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This paper introduces a query refinement method applied to questions asked by users to a system during a meeting or a conversation that they have with other users. To answer the questions, the proposed method leverages the local context of the conversation ...
Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...
For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...
This report presents a study on assisting users in building queries to perform real-time searches in a news and social media monitoring system. The system accepts complex queries, and we assist the user by suggesting related keywords or entities. We do thi ...
Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...
We propose a method for extractive summarization of audiovisual recordings focusing on topic-level segments. We first build a content similarity graph between all segments across the collection, using word vectors from the transcripts, and then select the ...
This paper reports on an approach and experiments to automatically build a cross-lingual multi-word entity resource. Starting from a collection of millions of acronym/expansion pairs for 22 languages where expansion variants were grouped into monolingual c ...
European Language Resources Association (ELRA)2016
A popular application in Natural Language Processing (NLP) is the Sentiment Analysis (SA), i.e., the task of extracting contextual polarity from a given text. The social network Twitter provides an immense amount of text (called tweets) generated by users ...
In this paper, a compressive sensing (CS) perspective to exemplar-based speech processing is proposed. Relying on an analytical relationship between CS formulation and statistical speech recognition (Hidden Markov Models HMM), the automatic speech recognit ...
This paper discusses Kamusi Pre:D, a system to improve translation by disambiguating word senses in a source document with reference to a large concept-based lexicon that is aligned by sense across numerous languages. Currently under active development, th ...