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- Thomas Lavergne, Olivier Cappé, François Yvon
- ACL
- 2010
Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate structural dependency… (More)
- Hai Son Le, Alexandre Allauzen, François Yvon
- HLT-NAACL
- 2012
The use of conventional maximum likelihood estimates hinders the performance of existing phrase-based translation models. For lack of sufficient training data, most models only consider a small… (More)
- Hemant Misra, François Yvon, Joemon M. Jose, Olivier Cappé
- CIKM
- 2009
In this paper, the task of text segmentation is approached from a topic modeling perspective. We investigate the use of latent Dirichlet allocation (LDA) topic model to segment a text into… (More)
- Hai Son Le, Ilya Oparin, Alexandre Allauzen, Jean-Luc Gauvain, François Yvon
- 2011 IEEE International Conference on Acoustics…
- 2011
This paper introduces a new neural network language model (NNLM) based on word clustering to structure the output vocabulary: Structured Output Layer NNLM. This model is able to handle vocabularies… (More)
- Catherine Kobus, François Yvon, Géraldine Damnati
- COLING
- 2008
Electronic written texts used in computermediated interactions (e-mails, blogs, chats, etc) present major deviations from the norm of the language. This paper presents an comparative study of systems… (More)
- Loïs Rigouste, Olivier Cappé, François Yvon
- Inf. Process. Manage.
- 2007
In this article, we investigate the use of a probabilistic model for unsupervised clustering in text collections. Unsupervised clustering has become a basic module for many intelligent text… (More)
- Josep Maria Crego, François Yvon, José B. Mariño
- Prague Bull. Math. Linguistics
- 2011
This paper describes N, an open source statistical machine translation (SMT) toolkit for translation models estimated as n-gram language models of bilingual units (tuples). This toolkit includes… (More)
- Philippe Langlais, François Yvon
- COLING
- 2008
Recent years have witnessed a growing interest in analogical learning for NLP applications. If the principle of analogical learning is quite simple, it does involve complex steps that seriously limit… (More)
- Hai Son Le, Ilya Oparin, Alexandre Allauzen, Jean-Luc Gauvain, François Yvon
- IEEE Transactions on Audio, Speech, and Language…
- 2013
This paper extends a novel neural network language model (NNLM) which relies on word clustering to structure the output vocabulary: Structured OUtput Layer (SOUL) NNLM. This model is able to handle… (More)
- Hai Son Le, Thomas Lavergne, +6 authors François Yvon
- WMT@NAACL-HLT
- 2012
Data Pre-processing • Better normalization tools provide better BLEU scores • Specific pre-processing for German as source language • Cleaning noisy data sets (GigaWord) – Discard sentences in other… (More)