Search Results for author: Patrik Lambert

Found 11 papers, 0 papers with code

Improving Robustness in Real-World Neural Machine Translation Engines

no code implementations WS 2019 Rohit Gupta, Patrik Lambert, Raj Nath Patel, John Tinsley

As a commercial provider of machine translation, we are constantly training engines for a variety of uses, languages, and content types.

Machine Translation Translation

Attention and Lexicon Regularized LSTM for Aspect-based Sentiment Analysis

no code implementations ACL 2019 Lingxian Bao, Patrik Lambert, Toni Badia

Abstract Attention based deep learning systems have been demonstrated to be the state of the art approach for aspect-level sentiment analysis, however, end-to-end deep neural networks lack flexibility as one can not easily adjust the network to fix an obvious problem, especially when more training data is not available: e. g. when it always predicts \textit{positive} when seeing the word \textit{disappointed}.

Aspect-Based Sentiment Analysis

MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification

no code implementations LREC 2018 Jeremy Barnes, Patrik Lambert, Toni Badia

While sentiment analysis has become an established field in the NLP community, research into languages other than English has been hindered by the lack of resources.

General Classification Sentiment Analysis

Adapting Freely Available Resources to Build an Opinion Mining Pipeline in Portuguese

no code implementations LREC 2014 Patrik Lambert, Carlos Rodr{\'\i}guez-Penagos

We present a complete UIMA-based pipeline for sentiment analysis in Portuguese news using freely available resources and a minimal set of manually annotated training data.

General Classification Named Entity Recognition +3

Automatic Translation of Scientific Documents in the HAL Archive

no code implementations LREC 2012 Patrik Lambert, Holger Schwenk, Fr{\'e}d{\'e}ric Blain

This paper describes the development of a statistical machine translation system between French and English for scientific papers.

Domain Adaptation Machine Translation +1

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