Towards Interpretability of Automatic Phoneme Analysis in Cleft Lip and Palate Speech

  • Cleft Lip and Palate ranks among the most common congenital abnormalities and significantly influences speech articulation, resulting in varying phonemic impacts. In a clinical context, a detailed diagnosis is carried out by time-consuming perceptual evaluations. We use perceptual ratings of different articulatory modifications on phoneme-level as ground-truth and propose a system based on wav2vec 2.0, trained to the downstream task of classifying phonemic criteria as a multi-class and multi-label problem. The system is trained for detection on utterance level, without the usage of phoneme labels. To gain a clearer understanding of which areas of the speech signal have the greatest impact on classification, we assess the extent to which our system aligns with expert ratings at the phoneme level. Additionally, we examine which specific phonemes play a decisive role in determining the final classification of the labeled criteria. The results show that salient phonemes marked by experts contribute remarkably greater to the classificationCleft Lip and Palate ranks among the most common congenital abnormalities and significantly influences speech articulation, resulting in varying phonemic impacts. In a clinical context, a detailed diagnosis is carried out by time-consuming perceptual evaluations. We use perceptual ratings of different articulatory modifications on phoneme-level as ground-truth and propose a system based on wav2vec 2.0, trained to the downstream task of classifying phonemic criteria as a multi-class and multi-label problem. The system is trained for detection on utterance level, without the usage of phoneme labels. To gain a clearer understanding of which areas of the speech signal have the greatest impact on classification, we assess the extent to which our system aligns with expert ratings at the phoneme level. Additionally, we examine which specific phonemes play a decisive role in determining the final classification of the labeled criteria. The results show that salient phonemes marked by experts contribute remarkably greater to the classification of the correct class using feature relevance explanation methods. To the best of our knowledge, this is the first study incorporating various utterance-level articulatory modifications classification and phoneme-level interpretation, offering a more comprehensive understanding for potential clinical applications.show moreshow less

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Ilja Baumann, Dominik Wagner, Maria Schuster, Elmar Nöth, Tobias Bocklet
DOI:https://doi.org/10.1109/ICASSP48485.2024.10447632
Parent Title (English):IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Document Type:conference proceeding (article)
Language:English
Reviewed:Begutachtet/Reviewed
Release Date:2024/07/03
Tag:pathologic speech, cleft lip and palate, children’s speech, automatic assessment
Pagenumber:5
First Page:12602
Last Page:12606
institutes:Fakultät Informatik
Licence (German):Keine Lizenz - Deutsches Urheberrecht gilt
Verstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.