@InProceedings{Frohnmaier2024_1209,
<br/>   author = {Mariano Frohnmaier and Steffen Freisinger and Madeline Faye Holt and Munir Georges},
<br/>   booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2024},
<br/>   title = {NoiSLU: A Noisy Speech Corpus for Spoken Language Understanding in the Public Transport Domain},
<br/>   year = {2024},
<br/>   editor = {Timo Baumann},
<br/>   month = mar,
<br/>   pages = {86--93},
<br/>   publisher = {TUDpress, Dresden},
<br/>   abstract  = {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.},
<br/>   isbn = {978-3-95908-325-6},
<br/>   issn = {0940-6832},
<br/>   keywords = {Spracherkennung und -verstehen},
<br/>   url = {https://www.essv.de/pdf/2024_86_93.pdf},
<br/>   doi = {10.35096/othr/pub-7084},
<br/>}