Interpretable Assessment of Speech Intelligibility Using Deep Learning: A Case Study on Speech Disorders Due to Head and Neck Cancers (2024.lrec-main)
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Sondes Abderrazek, Corinne Fredouille, Alain Ghio, Muriel Lalain, Christine Meunier, Mathieu Balaguer, Virginie Woisard
| Challenge: | Using deep learning, speech disorders can be evaluated by perceptual measures, but they are subject to subjectivity and lack of reproducibility. |
| Approach: | They propose to use deep-learning to explain hidden representations in a deep- learning speech model to provide a deeper understanding of the final intelligibility assessment of patients with Head and Neck Cancers. |
| Outcome: | The proposed approach predicts speech intelligibility and severity of patients with Head and Neck Cancers while giving relevant interpretations of the final assessment at the phonemes and phonetic feature levels. |
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