Title:	Recognition of Heavily Accented and Emotional Speech of English and Czech Holocaust Survivors Using Various DNN Architectures
Authors:	Psutka, Josef Pražák, Aleš Vaněk, Jan
Citation:	PSUTKA, J. PRAŽÁK, A. VANĚK, J. Recognition of Heavily Accented and Emotional Speech of English and Czech Holocaust Survivors Using Various DNN Architectures. In 23rd International Conference, SPECOM 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings. Cham: Springer, 2021. s. 553-564. ISBN: 978-3-030-87801-6 , ISSN: 0302-9743
Issue Date:	2021
Publisher:	Springer
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85116391976 http://hdl.handle.net/11025/47254
ISBN:	978-3-030-87801-6
ISSN:	0302-9743
Keywords in different language:	Speech recognition;Acoustic modeling
Abstract in different language:	The Malach Project [6] verified the possibility of using automatic speech recognition (ASR) methods to search for information in large multilingual archives of Holocaust testimonies. After the end of the MALACH project, in which we participated, we continued to work on the completion and implementation of the project’s objectives with priority for two languages - Czech and English. We have developed and implemented a full-text search system that can be used by experts and by the general public in the MALACH Centre for Visual History and Jewish Museum in Prague. ASR is a key technology that ensures the functioning of the whole information retrieval process. To ensure the highest quality searches, we are constantly striving to develop this technology using the state-of-the-art methods. The article presents the latest results obtained in extensive experiments using various DNN architectures in the ASR of the English and Czech MALACH archives. The paper is therefore one of the first responses to M. Picheny’s call [10] to the speech community to reconsider this very difficult task of recognizing strongly emotional and heavily accented speech of Holocaust survivors.
Rights:	Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Springer
Appears in Collections:	Konferenční příspěvky / Conference Papers (KKY) OBD

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