Articulatory feature asynchrony analysis and compensation in detection-based ASR

This paper investigates the effects of two types of imperfection, namely detection errors and articulatory feature asynchrony, of the front-end articulatory feature detector on the performance of a detection-based ASR system. Based on a set of variable-controlled experiments, we find that articulatory feature asynchrony is the major issue that should be addressed in detection-based ASR. To this end, we propose several methods to reduce the asynchrony or the effects of asynchrony. The results are quite promising; for example, currently, we can achieve 67.67% phone accuracy in the TIMIT free phone recognition task with only 11 binary-valued articulatory features.