This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...
We present a system for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a priori. The sources are mo...
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...