Papers by Christine Meunier

2 papers
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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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.
Dysarthric speech evaluation: automatic and perceptual approaches (L18-1)

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Challenge: Perceptual evaluation is still the most common method in clinical practice for the diagnosis and monitoring of the condition progression of people suffering from dysarthria.
Approach: They propose an automatic approach for anomaly detection at the phone level for dysarthric speech . they propose a perceptual evaluation protocol that uses annotated french corpora to analyze the system behavior.
Outcome: The proposed method was validated on different corpora and speech styles.

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