Neumeyer, L., Sankar, A., & Digalakis, V. (1995). A comparative study of speaker adaptation techniques. system, 1, 2.
In previous work, we showed how to constrain the estimation of continuous mixture-density hidden Markov models (HMMs) when the amount of adaptation data is small. We used maximum-likelihood (ML) transformation-based approaches and Bayesian techniques to achieve near native performance when testing nonnative speakers of the recognizer language. In this paper, we study various ML-based techniques and compare experimental results on data sets with recordings from nonnative and native speakers of American English. We divide the transformation-based techniques into two groups. In feature-space techniques, we hypothesize an underlying transformation in the feature-space that results in a transformation of the HMM parameters. In model-space techniques, we hypothesize a direct transformation of the HMM parameters. […]