In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
Several researchers have proposed semi-supervised learning methods for adapting event extraction systems to new event types. This paper investigates two kinds of bootstrapping met...
Continuous speech input for ASR processing is usually presegmented into speech stretches by pauses. In this paper, we propose that smaller, prosodically defined units can be ident...
Yi-Fen Liu, Shu-Chuan Tseng, Jyh-Shing Roger Jang,...
While peer-to-peer (P2P) video streaming systems have achieved promising results, they introduce a large number of unnecessary traverse links, which consequently leads to substanti...
Yan Chen, Beibei Wang, W. Sabrina Lin, Yongle Wu, ...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...