Towards Interpreting Deep Learning Models to Understand Loss of Speech Intelligibility in Speech Disorders — Step 1: CNN Model-Based Phone Classification-Reference-Cited by-同舟云学术

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Towards Interpreting Deep Learning Models to Understand Loss of Speech Intelligibility in Speech Disorders — Step 1: CNN Model-Based Phone Classification

Published:2020-10-25 Issue: Volume: Page:
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Container-title:Interspeech 2020
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Author:

Abderrazek Sondes,Fredouille Corinne,Ghio Alain,Lalain Muriel,Meunier Christine,Woisard Virginie

Publisher

ISCA

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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

2. Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective;Frontiers in Artificial Intelligence;2022-10-28

3. Example-based Explanations with Adversarial Attacks for Respiratory Sound Analysis;Interspeech 2022;2022-09-18

4. Towards Interpreting Deep Learning Models to Understand Loss of Speech Intelligibility in Speech Disorders Step 2: Contribution of the Emergence of Phonetic Traits;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

5. Validation of an intelligibility test based on acoustic-phonetic decoding of pseudo-words: overall results from patients with cancer of the oral cavity and the oropharynx;Folia Phoniatrica et Logopaedica;2021-09-21

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