Rapid speaker adaptation by reference model interpolation

We present in this work a novel algorithm for fast speaker adaptation using only small amounts of adaptation data. It is motivated by the fact that a set of representative speakers can provide a priori knowledge to guide the estimation of a new speaker in the speaker-space. The proposed algorithm enables an a posteriori selection of reference models in the speakerspace as opposed to the a priori selection of reference speaker-space commonly used in techniques such as Eigenvoices. We compare the proposed algorithm with the common rapid adaptation techniques within the context of phoneme recognition task. Experimental results on the IDIOLOGOS and PAIDIALOGOS corpus [1] show that the proposed algorithm achieves slightly better improvement than classic Eigenvoices in phoneme accuracy rate, especially for atypical speakers such as children.