1. A method of speech recognition comprising the steps of: grouping acoustics to form classes based on acoustic features; clustering training speakers by the classes to provide class-specific cluster systems; selecting from the cluster systems, a subset of cluster systems closest to adaptation data from a speaker; transforming the subset of cluster systems to bring the subset of cluster systems closer to the speaker based on the adaptation data to form adapted cluster systems; and combining the adapted cluster systems to create a speaker adapted system for decoding speech from the speaker.
1. A method of speech recognition comprising the steps of: grouping acoustics to form classes based on acoustic features; clustering training speakers by the classes to provide class-specific cluster systems; selecting from the cluster systems, a subset of cluster systems closest to adaptation data from a speaker; transforming the subset of cluster systems to bring the subset of cluster systems closer to the speaker based on the adaptation data to form adapted cluster systems; and combining the adapted cluster systems to create a speaker adapted system for decoding speech from the speaker. 5. The method of speech recognition as recited in claim 1, further comprising the step of building class-specific cluster systems based on speaker dependent systems and partitions of acoustic space, each partition of acoustic space being characterized by a different set of acoustic features.