Instantaneous environment adaptation techniques based on fast PMC and MAP-CMS methods

This paper proposes instantaneous environment adaptation techniques for both additive noise and channel distortion based on the fast PMC (FPMC) and the MAP-CMS methods. The instantaneous adaptation techniques enable a recognizer to improve recognition on a single sentence that is used for the adaptation in real-time. The key innovations enabling the system to achieve the instantaneous adaptation are: (1) a cepstral mean subtraction method based on maximum a posteriori estimation (MAP-CMS), (2) real-time implementation of the fast parallel model combination (PMC) that we proposed previously, (3) utilization of multi-pass search, and (4) a new combination method of MAP-CMS and FPMC to solve the problem of both channel distortion and additive noise. Experiment results showed that the proposed methods enabled the system to perform recognition and adaptation simultaneously nearly in real-time and obtained good improvements in performance