TY - CHAP A1 - Baumann, Ilja A1 - Wagner, Dominik A1 - Schuster, Maria A1 - Riedhammer, Korbinian A1 - Nöth, Elmar A1 - Bocklet, Tobias T1 - Towards Self-Attention Understanding for Automatic Articulatory Processes Analysis in Cleft Lip and Palate Speech N2 - Cleft lip and palate (CLP) speech presents unique challenges for automatic phoneme analysis due to its distinct acoustic characteristics and articulatory anomalies. We perform phoneme analysis in CLP speech using a pre-trained wav2vec 2.0 model with a multi-head self-attention classification module to capture long-range dependencies within the speech signal, thereby enabling better contextual understanding of phoneme sequences. We demonstrate the effectiveness of our approach in the classification of various articulatory processes in CLP speech. Furthermore, we investigate the interpretability of self-attention to gain insights into the model’s understanding of CLP speech characteristics. Our findings highlight the potential of the selfattention mechanisms for improving automatic phoneme analysis in CLP speech, paving the way for enhanced diagnostics, adding interpretability for therapists and affected patients. KW - pathologic speech, cleft lip and palate, children’s speech, automatic assessment Y1 - 2024 U6 - https://doi.org/10.21437/Interspeech.2024-2134 SP - 2430 EP - 2434 ER -