Automatic speech recognition for under-resourced languages: A survey
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Date
2014Author
Besacier, Laurent
Barnard, Etienne
Karpov, Alexey
Schultz, Tanja
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Show full item recordAbstract
Speech processing for under-resourced languages is an active field of research, which has experienced significant progress during the
past decade. We propose, in this paper, a survey that focuses on automatic speech recognition (ASR) for these languages. The definition
of under-resourced languages and the challenges associated to them are first defined. The main part of the paper is a literature review of
the recent (last 8 years) contributions made in ASR for under-resourced languages. Examples of past projects and future trends when
dealing with under-resourced languages are also presented. We believe that this paper will be a good starting point for anyone interested
to initiate research in (or operational development of) ASR for one or several under-resourced languages. It should be clear, however,
that many of the issues and approaches presented here, apply to speech technology in general (text-to-speech synthesis for instance).
2013 Published by Elsevier B.V.
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https://www.sciencedirect.com/science/article/pii/S0167639313000988https://www.researchgate.net/publication/259118437_Automatic_speech_recognition_for_under-resourced_languages_A_survey
http://hdl.handle.net/10394/26495
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- Faculty of Engineering [1122]
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