We use automatically extracted acoustic features to detect speech which is generated under stress, achieving 76.24% accuracy with a binary logistic regression. Our data are task-o...
Matthew Frampton, Sandeep Sripada, Ricardo Augusto...
This paper explores methods to alleviate the effect of lexical sparseness in the classification of verbal arguments. We show how automatically generated selectional preferences ar...
We present a scalable joint language model designed to utilize fine-grain syntactic tags. We discuss challenges such a design faces and describe our solutions that scale well to l...
This paper provides a study of the theoretical properties of Most Relevant Explanation (MRE) [12]. The study shows that MRE defines an implicit soft relevance measure that enables ...
: If Topic Maps should be exchanged in distributed environments a common semantic problem occurs: Do two Topics refer to the same Subject? If they describe the same Subject the giv...