There has been relatively little work focused on determining the formality level of individual lexical items. This study applies information from large mixedgenre corpora, demonst...
Update of acoustic and language models is vital to maintain performance of automatic speech recognition (ASR) systems. To alleviate efforts for updating models, we propose a "...
Yuya Akita, Masato Mimura, Graham Neubig, Tatsuya ...
We present an unsupervised model for joint phrase alignment and extraction using nonparametric Bayesian methods and inversion transduction grammars (ITGs). The key contribution is...
Graham Neubig, Taro Watanabe, Eiichiro Sumita, Shi...
We give a framework for denotational semantics for the polymorphic “core” of the programming language ML. This framework requires no more semantic material than what is needed...
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...