Development of Indonesian Large Vocabulary Continuous Speech Recognition System within A-STAR Project.
Sakriani Sakti, Eka Kelana, Hammam Riza, Shinsuke Sakai, Konstantin Markov, Satoshi Nakamura · 2008
The paper outlines the development of a large vocabulary continuous speech recognition (LVCSR) system for the Indonesian language within the Asian speech translation (A-STAR) project. An overview of the A-STAR project and Indonesian language characteristics will be briefly described. We then focus on a discussion of the development of Indonesian LVCSR, including data resources issues, acoustic modeling, language modeling, the lexicon, and accuracy of recognition. There are three types of Indonesian data resources: daily news, telephone application, and BTEC tasks, which are used in this project. They are available in both text and speech forms. The Indonesian speech recognition engine was trained using the clean speech of both daily news and telephone application tasks. The optimum performance achieved on the BTEC task was 92.47 % word accuracy.