4th International Conference on Spoken Language Processing
Philadelphia, PA, USA
We describe our recent work on improving an overlapping articulatory feature (sub-phonemic) based speech recognizer with robustness to the requirement of training data. A new decision-tree algorithm is developed and applied to the recognizer design which results in hierarchical partitioning of the articulatory state space. The articulatory states associated with common acoustic correlates, a phenomenon caused by the many-to-one articulation-to-acoustics mapping well known in speech production, are automatically clustered by the decision-tree algorithm. This enables effective prediction of the unseen articulatory states in the training, thereby increasing the recognizer’s robustness. Some preliminary experimental results are provided.
Bibliographic reference. Deng, Li / Wu, Jim Jian-Xiong (1996): "Hierarchical partition of the articulatory state space for overlapping-feature based speech recognition", In ICSLP-1996, 2266-2269.