Gales, M.J.F., Knill, K.M., Ragni, A. orcid.org/0000-0003-0634-4456 et al. (1 more author) (2014) Speech recognition and keyword spotting for low-resource languages : Babel project research at CUED. In: Fourth International Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU-2014). Fourth International Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU-2014), 14-16 May 2014, St. Petersburg, Russia. International Speech Communication Association (ISCA) , pp. 16-23.
Abstract
Recently there has been increased interest in Automatic Speech Recognition (ASR) and Key Word Spotting (KWS) systems for low resource languages. One of the driving forces for this research direction is the IARPA Babel project. This paper describes some of the research funded by this project at Cambridge University, as part of the Lorelei team co-ordinated by IBM. A range of topics are discussed including: deep neural network based acoustic models; data augmentation; and zero acoustic model resource systems. Performance for all approaches is evaluated using the Limited (approximately 10 hours) and/or Full (approximately 80 hours) language packs distributed by IARPA. Both KWS and ASR performance figures are given. Though absolute performance varies from language to language, and keyword list, the approaches described show consistent trends over the languages investigated to date. Using comparable systems over the five Option Period 1 languages indicates a strong correlation between ASR performance and KWS performance.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | keyword spotting; deep neural network; low-resource languages; multi-lingual systems |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Nov 2019 12:26 |
Last Modified: | 25 Nov 2019 12:26 |
Published Version: | https://www.isca-speech.org/archive/sltu_2014/sl14... |
Status: | Published |
Publisher: | International Speech Communication Association (ISCA) |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152840 |