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Semi-supervised G2p bootstrapping and its application to ASR for a very under-resourced language: Iban
2014
Workshop on Spoken Language Technologies for Under-resourced Languages
This paper describes our experiments and results on using a local dominant language in Malaysia (Malay), to bootstrap automatic speech recognition (ASR) for a very under-resourced language: Iban (also spoken in Malaysia on the Borneo Island part). Resources in Iban for building a speech recognition were nonexistent. For this, we tried to take advantage of a language from the same family with several similarities. First, to deal with the pronunciation dictionary, we proposed a bootstrapping
dblp:conf/sltu/JuanBR14
fatcat:mus4jszk25ekrhak5o3nz4wbsm