In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
The scope of this paper is the interpretation of a user's intention via a video camera and a speech recognizer. In comparison to previous work which only takes into account g...
This paper describes a framework for making up a set of syllables and phonemes that subsequently is used in the creation of acoustic models for continuous speech recognition of Lit...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
We have developed a VLSI chip for 5,000 word speakerindependent continuous speech recognition. This chip employs a context-dependent HMM (hidden Markov model) based speech recogni...