LUX-ASR: Building an ASR system for the Luxembourgish language

Reference : LUX-ASR: Building an ASR system for the Luxembourgish language


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/55105

Title :	LUX-ASR: Building an ASR system for the Luxembourgish language
Language :	English
Author, co-author :	Gilles, Peter [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Humanities (DHUM) >]
	Hosseini Kivanani, Nina [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
	Hillah, Léopold Edem Ayité [University of Luxembourg > Faculty of Science, Technology and Medecine (FSTM) > >]
Publication date :	2023
Main document title :	Proceedings - 2022 IEEE Spoken Language Technology Workshop (SLT)
Editor :	IEEE, Spoken Language Technology
Pages :	1147-1149
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISBN :	978-1-6654-7189-3
Event name :	2022 IEEE Spoken Language Technology Workshop (SLT) SLT 2022
Event date :	from 09-01-2023 to 12-01-2023
Event organizer :	SLT
Event place (city) :	Doha
Event country :	Qatar
Keywords :	[en] Automatic Speech Recognition ; Luxembourgish
Abstract :	[en] We present a first system for automatic speech recognition (ASR) for the low-resource language Luxembourgish. By applying transfer-learning, we were able to fine-tune Meta’s wav2vec2-xls-r-300m checkpoint with 35 hours of labeled Luxembourgish speech data. The best word error rate received lies at 14.47.
Permalink :	http://hdl.handle.net/10993/55105

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Open access	0001147.pdf		Author preprint	164.31 kB	View/Open

All documents in ORBi^lu are protected by a user license.