On combining acoustic and modulation spectrograms in an attention LSTM-based system for speech intelligibility level classification-Reference-Cited by-同舟云学术

On combining acoustic and modulation spectrograms in an attention LSTM-based system for speech intelligibility level classification

Published:2021-10 Issue: Volume:456 Page:49-60
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Gallardo-Antolín Ascensión,Montero Juan M.

Funder

Gobierno de España Ministerio de Ciencia e Innovación

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference41 articles.

1. Dysarthric speech: A comparison of computerized speech recognition and listener intelligibility;Doyle;Journal of Rehabilitation Research and Development,1997

2. Spectral subspace analysis for automatic assessment of pathological speech intelligibility;Janbakhshi;Proc. Interspeech,2019

3. Automatic intelligibility assessment of speakers after laryngeal cancer by means of acoustic modeling;Bocklet;Journal of Voice,2012

4. Intelligibility assessment and speech recognizer word accuracy rate prediction for dysarthric speakers in a factor analysis subspace;Martínez;ACM Transactions on Accessible Computing,2015

5. Random Forest-Based Prediction of Parkinson’s Disease Progression Using Acoustic, ASR and Intelligibility Features;Zlotnik;Proc. Interspeech,2015

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