73 hoarse persons (48.3 ± 16.8 years) who read the German version of the text "The North Wind and the Sun". The reference evaluation was obtained by five speech therapists and physicians who rated intelligibility according to a 5-point Likert scale. In the 3-D visualization, the different levels of intelligibility were clearly separated. This could be the basis for an objective support for diagnostics in voice and speech rehabilitation. © 2014 Springer International Publishing.

Authors with CRIS profile

Tino Haderlein Professur für Informatik (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Michael Döllinger Professur für Computational Medicine (DFG-Forschungsprofessur) Elmar Nöth Professur für Informatik (Mustererkennung)

Involved external institutions

Universiteit Gent (UGent) / Ghent University BE Belgium (BE)

How to cite

APA:

Haderlein, T., Middag, C., Maier, A., Martens, J.-P., Döllinger, M., & Nöth, E. (2014). Visualization of Intelligibility Measured by Language-Independent Features. In Proc. Text, Speech and Dialogue; 17th International Conference, TSD 2014 (pp. 547-554). Brno, Czech Republic, CZ: Cham, Heidelberg, New York, Dordrecht, London: Springer.

MLA:

Haderlein, Tino, et al. "Visualization of Intelligibility Measured by Language-Independent Features." Proceedings of the Proc. Text, Speech and Dialogue; 17th International Conference (TSD 2014), Brno, Czech Republic Cham, Heidelberg, New York, Dordrecht, London: Springer, 2014. 547-554.

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