Towards Interpreting Deep Learning Models to Understand Loss of Speech Intelligibility in Speech Disorders Step 2: Contribution of the Emergence of Phonetic Traits-Reference-Cited by-同舟云学术

Towards Interpreting Deep Learning Models to Understand Loss of Speech Intelligibility in Speech Disorders Step 2: Contribution of the Emergence of Phonetic Traits

Published:2022-05-23 Issue: Volume: Page:
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Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Abderrazek Sondes¹,Fredouille Corinne¹,Ghio Alain²,Lalain Muriel²,Meunier Christine²,Woisard Virginie³

Affiliation:

1. LIA, Avignon University,France

2. Aix-Marseille Univ, LPL, CNRS,Aix-en-Provence,France

3. UT2J, Octogone-Lordat, Toulouse University & Toulouse Hospital,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746198.pdf?arnumber=9746198

Reference14 articles.

1. Carcinologic Speech Severity Index Project: A Database of Speech Disorders Productions to Assess Quality of Life Related to Speech After Cancer;astesano,0

2. How to Compare Automatically Two Phonological Strings: Application to Intelligibility Measurement in the Case of Atypical Speech;ghio;LREC 2020 12th Language Resources and Evaluation Conference,2020

3. Achile : un dispositif de décodage acoustico-phonétique et d’identification lexicale indépendant du locuteur à partir de modules mixtes;ghio;Phd thesis (in French),1997

4. Inferring Phonemic Classes from CNN Activation Maps Using Clustering Techniques

5. Viualizing data using t-sne;van der maaten;Journal of Machine Learning Research,2008

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1. Interpreting Deep Representations of Phonetic Features via Neuro-Based Concept Detector: Application to Speech Disorders Due to Head and Neck Cancer;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023