Article Dans Une Revue Speech Communication Année : 2014

Automatic speech recognition for under-resourced languages: A survey

Résumé

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).
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Dates et versions

hal-04925128 , version 1 (09-02-2025)

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Laurent Besacier, Etienne Barnard, Alexey Karpov, Tanja Schultz. Automatic speech recognition for under-resourced languages: A survey. Speech Communication, 2014, 56, pp.85-100. ⟨10.1016/j.specom.2013.07.008⟩. ⟨hal-04925128⟩
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