Multi-channel acoustic analysis of phoneme /s/ mispronunciation for lateral sigmatism detection
| Autor: | Zuzanna Miodońska, Natalia Moćko, Pawel Badura, Michal Krecichwost, Joanna Trzaskalik |
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| Rok vydání: | 2019 |
| Předmět: |
Beamforming
Signal processing Computer science Speech recognition Feature vector 0206 medical engineering Feature extraction Biomedical Engineering Speech corpus 02 engineering and technology 020601 biomedical engineering Support vector machine Formant 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Mel-frequency cepstrum |
| Zdroj: | Biocybernetics and Biomedical Engineering. 39:246-255 |
| ISSN: | 0208-5216 |
| DOI: | 10.1016/j.bbe.2018.11.005 |
| Popis: | The paper presents a method for computer-aided detection of lateral sigmatism. The aim of the study is to design an automated sigmatism diagnosis tool. For that purpose, a reference speech corpus has been collected. It contains 438 recordings of a phoneme /s/ surrounded by certain vowels with normative and simulated pathological pronunciation. The acoustic signal is recorded with an acoustic mask, which is a set of microphones organised in a semi-cylindrical surface around the subject's face. Frames containing /s/ phoneme are subjected to beamforming and feature extraction. Two different feature vectors containing, e.g., Mel-frequency cepstral coefficients and fricative formants, are defined and evaluated in terms of binary classification involving support vector machines. A single-channel analysis is confronted with multi-channel processing. The experimental results show that the multi-channel speech signal processing supported by beamforming is able to increase the pathology detection capabilities in general. |
| Databáze: | OpenAIRE |
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