METHOD OF TRAINING A ROBUST SPEAKER-DEPENDENT SPEECH RECOGNITION SYSTEM WITH SPEAKER-DEPENDENT EXPRESSIONS AND ROBUST SPEAKER-DEPENDENT SPEECH RECOGNITION SYSTEM

摘要

The present invention provides a method of incorporating speaker-dependent expressions into a speaker-independent speech recognition system providing training data for a plurality of environmental conditions and for a plurality of speakers. The speaker­dependent expression is transformed in a sequence of feature vectors and a mixture density of the set of speaker-independent training data is determined that has a minimum distance to the generated sequence of feature vectors. The determined mixture density is then assigned to a Hidden-Markov-Model (HMM) state of the speaker-dependent expression. Therefore, speaker-dependent training data and references no longer have to be explicitly stored in the speech recognition system. Moreover, by representing a speaker-dependent expression by speaker-independent training data, an environmental adaptation is inherently provided. Additionally, the invention provides generation of artificial feature vectors on the basis of the speaker-dependent expression providing a substantial improvement for the robustness of the speech recognition system with respect to varying environmental conditions.