Search Results for author: Loïc Barrault

Found 26 papers, 13 papers with code

Findings of the IWSLT 2022 Evaluation Campaign

no code implementations IWSLT (ACL) 2022 Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, Marcely Zanon Boito, Ondřej Bojar, Roldano Cattoni, Anna Currey, Georgiana Dinu, Kevin Duh, Maha Elbayad, Clara Emmanuel, Yannick Estève, Marcello Federico, Christian Federmann, Souhir Gahbiche, Hongyu Gong, Roman Grundkiewicz, Barry Haddow, Benjamin Hsu, Dávid Javorský, Vĕra Kloudová, Surafel Lakew, Xutai Ma, Prashant Mathur, Paul McNamee, Kenton Murray, Maria Nǎdejde, Satoshi Nakamura, Matteo Negri, Jan Niehues, Xing Niu, John Ortega, Juan Pino, Elizabeth Salesky, Jiatong Shi, Matthias Sperber, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Yogesh Virkar, Alexander Waibel, Changhan Wang, Shinji Watanabe

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.

Speech-to-Speech Translation Translation

Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022

no code implementations IWSLT (ACL) 2022 Sebastian T. Vincent, Loïc Barrault, Carolina Scarton

This paper describes the SLT-CDT-UoS group's submission to the first Special Task on Formality Control for Spoken Language Translation, part of the IWSLT 2022 Evaluation Campaign.

Domain Adaptation Re-Ranking +1

Controlling Extra-Textual Attributes about Dialogue Participants: A Case Study of English-to-Polish Neural Machine Translation

no code implementations10 May 2022 Sebastian T. Vincent, Loïc Barrault, Carolina Scarton

We focus on the underresearched problem of utilising external metadata in automatic translation of TV dialogue, proposing a case study where a wide range of approaches for controlling attributes in translation is employed in a multi-attribute scenario.

Machine Translation Morphological Analysis +1

Speech Resources in the Tamasheq Language

1 code implementation13 Jan 2022 Marcely Zanon Boito, Fethi Bougares, Florentin Barbier, Souhir Gahbiche, Loïc Barrault, Mickael Rouvier, Yannick Estève

In this paper we present two datasets for Tamasheq, a developing language mainly spoken in Mali and Niger.

Translation

Active Learning by Acquiring Contrastive Examples

1 code implementation EMNLP 2021 Katerina Margatina, Giorgos Vernikos, Loïc Barrault, Nikolaos Aletras

Common acquisition functions for active learning use either uncertainty or diversity sampling, aiming to select difficult and diverse data points from the pool of unlabeled data, respectively.

Active Learning Natural Language Understanding

Simultaneous Machine Translation with Visual Context

1 code implementation EMNLP 2020 Ozan Caglayan, Julia Ive, Veneta Haralampieva, Pranava Madhyastha, Loïc Barrault, Lucia Specia

Simultaneous machine translation (SiMT) aims to translate a continuous input text stream into another language with the lowest latency and highest quality possible.

Machine Translation Translation

Probing the Need for Visual Context in Multimodal Machine Translation

no code implementations NAACL 2019 Ozan Caglayan, Pranava Madhyastha, Lucia Specia, Loïc Barrault

Current work on multimodal machine translation (MMT) has suggested that the visual modality is either unnecessary or only marginally beneficial.

Multimodal Machine Translation Translation

Multimodal Grounding for Sequence-to-Sequence Speech Recognition

1 code implementation9 Nov 2018 Ozan Caglayan, Ramon Sanabria, Shruti Palaskar, Loïc Barrault, Florian Metze

Specifically, in our previous work, we propose a multistep visual adaptive training approach which improves the accuracy of an audio-based Automatic Speech Recognition (ASR) system.

Automatic Speech Recognition Sequence-To-Sequence Speech Recognition

How2: A Large-scale Dataset for Multimodal Language Understanding

1 code implementation1 Nov 2018 Ramon Sanabria, Ozan Caglayan, Shruti Palaskar, Desmond Elliott, Loïc Barrault, Lucia Specia, Florian Metze

In this paper, we introduce How2, a multimodal collection of instructional videos with English subtitles and crowdsourced Portuguese translations.

Automatic Speech Recognition Machine Translation +1

LIUM-CVC Submissions for WMT18 Multimodal Translation Task

no code implementations WS 2018 Ozan Caglayan, Adrien Bardet, Fethi Bougares, Loïc Barrault, Kai Wang, Marc Masana, Luis Herranz, Joost Van de Weijer

This paper describes the multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT18 Shared Task on Multimodal Translation.

Machine Translation Translation

What you can cram into a single vector: Probing sentence embeddings for linguistic properties

5 code implementations3 May 2018 Alexis Conneau, German Kruszewski, Guillaume Lample, Loïc Barrault, Marco Baroni

Although much effort has recently been devoted to training high-quality sentence embeddings, we still have a poor understanding of what they are capturing.

General Classification Sentence Classification +1

Neural Machine Translation by Generating Multiple Linguistic Factors

no code implementations5 Dec 2017 Mercedes García-Martínez, Loïc Barrault, Fethi Bougares

FNMT system is designed to manage larger vocabulary and reduce the training time (for systems with equivalent target language vocabulary size).

Machine Translation Translation

LIUM Machine Translation Systems for WMT17 News Translation Task

1 code implementation WS 2017 Mercedes García-Martínez, Ozan Caglayan, Walid Aransa, Adrien Bardet, Fethi Bougares, Loïc Barrault

This paper describes LIUM submissions to WMT17 News Translation Task for English-German, English-Turkish, English-Czech and English-Latvian language pairs.

Machine Translation Translation

LIUM-CVC Submissions for WMT17 Multimodal Translation Task

no code implementations WS 2017 Ozan Caglayan, Walid Aransa, Adrien Bardet, Mercedes García-Martínez, Fethi Bougares, Loïc Barrault, Marc Masana, Luis Herranz, Joost Van de Weijer

This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation.

Machine Translation Translation

NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems

1 code implementation1 Jun 2017 Ozan Caglayan, Mercedes García-Martínez, Adrien Bardet, Walid Aransa, Fethi Bougares, Loïc Barrault

nmtpy has been used for LIUM's top-ranked submissions to WMT Multimodal Machine Translation and News Translation tasks in 2016 and 2017.

Multimodal Machine Translation Translation

Multimodal Attention for Neural Machine Translation

1 code implementation13 Sep 2016 Ozan Caglayan, Loïc Barrault, Fethi Bougares

We show that a dedicated attention for each modality achieves up to 1. 6 points in BLEU and METEOR compared to a textual NMT baseline.

Image Captioning Machine Translation +1

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