Jacobian Approach to Joint Adaptation to Noise, Channel and Vocal Tract Length

This paper describes the Jacobian approach to simulta-neously adapting acoustic models to unknown noise, chan-nel and vocal tract length from a supervised adaptation data. As has been both theoretically and experimentally shown, Jacobian adaptation is one of most efficient methods for model adaptation if the target condition is close to the initial condition. It utilizes the linear relationship in the neighbor of the initial condition which in turn can be used in de-composition of multiple factors. The analytic relationship between noise, channel, vocal tract length and the observed cepstrum is linearized using the Jacobian matrices. Least squares fit gives the estimates of noise, channel and vocal tract stretch parameters. Experimental evaluation gave a significant improvement to the recognition accuracy.