Guillaume Pitel


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Unsupervised Word Sense Induction from Multiple Semantic Spaces with Locality Sensitive Hashing
Claire Mouton | Guillaume Pitel | Gaël de Chalendar | Anne Vilnat
Proceedings of the International Conference RANLP-2009


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Semi-automatic Building Method for a Multidimensional Affect Dictionary for a New Language
Guillaume Pitel | Gregory Grefenstette
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Detecting the tone or emotive content of a text message is increasingly important in many natural language processing applications. While for the English language there exists a number of affect, emotive, opinion, or affect computer-usable lexicons for automatically processing text, other languages rarely possess these primary resources. Here we present a semi-automatic technique for quickly building a multidimensional affect lexicon for a new language. Most of the work consists of defining 44 paired affect directions (e.g. love-hate, courage-fear, etc.) and choosing a small number of seed words for each dimension. From this initial investment, we show how a first pass affect lexicon can be created for new language, using a SVM classifier trained on a feature space produced from Latent Semantic Analysis over a large corpus in the new language. We evaluate the accuracy of placing newly found emotive words in one or more of the defined semantic dimensions. We illustrate this technique by creating an affect lexicon for French, but the techniques can be applied to any language found on the Web and for which a large quantity of text exists.


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A Deep-Parsing Approach to Natural Language Understanding in Dialogue System: Results of a Corpus-Based Evaluation
Alexandre Denis | Matthieu Quignard | Guillaume Pitel
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

This paper presents an approach to dialogue understanding based on a deep parsing and rule-based semantic analysis. Its performance in the semantic evaluation performed in the framework of the EVALDA/MEDIA campaign is encouraging. The MEDIA project aims to evaluate natural language understanding systems for French on a hotel reservation task (Devillers et al., 2004). For the evaluation, five participating teams had to produce an annotated version of the input utterances in compliance with a commonly agreed format (the MEDIA formalism). An approach based on symbolic processing was not straightforward given the conditions of the evaluation but we achieved a score close to that of statistical systems, without needing an annotated corpus. Despite the architecture has been designed for this campaign, exclusively dedicated to spoken dialogue understanding, we believe that our approach based on a LTAG parser and two ontologies can be used in real dialogue systems, providing quite robust speech understanding and facilities for interfacing with a dialogue manager and the application itself.

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Resolution of Referents Groupings in Practical Dialogues
Alexandre Denis | Guillaume Pitel | Matthieu Quignard
Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue

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Scaling Construction Grammar up to Production Systems: the Situated Constructional Interpretation Model
Guillaume Pitel
Proceedings of the Third Workshop on Scalable Natural Language Understanding