Title:	Transformer-Based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project
Authors:	Lehečka, Jan Psutka, Josef Psutka, Josef
Citation:	LEHEČKA, J. PSUTKA, J. PSUTKA, J. Transformer-Based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project. In Text, Speech, and Dialogue 25th International Conference, TSD 2022, Brno, Czech Republic, September 6–9, 2022, Proceedings. Cham: Springer International Publishing, 2022. s. 301-312. ISBN: 978-3-031-16269-5 , ISSN: 0302-9743
Issue Date:	2022
Publisher:	Springer International Publishing
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85139084966 http://hdl.handle.net/11025/50924
ISBN:	978-3-031-16269-5
ISSN:	0302-9743
Keywords in different language:	Wav2Vec 2.0;Colloquial speech;ASR
Abstract in different language:	Czech is a very specific language due to its large differences between the formal and the colloquial form of speech. While the formal (written) form is used mainly in official documents, literature, and public speeches, the colloquial (spoken) form is used widely among people in casual speeches. This gap introduces serious problems for ASR systems, especially when training or evaluating ASR models on datasets containing a lot of colloquial speech, such as the MALACH project. In this paper, we are addressing this problem in the light of a new paradigm in end-to-end ASR systems – recently introduced self-supervised audio Transformers. Specifically, we are investigating the influence of colloquial speech on the performance of Wav2Vec 2.0 models and their ability to transcribe colloquial speech directly into formal transcripts. We are presenting results with both formal and colloquial forms in the training transcripts, language models, and evaluation transcripts.
Rights:	Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Springer Nature Switzerland AG
Appears in Collections:	Konferenční příspěvky / Conference papers (NTIS) Konferenční příspěvky / Conference Papers (KKY) OBD

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