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Transcribing Southern Min speech corpora with a Web-Based language learning system

Authors :
Jun Cai
Jacques Feldmar
Jean-Paul Haton
Dominique Fohr
Yves Laprie
Analysis, perception and recognition of speech (PAROLE)
INRIA Lorraine
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
Source :
International Conference on Audio, Language and Image Processing-ICALIP 2008, International Conference on Audio, Language and Image Processing-ICALIP 2008, Jul 2008, Shangai, China
Publication Year :
2008
Publisher :
IEEE, 2008.

Abstract

The paper proposes a human-computation-based scheme for transcribing Southern Min speech corpora. The core idea is to implement a Web-based language learning system to collect orthographic and phonetic labels from a large amount of language learners and choose the commonly input labels as the transcriptions of the corpora. It is essentially a technology of distributed knowledge acquisition. Some computer-aided mechanisms are also used to verify the collected transcriptions. The benefit of the scheme is that it makes the transcribing task neither tedious nor costly. No significant budget should be made for transcribing large corpora. The design of a system for transcribing Min Nan speech corpora is described in detail. The application of a prototype version of the system shows that this transcribing scheme is an effective and economical way to generate orthographic and phonetic transcriptions.

Details

Database :
OpenAIRE
Journal :
2008 International Conference on Audio, Language and Image Processing
Accession number :
edsair.doi.dedup.....60e75ab092c573defcdb5a940b6f89e7
Full Text :
https://doi.org/10.1109/icalip.2008.4590181