Prosody is an important cue for identifying dialog acts. In this paper, we show that modeling the sequence of acoustic– prosodic values as n-gram features with a maximum entropy model for dialog act (DA) tagging can perform better than conventional approaches that use coarse representation of the prosodic contour through summative statistics of the prosodic contour. The proposed scheme for expl...

We investigate authorship attribution using classifiers based on frame semantics. The purpose is to discover whether adding semantic information to lexical and syntactic methods for authorship attribution will improve them, specifically to address the difficult problem of authorship attribution of translated texts. Our results suggest (i) that frame-based classifiers are usable for author attri...

This work describes the University of the Basque Country system (UBC-ALM) for lexical sample and all-words WSD subtasks of SemEval-2007 task 17, where it performed in the second and fifth positions respectively. The system is based on a combination of k-Nearest Neighbor classifiers, with each classifier learning from a distinct set of features: local features (syntactic, collocations features),...

We present a machine learning framework for resolving other-anaphora. Besides morpho-syntactic, recency, and semantic features based on existing lexical knowledge resources, our algorithm obtains additional semantic knowledge from the Web. We search the Web via lexico-syntactic patterns that are specific to other-anaphors. Incorporating this innovative feature leads to an 11.4 percentage point ...

The automatic disambiguation of verbs in domain independent text becomes more and more important for applications such as Machine Translation, Text Summarization, and Question Answering, mainly because verbs play a key factor in the syntactic and semantic interpretation of sentences. In this paper we present a system for the automatic classification of token verbs in context based on VerbNet cl...

This paper describes about an automatic technique of evaluating summary. The standard and popular summary evaluation techniques or tools are not fully automatic; they all need some manual process. Using textual entailment (TE) the generated summary can be evaluated automatically without any manual evaluation/process. The TE system is the composition of lexical entailment module, lexical distanc...

This paper describes our system of recognizing textual entailment for RTE-5 challenge at TAC 2009. We propose a textual entailment recognition framework and implement a system of classification which takes lexical, syntactic and semantic features as considered. To improve the performance, some lexical-semantic resources and web knowledge bases are also incorporated in the system. Official resul...

Two experiments are reported examining the relationship between lexical and syntactic processing during language comprehension, combining techniques common to the on-line study of syntactic ambiguity resolution with priming techniques common to the study of lexical processing. By manipulating grammatical properties of lexical primes, we explore how lexically based knowledge is activated and gui...