This paper presents the development of the speech, text and pronunciation dictionary resources required to build a large vocabulary speech recognizer for the Malay language. This project is a collaboration project among three universities: USM, MMU from Malaysia and NTUfrom Singapore. The Malay speech corpus consists of read speech (speaker independent/ dependent and accent independent/ dependent) and broadcast news. To date, 90 speakers have been recorded which is equal to a total ofnearly 70 hours of read speech, and 10 hours of broadcast news from local TV stations in Malaysia was transcribed. The text corpus consists of 700Mbytes of data extracted from Malaysia's local news web pages from 1998-2008 and a rule based G2P tool is develop to generate the pronunciation dictionary.
Kamus Dewan is the authoritative dictionary for Bahasa Malaysia, containing a wealth of linguistic and cultural information about Bahasa Malaysia. It is currently available in print, as well as an searchable online dictionary. However, the online dictionary lacks advanced search capabilities that target specific fields within each headword and lemma entry. For these information to be targeted and extracted efficiently by computers, the macro-and micro-structures of Kamus Dewan entries need to be first annotated or marked up explicitly. We describe how TEI-P5 guidelines have been applied in this endeavour to make the Kamus Dewan more machine-tractable. We also give some examples of how the machine-tractable data from Kamus Dewan can be used for linguistic research and analysis, as well as for producing other language resources.
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