An efficient approximation of the forward-backward algorithm to deal with packet loss, with applications to remote speech recognition

摘要

This paper proposes an efficient approximation of the forward-backward (FB) algorithm, for the purpose of estimating missing features, based on downsampling statistical models. The paper discusses the role of hidden Markov models (HMMs) in the estimation