Automatic speech recognition for under-resourced languages: A survey

Authors:
Laurent Besacier;Etienne Barnard;Alexey Karpov;Tanja Schultz
Affiliations:
Laboratory of Informatics of Grenoble, Grenoble, France;North-West University, Vanderbijlpark, South Africa;St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia;Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Venue:
Speech Communication
Year:
2014

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Abstract

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 8years) 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).