Speech recognition using multi-state acoustic and articulatory features models with asynchronous states transition

In this paper, we propose two improvements to the articulatory feature (AF) models. We introduce the use of 3-state AF model with multiple observation distributions that gives a better modeling of the articulatory features within a phone. This results in an improvement of about 1% in phone recognition on the TIMIT task. Combining the AF model with acoustic-based HMM achieves an improvement of 1.6% compares to use acoustic features only. We then introduce the asynchronous state combination of the 3-state AF models with acoustic-based HMM and obtain an additional improvement of 1.7%.