We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduc...
For extractive meeting summarization, previous studies have shown performance degradation when using speech recognition transcripts because of the relatively high speech recogniti...
Word Segmentation is the foremost obligatory task in almost all the NLP applications where the initial phase requires tokenization of input into words. Urdu is amongst the Asian l...
We suggest improvements to a previously proposed framework for integrating Conditional Random Fields and Hidden Markov Models, dubbed a Crandem system (2009). The previous authors...
Rohit Prabhavalkar, Preethi Jyothi, William Hartma...
Deploying an automatic speech recognition system with reasonable performance requires expensive and time-consuming in-domain transcription. Previous work demonstrated that non-pro...
We present a novel approach to metaphor interpretation and a system that produces literal paraphrases for metaphorical expressions. Such a representation is directly transferable ...
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
We treat the text summarization problem as maximizing a submodular function under a budget constraint. We show, both theoretically and empirically, a modified greedy algorithm can...
Factorization is the operation of transforming a production in a Linear Context-Free Rewriting System (LCFRS) into two simpler productions by factoring out a subset of the nonterm...