5th International Conference on Spoken Language Processing
In this paper, we apply context dependent phonetic modeling on the task of large vocabulary (with 20 thousand words) Taiwanese multi-syllabic word recognition. Considering the phonetic characteristics of Taiwanese, the right context dependent (RCD) phones instead of the general tri-phones are used. The RCDs are further clustered at the sub-phone or state level using a decision tree with a set of context-split questions specially designed for Taiwanese speech according to the acoustic/phonetic knowledge. For the speaker dependent case, 7.18% word error rate is achieved. A real-time prototype system implemented on a Pentium-II personal computer running MS-Windows95/ NT is also shown to validate the approaches proposed here.
Bibliographic reference. Lyu, Ren-yuan / Chiang, Yuang-jin / Hsieh, Wen-ping (1998): "A large-vocabulary taiwanese (MIN-NAN) multi-syllabic word recognition system based upon right-context-dependent phones with state clustering by acoustic decision tree", In ICSLP-1998, paper 0080.