Search Results for author: Rachel Bawden

Found 29 papers, 7 papers with code

Le projet FREEM : ressources, outils et enjeux pour l’étude du français d’Ancien Régime (The F RE EM project: Resources, tools and challenges for the study of Ancien Régime French)

no code implementations JEP/TALN/RECITAL 2022 Simon Gabay, Pedro Ortiz Suarez, Rachel Bawden, Alexandre Bartz, Philippe Gambette, Benoît Sagot

En dépit de leur qualité certaine, les ressources et outils disponibles pour l’analyse du français d’Ancien Régime ne sont plus à même de répondre aux enjeux de la recherche en linguistique et en littérature pour cette période.

The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task

no code implementations WMT (EMNLP) 2020 Nikita Moghe, Christian Hardmeier, Rachel Bawden

Our baseline systems are transformer-big models that are pre-trained on the WMT’19 News Translation task and fine-tuned on pseudo-in-domain web crawled data and in-domain task data.

Machine Translation Translation

The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task

no code implementations WMT (EMNLP) 2020 Rachel Bawden, Alexandra Birch, Radina Dobreva, Arturo Oncevay, Antonio Valerio Miceli Barone, Philip Williams

We describe the University of Edinburgh’s submissions to the WMT20 news translation shared task for the low resource language pair English-Tamil and the mid-resource language pair English-Inuktitut.

Language Modelling Machine Translation +1

ParBLEU: Augmenting Metrics with Automatic Paraphrases for the WMT’20 Metrics Shared Task

no code implementations WMT (EMNLP) 2020 Rachel Bawden, Biao Zhang, Andre Tättar, Matt Post

We describe parBLEU, parCHRF++, and parESIM, which augment baseline metrics with automatically generated paraphrases produced by PRISM (Thompson and Post, 2020a), a multilingual neural machine translation system.

Machine Translation Translation

MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification

no code implementations24 May 2022 Yu Lu Liu, Rachel Bawden, Thomas Scaliom, Benoît Sagot, Jackie Chi Kit Cheung

In text summarization and simplification, system outputs must be evaluated along multiple dimensions such as relevance, factual consistency, fluency, and grammaticality, and a wide range of possible outputs could be of high quality.

Language Modelling Masked Language Modeling +2

From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French

no code implementations18 Feb 2022 Simon Gabay, Pedro Ortiz Suarez, Alexandre Bartz, Alix Chagué, Rachel Bawden, Philippe Gambette, Benoît Sagot

Because these historical states are at the same time more complex to process and more scarce in the corpora available, specific efforts are necessary to train natural language processing (NLP) tools adapted to the data.

Language Modelling Natural Language Processing +2

Few-shot learning through contextual data augmentation

1 code implementation EACL 2021 Farid Arthaud, Rachel Bawden, Alexandra Birch

Machine translation (MT) models used in industries with constantly changing topics, such as translation or news agencies, need to adapt to new data to maintain their performance over time.

Data Augmentation Few-Shot Learning +3

Document Sub-structure in Neural Machine Translation

1 code implementation LREC 2020 Radina Dobreva, Jie zhou, Rachel Bawden

Current approaches to machine translation (MT) either translate sentences in isolation, disregarding the context they appear in, or model context at the level of the full document, without a notion of any internal structure the document may have.

Machine Translation Translation

DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation

2 code implementations30 May 2019 Rachel Bawden, Sophie Rosset, Thomas Lavergne, Eric Bilinski

We provide a preliminary analysis of the corpus to confirm that the participants' judgments reveal perceptible differences in MT quality between the two MT systems used.

Machine Translation Translation

Detecting context-dependent sentences in parallel corpora

no code implementations JEPTALNRECITAL 2018 Rachel Bawden, Thomas Lavergne, Sophie Rosset

In this article, we provide several approaches to the automatic identification of parallel sentences that require sentence-external linguistic context to be correctly translated.

Machine Translation Translation

Evaluating Discourse Phenomena in Neural Machine Translation

no code implementations NAACL 2018 Rachel Bawden, Rico Sennrich, Alexandra Birch, Barry Haddow

Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50% accuracy on our coreference test set and 53. 5% for coherence/cohesion (compared to a non-contextual baseline of 50%).

Machine Translation Translation

Machine Translation of Speech-Like Texts: Strategies for the Inclusion of Context

no code implementations JEPTALNRECITAL 2017 Rachel Bawden

Whilst the focus of Machine Translation (MT) has for a long time been the translation of planned, written texts, more and more research is being dedicated to translating speech-like texts (informal or spontaneous discourse or dialogue).

Machine Translation TAG +1

Correcting and Validating Syntactic Dependency in the Spoken French Treebank Rhapsodie

no code implementations LREC 2014 Rachel Bawden, Marie-Am{\'e}lie Botalla, Kim Gerdes, Sylvain Kahane

The micro-syntactic annotation process, presented in this paper, includes a semi-automatic preparation of the transcription, the application of a syntactic dependency parser, transcoding of the parsing results to the Rhapsodie annotation scheme, manual correction by multiple annotators followed by a validation process, and finally the application of coherence rules that check common errors.

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