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MFCC-based Remote Pathology Detection on Speech Transmitted Through the Telephone Channel - Impact of Linear Distortions: Band Limitation, Frequency Response and Noise., , , , and . BIOSIGNALS, page 41-48. INSTICC Press, (2009)Quels tests d'intelligibilité pour évaluer les troubles de production de la parole ? (What kind of intelligibility test to assess speech production disorders?)., , , , , , , and . JEP-TALN-RECITAL (1), page 589-596. AFCP - ATALA, (2016)Interpretable Assessment of Speech Intelligibility Using Deep Learning: A Case Study on Speech Disorders Due to Head and Neck Cancers., , , , , , and . LREC/COLING, page 9170-9179. ELRA and ICCL, (2024)Exploring Pathological Speech Quality Assessment with ASR-Powered Wav2Vec2 in Data-Scarce Context., , , , and . LREC/COLING, page 6935-6944. ELRA and ICCL, (2024)Towards objective and interpretable speech disorder assessment: a comparative analysis of CNN and transformer-based models., , , , and . CoRR, (2024)Apprentissage profond pour l'analyse de la parole pathologique : étude comparative entre modèles CNN et à base de transformers., , , , and . TALN (JEP), page 261-270. ATALA and AFPC, (2024)How to Compare Automatically Two Phonological Strings: Application to Intelligibility Measurement in the Case of Atypical Speech., , , , and . LREC, page 1689-1694. European Language Resources Association, (2020)Global Speaker Clustering towards Optimal Stopping Criterion in Binary Key Speaker Diarization., , , and . IberSPEECH, volume 8854 of Lecture Notes in Computer Science, page 59-68. Springer, (2014)Interpreting Deep Representations of Phonetic Features via Neuro-Based Concept Detector: Application to Speech Disorders Due to Head and Neck Cancer., , , , , and . IEEE ACM Trans. Audio Speech Lang. Process., (2023)A Tutorial on Text-Independent Speaker Verification, , , , , , , , , and . Journal on Applied Signal Processing, (2004)