TY - CONF A1 - Rykova, Eugenia A1 - Walther, Mathias A2 - Luz de Araujo, Pedro Henrique A2 - Baumann, Andreas A2 - Gromann, Dagmar A2 - Krenn, Brigitte A2 - Roth, Benjamin A2 - Wiegand, Michael T1 - Linguistic and extralinguistic factors in automatic speech recognition of German atypical speech TI - Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024) N2 - Automatic speech recognition (ASR) has been already used in speech and language therapy, including diagnostic tasks and practice exercises for people with aphasia (PWA). The lack of relevant data makes it difficult to evaluate the algorithms’ suitability for German-speaking PWA. For the current project, four open-source ASR models were selected based on their performance on other types of atypical speech, and the details of their evaluation are presented in this paper. The four selected models are generally robust to speakers’ gender and age. The one-word recognition yields better results for words of moderate length. Speech rate should be neither too slow nor too quick for lower error rates both in words and phrases, and the latter should be also of moderate length. Y1 - 2024 UR - https://opus4.kobv.de/opus4-th-wildau/frontdoor/index/index/docId/1991 UR - https://nbn-resolving.org/urn:nbn:de:kobv:526-opus4-19915 UR - https://aclanthology.org/2024.konvens-main.36/ SP - 358 EP - 367 PB - Association for Computational Linguistics CY - Wien ER -