In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
We develop a method for detecting errors in semantic predicate-argument annotation, based on the variation n-gram error detection method. After establishing an appropriate data re...
We develop a method to detect erroneous interpretation results of user utterances by exploiting utterance histories of individual users in spoken dialogue systems that were deploy...
This paper proposes an on-line error detecting method for a manually annotated corpus using min-max modular (M3 ) neural networks. The basic idea of the method is to use guaranteed...
We propose a new method for detecting errors in “gold-standard” part-ofspeech annotation. The approach locates errors with high precision based on n-grams occurring in the cor...