Unified framework for basis-based speaker adaptation using 2-mode analysis

Abstract

A unified 2-mode analysis method is presented for a speaker adaptation method that uses bases. Different structures of training matrices produce different sets of bases in the same framework. Two forms of training matrices are investigated. Bases obtained from the same training matrix as eigenvoice express the same space as that of eigenvoice, hence producing the same recognition result; the new form of training matrix produces the bases that express a different space but also capture the variation of training speakers. In the isolated word recognition experiment, the speaker-adapted model that uses the new bases reduces the error rates of the speaker-independent model and eigenvoice by about 71 and 26% on average, respectively, for adaptation data longer than 3 s.