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Found 29 papers, 8 papers with code
Flux d’informations dans les systèmes encodeur-décodeur. Application à l’explication des biais de genre dans les systèmes de traduction automatique. (Information flow in encoder-decoder systems applied to the explanation of gender bias in machine translation systems)
Ce travail présente deux séries d’expériences visant à identifier les flux d’information dans les systèmes de traduction neuronaux.
Ré-ordonnancement via programmation dynamique pour l’adaptation cross-lingue d’un analyseur en dépendances (Sentence reordering via dynamic programming for cross-lingual dependency parsing )
Cet article s’intéresse au transfert cross-lingue d’analyseurs en dépendances et étudie des méthodes pour limiter l’effet potentiellement néfaste pour le transfert de divergences entre l’ordre des mots dans les langues source et cible.
Modèle-s bayés-ien-s pour la segment-ation à deux niveau-x faible-ment super-vis-é-e (Bayesian models for weakly supervised two-level segmentation )
La segmentation automatique en mots et en morphèmes est une étape cruciale dans le processus de documentation des langues.
Multi-Domain Adaptation in Neural Machine Translation with Dynamic Sampling Strategies
In this paper, we study dynamic data selection strategies that are able to automatically re-evaluate the usefulness of data samples and to evolve a data selection policy in the course of training.
Weakly Supervised Word Segmentation for Computational Language Documentation
Word and morpheme segmentation are fundamental steps of language documentation as they allow to discover lexical units in a language for which the lexicon is unknown.
Two-Step MT: Predicting Target Morphology
This paper describes a two-step machine translation system that addresses the issue of translating into a morphologically rich language (English to Czech), by performing separately the translation and the generation of target morphology.
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation
Supervised machine translation works well when the train and test data are sampled from the same distribution.
LIMSI @ WMT 2020
This paper describes LIMSI’s submissions to the translation shared tasks at WMT’20.
A Study of Residual Adapters for Multi-Domain Neural Machine Translation
Domain adaptation is an old and vexing problem for machine translation systems.
Priming Neural Machine Translation
Priming is a well known and studied psychology phenomenon based on the prior presentation of one stimulus (cue) to influence the processing of a response.
Optimizing Word Alignments with Better Subword Tokenization
Word alignment identify translational correspondences between words in a parallel sentence pair and are used and for example and to train statistical machine translation and learn bilingual dictionaries or to perform quality estimation.
Vers la production automatique de sous-titres adaptés à l’affichage (Towards automatic adapted monolingual captioning)
Une façon de réaliser un sous-titrage automatique monolingue est d’associer un système de reconnaissance de parole avec un modèle de traduction de la transcription vers les sous-titres.
Biais de genre dans un système de traduction automatiqueneuronale : une étude préliminaire (Gender Bias in Neural Translation : a preliminary study )
Cet article présente les premiers résultats d’une étude en cours sur les biais de genre dans les corpus d’entraînements et dans les systèmes de traduction neuronale.
Evaluating Subtitle Segmentation for End-to-end Generation Systems
Subtitle segmentation can be evaluated with sequence segmentation metrics against a human reference.
Joint Generation of Captions and Subtitles with Dual Decoding
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 appears as the only viable way to boost throughput and lower the related post-production costs.
Graph Neural Networks for Multiparallel Word Alignment
First, we create a multiparallel word alignment graph, joining all bilingual word alignment pairs in one graph.
Screening Gender Transfer in Neural Machine Translation
This paper aims at identifying the information flow in state-of-the-art machine translation systems, taking as example the transfer of gender when translating from French into English.
One Source, Two Targets: Challenges and Rewards of Dual Decoding
Machine translation is generally understood as generating one target text from an input source document.
Graph Algorithms for Multiparallel Word Alignment
With the advent of end-to-end deep learning approaches in machine translation, interest in word alignments initially decreased; however, they have again become a focus of research more recently.
Can You Traducir This? Machine Translation for Code-Switched Input
Code-Switching (CSW) is a common phenomenon that occurs in multilingual geographic or social contexts, which raises challenging problems for natural language processing tools.
Generative latent neural models for automatic word alignment
Word alignments identify translational correspondences between words in a parallel sentence pair and are used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems or to perform quality estimation.
Neural Baselines for Word Alignment
Word alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems , or to perform quality estimation.
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings
We find that alignments created from embeddings are superior for four and comparable for two language pairs compared to those produced by traditional statistical aligners, even with abundant parallel data; e. g., contextualized embeddings achieve a word alignment F1 for English-German that is 5 percentage points higher than eflomal, a high-quality statistical aligner, trained on 100k parallel sentences.
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality.
Using Monolingual Data in Neural Machine Translation: a Systematic Study
Our findings confirm that back-translation is very effective and give new explanations as to why this is the case.
Unsupervised Word Segmentation from Speech with Attention
We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL).
Bayesian Models for Unit Discovery on a Very Low Resource Language
Developing speech technologies for low-resource languages has become a very active research field over the last decade.
