Robust and Complex Approach of Pathological Speech Signal Analysis

Autor: Mekyska, Jiri, Janousova, Eva, Gomez-Vilda, Pedro, Smekal, Zdenek, Rektorova, Irena, Eliasova, Ilona, Kostalova, Milena, Mrackova, Martina, Alonso-Hernandez, Jesus B., Faundez-Zanuy, Marcos, López-de-Ipiña, Karmele
Rok vydání: 2022
Předmět:
Zdroj: Neurocomputing, Volume 167, 2015, Pages 94-111, ISSN 0925-2312
Druh dokumentu: Working Paper
DOI: 10.1016/j.neucom.2015.02.085
Popis: This paper presents a study of the approaches in the state-of-the-art in the field of pathological speech signal analysis with a special focus on parametrization techniques. It provides a description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from different areas of speech signal processing like speech recognition or coding). As an original contribution, this work introduces 36 completely new pathological voice measures based on modulation spectra, inferior colliculus coefficients, bicepstrum, sample and approximate entropy and empirical mode decomposition. The significance of these features was tested on 3 (English, Spanish and Czech) pathological voice databases with respect to classification accuracy, sensitivity and specificity.
Comment: 41 pages, published in Neurocomputing, Volume 167, 2015, Pages 94-111, ISSN 0925-2312
Databáze: arXiv