Juan, Sarah Samson and Besacier, Laurent and Rossato, Solange (2014) Semi-supervised G2P Bootstrapping and Its Application to ASR for a Very Under-resourced Language: Iban. In: Proceedings of Workshop for Spoken Language Technology for Under-resourced (SLTU), St Petersbourg, Russia.
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Abstract
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 strategy to develop an Iban pronunciation lexicon from a Malay one. A hybrid version, mix of Malay and Iban pronunciations, was also built and evaluated. Following this, we experimented with three Iban ASRs; each depended on either one of the three different pronunciation dictionaries: Malay, Iban or hybrid.
Item Type: | Proceeding (Paper) |
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Uncontrolled Keywords: | under-resourced languages, speech recognition, Iban language, Malay language, bootstrapping, Kaldi, Universiti Malaysia Sarawak, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology |
Depositing User: | Samson Juan |
Date Deposited: | 16 Oct 2015 01:20 |
Last Modified: | 16 Oct 2015 01:20 |
URI: | http://ir.unimas.my/id/eprint/8879 |
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