75 citations · 168 across the 13 of their papers we have counts for
17 papers
Improving Language Identification for Code-Switched Utterances with Integer Linear Programming
Joanna Radoła, Josep Maria Crego, François Yvon
Automatic identification of code-switched (CS) utterances remains a challenge for language identification (LID) systems, causing such texts to be underrepresented in the training d…
Reasoning about In-Context Samples for Machine-Translation
Maxime Bouthors, Josep Crego, François Yvon
Large Language Models (LLMs) can be trained to perform chain-of-thoughts reasoning in order to improve the reliability of their responses. In this work, we investigate how explicit…
English to Central Kurdish Speech Translation: Corpus Creation, Evaluation, and Orthographic Standardization
Mohammad Mohammadamini, Daban Q. Jaff, Josep Crego +2
We present KUTED, a speech-to-text translation (S2TT) dataset for Central Kurdish, derived from TED and TEDx talks. The corpus comprises 91,000 sentence pairs, including 170 hours…
Improving Retrieval-Augmented Neural Machine Translation with Monolingual Data
Maxime Bouthors, Josep Crego, François Yvon
Conventional retrieval-augmented neural machine translation (RANMT) systems leverage bilingual corpora, e.g., translation memories (TMs). Yet, in many settings, monolingual corpora…
Optimizing example selection for retrieval-augmented machine translation with translation memories
Maxime Bouthors, Josep Crego, François Yvon
Retrieval-augmented machine translation leverages examples from a translation memory by retrieving similar instances. These examples are used to condition the predictions of a neur…
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison
Maxime Bouthors, Josep Crego, Francois Yvon
Retrieval-Augmented Neural Machine Translation (RAMT) architectures retrieve examples from memory to guide the generation process. While most works in this trend explore new ways t…
Towards Example-Based NMT with Multi-Levenshtein Transformers
Maxime Bouthors, Josep Crego, François Yvon
Retrieval-Augmented Machine Translation (RAMT) is attracting growing attention. This is because RAMT not only improves translation metrics, but is also assumed to implement some fo…
BiSync: A Bilingual Editor for Synchronized Monolingual Texts
Josep Crego, Jitao Xu, François Yvon
In our globalized world, a growing number of situations arise where people are required to communicate in one or several foreign languages. In the case of written communication, us…
Bilingual Synchronization: Restoring Translational Relationships with Editing Operations
Jitao Xu, Josep Crego, François Yvon
Machine Translation (MT) is usually viewed as a one-shot process that generates the target language equivalent of some source text from scratch. We consider here a more general set…
Integrating Translation Memories into Non-Autoregressive Machine Translation
Jitao Xu, Josep Crego, François Yvon
Non-autoregressive machine translation (NAT) has recently made great progress. However, most works to date have focused on standard translation tasks, even though some edit-based N…
Joint Generation of Captions and Subtitles with Dual Decoding
Jitao Xu, François Buet, Josep Crego +2
As the amount of audio-visual content increases, the need to develop automatic captioning and subtitling solutions to match the expectations of a growing international audience app…
SYSTRAN Purely Neural MT Engines for WMT2017
Yongchao Deng, Jungi Kim, Guillaume Klein +7
This paper describes SYSTRAN's systems submitted to the WMT 2017 shared news translation task for English-German, in both translation directions. Our systems are built using OpenNM…
Domain specialization: a post-training domain adaptation for Neural Machine Translation
Christophe Servan, Josep Crego, Jean Senellart
Domain adaptation is a key feature in Machine Translation. It generally encompasses terminology, domain and style adaptation, especially for human post-editing workflows in Compute…
Neural Machine Translation from Simplified Translations
Josep Crego, Jean Senellart
Text simplification aims at reducing the lexical, grammatical and structural complexity of a text while keeping the same meaning. In the context of machine translation, we introduc…
Domain Control for Neural Machine Translation
Catherine Kobus, Josep Crego, Jean Senellart
Machine translation systems are very sensitive to the domains they were trained on. Several domain adaptation techniques have been deeply studied. We propose a new technique for ne…
Boosting Neural Machine Translation
Dakun Zhang, Jungi Kim, Josep Crego +1
Training efficiency is one of the main problems for Neural Machine Translation (NMT). Deep networks need for very large data as well as many training iterations to achieve state-of…
SYSTRAN's Pure Neural Machine Translation Systems
Josep Crego, Jungi Kim, Guillaume Klein +27
Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by severa…