Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models (GMMs) to determine how well ...
In recent years, the development of a feature-based general statistical framework has been pursued for automatic speech recognition via novel designs of minimal or atomic units ...
Modeling phonological units of speech is a critical issue in speech recognition. In this paper, our recent development of an overlapping-feature-based phonological model that re...
Generation of high-precision sub-phonetic attribute (also known as phonological features) and phone lattices is a key frontend component for detection-based bottom-up speech rec...
Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models to determine how well each st...
Recently, Deep Belief Networks (DBNs) have been proposed for phone recognition and were found to achieve highly competitive performance. In the original DBNs, only framelevel in...
h-index: Number of publications with at least h citations each.