Adopting Malay Syllable Structure for Syllable Based Speech Synthesizer for Iban and Bidayuh Languages

Abstract

Sarawak, Malaysia, has many under-resourced languages, which stands to become extinct if measures are not taken to preserve and maintain them. These languages are mostly spoken by the indigenous groups and not all of the languages are documented or studied. As an initiative to preserve, a Text to Speech (TTS) system has been built for Iban and Bidayuh languages, two out of 44 living languages in Sarawak. To expedite the development, we employed knowledge of closely-related language, i.e. Malay, which is the first language in Malaysia. In this paper, we employed a syllabification algorithm based on Malay syllable structure to build the Iban and Bidayuh syllable list and speech corpus. An accuracy test for the algorithm was conducted to determine the quality of the output from the TTS system using Categorical Estimation (CE). Test showed high percentage in accuracy and quality has a mean score of 3.07 out of 5, suggesting the approach works.