TY - CHAP A1 - Frohnmaier, Mariano A1 - Freisinger, Steffen A1 - Holt, Madeline Faye A1 - Georges, Munir ED - Baumann, Timo T1 - NoiSLU: a Noisy speech corpus for Spoken Language Understanding in the Public Transport Domain T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - The use of local public transport requires the barrier-free purchase of a ticket. Travellers who are not proficient in the local language benefit from a multilingual human(ticket)machine voice interaction. This paper presents a nearly parallel audio dataset with 13218 annotated user queries from 20 speakers for English, German and Dutch. The domain-specific speech corpus can be understood as an evaluation dataset for future research in Spoken Language Understanding (SLU) and thus, it enables researches to improve the quality of human-machine interaction applications. Furthermore, we compare the SLU performance of different compositions of Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU) models in baseline experiments on different test datasets. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70848 SN - 978-3-95908-325-6 SP - 86 EP - 93 PB - TUDpress CY - Dresden ER -