Natural Language Understanding

The Natural Language Understanding group works at the intersection of machine learning and natural language processing, with an emphasis on representation learning for the meaning of language, attention-based deep learning models, and structured prediction. We model summarization, abstraction (textual entailment), machine translation, knowledge extraction, syntactic structure, and lexical semantics, among other NLP problems. We develop deep learning models of the discovery and prediction of entities and their relations at multiple levels of representation for multiple tasks.

Current Group Members

HENDERSON, James (Brinton)
(Senior Researcher)
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(Research Assistant)
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MICULICICH, Lesly (Sadiht)
(Research Assistant)
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MARFURT, Andreas
(Research Assistant)
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(Research Assistant)
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MAI, Florian
(Research Assistant)
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  • BHATT, Chidansh
  • GASNIER, Catherine
  • HABIBI, Maryam
  • HAJLAOUI, Najeh
  • HONNET, Pierre-Edouard
  • LE, Quoc Anh
  • LISON, Pierre
  • LIYANAPATHIRANA, Jeevanthi Uthpala
  • LOAICIGA, Sharid
  • LUONG, Ngoc-Quang
  • MAHDABI, Parvaz
  • MATENA, Lukas
  • MEYER, Braida (Regula)
  • MEYER, Thomas
  • YAZDANI, Majid

Current Projects

Recent Projects

Group News

Domain adaptation for speech and language processing
education — Feb 08, 2019

The Idiap Research Institute in partnership with Swisscom invites applications for a post-doctoral (or similarly qualified) position in automatic speech recognition (ASR) and natural language processing (NLP). The position is funded by Swisscom, with a view to a long term collaboration.

Andrei Popescu-Belis, professor at HEIG-VD and former Idiap researcher, receives prize for best article
research — Jan 23, 2018

An article, co-authored by Prof. Andrei Popescu-Belis, has received the Best Paper Award at the International Joint Conference on Natural Language Processing (IJCNLP). The article presents the research of Dr Nikolaos Pappas - a postdoc at the Idiap Research Institute in Martigny - under the supervision of Prof. Popescu-Belis, former head of Idiap’s Natural Language Processing group.

Idiap has a new opening for an Internship position in Natural Language Processing on DNN-based coreference models
education — Dec 22, 2016

Co-reference is the relation between words or phrases in a text that refer to the same entity. DNNs have been successfully applied to a variety of NLP tasks, but for coreference resolution such approaches have shown limited improvement and a suitable model remains to be found. The goal of this internship is to go beyond classifiers that decide whether a pair of phrases is co-referent or not, and instead learn to represent, in the output layer, each of the entities of a text. In collaboration with a PhD student and a postdoc, the model will be applied to document-level machine translation. The work will thus relate to the EU SUMMA and SNSF MODERN projects.

Best Multimodal Paper Award to Nikolaos Pappas and co-authors at ICMR 2016
research — Jun 10, 2016

The paper "Multilingual Visual Sentiment Concept Matching" by Nikolaos Pappas, Mercan Topkara, Miriam Redi, Brendan Jou, Tao Chen, Hongyi Liu, Shih-Fu Chang has received the Best Multimodal Paper Award at the Annual ACM International Conference on Multimedia Retrieval (ICMR), held on June 6-9 in New York.

Idiap submission to MediaEval 2013 ranked first for the video hyperlinking task
research — Nov 26, 2013

The Idiap NLP group has participated in the search and hyperlinking task at the MediaEval 2013 evaluation campaign. The NLP group was ranked first out of eleven participants on the hyperlinking task (finding video segments related to a given one) and third out of seven on the keyword video search task.