Learning Algorithm

The dialogue strategies used by a spoken dialogue system strongly influence performance and user sat- isfaction. An ideal system would not use a single fixed strategy, but would adapt to …...

This paper presents an unsupervised approach to lexical acquisition with the goodness measure de- scription length gain (DLG) formulated following classic information theory within the minimum de- scription length (MDL) …...

Regular languages are widely used in NLP to- day in spite of their shortcomings. Efficient algorithms that can reliably learn these lan- guages, and which must in realistic applications only …...

Negation is present in all human languages and it is used to reverse the polarity of part of statements that are otherwise affirmative by default. A negated statement often carries …...

AbstractAutomatic annotation of gesture strokes is important for many gesture and sign language researchers. The unpredictable diversity of human gestures and video recording conditions require that we adopt a more …...

This paper presents the systems that we par- ticipated with in the Semantic Text Similar- ity task at SEMEVAL 2012. Based on prior research in semantic similarity and related- ness, …...

Learning algorithms for semantic parsing have improved drastically over the past decade, as steady improvements on bench- mark datasets have shown. In this pa- per we investigate whether they can …...

We present an approach for automatically learning to solve algebra word problems. Our algorithm reasons across sentence boundaries to construct and solve a sys- tem of linear equations, while simultane- …...

We present a novel method for the cross- lingual transfer of dependency parsers. Our goal is to induce a dependency parser in a target language of interest without any direct …...

We present two methods for the automatic de- tection of complex words in context as per- ceived by non-native English readers, for the SemEval 2016 Task 11 on Complex Word …...