Search Results for author: Maureen de Seyssel

Found 6 papers, 1 papers with code

Is the Language Familiarity Effect gradual? A computational modelling approach

no code implementations27 Jun 2022 Maureen de Seyssel, Guillaume Wisniewski, Emmanuel Dupoux

According to the Language Familiarity Effect (LFE), people are better at discriminating between speakers of their native language.

Probing phoneme, language and speaker information in unsupervised speech representations

no code implementations30 Mar 2022 Maureen de Seyssel, Marvin Lavechin, Yossi Adi, Emmanuel Dupoux, Guillaume Wisniewski

Language information, however, is very salient in the bilingual model only, suggesting CPC models learn to discriminate languages when trained on multiple languages.

Language Modelling

The Zero Resource Speech Challenge 2021: Spoken language modelling

no code implementations29 Apr 2021 Ewan Dunbar, Mathieu Bernard, Nicolas Hamilakis, Tu Anh Nguyen, Maureen de Seyssel, Patricia Rozé, Morgane Rivière, Eugene Kharitonov, Emmanuel Dupoux

We present the Zero Resource Speech Challenge 2021, which asks participants to learn a language model directly from audio, without any text or labels.

Language Modelling

The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

1 code implementation23 Nov 2020 Tu Anh Nguyen, Maureen de Seyssel, Patricia Rozé, Morgane Rivière, Evgeny Kharitonov, Alexei Baevski, Ewan Dunbar, Emmanuel Dupoux

We introduce a new unsupervised task, spoken language modeling: the learning of linguistic representations from raw audio signals without any labels, along with the Zero Resource Speech Benchmark 2021: a suite of 4 black-box, zero-shot metrics probing for the quality of the learned models at 4 linguistic levels: phonetics, lexicon, syntax and semantics.

Language Modelling Representation Learning

Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases

no code implementations6 Jul 2019 Estelle Maudet, Oralie Cattan, Maureen de Seyssel, Christophe Servan

For this task, we propose an approach based on language models and evaluate the impact on the results of different preprocessings and matching techniques.

Information Retrieval Semantic Similarity +1

Qwant Research @DEFT 2019 : appariement de documents et extraction d'informations \`a partir de cas cliniques (Document matching and information retrieval using clinical cases)

no code implementations JEPTALNRECITAL 2019 Estelle Maudet, Oralie Cattan, Maureen de Seyssel, Christophe Servan

Pour r{\'e}soudre cette t{\^a}che, nous proposons une approche reposant sur des mod{\`e}les de langue et {\'e}valuons l{'}impact de diff{\'e}rents pr{\'e}-traitements et de diff{\'e}rentes techniques d{'}appariement sur les r{\'e}sultats.

Information Retrieval

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