Search Results for author: Amandine Decker

Found 5 papers, 0 papers with code

With a Little Help from my (Linguistic) Friends: Topic Segmentation of Multi-party Casual Conversations

no code implementations5 Feb 2024 Amandine Decker, Maxime Amblard

Topics play an important role in the global organisation of a conversation as what is currently discussed constrains the possible contributions of the participant.

Topic and genre in dialogue

no code implementations6 Dec 2023 Amandine Decker, Ellen Breitholtz, Christine Howes, Staffan Larsson

In this paper we argue that topic plays a fundamental role in conversations, and that the concept is needed in addition to that of genre to define interactions.

Tackling Morphological Analogies Using Deep Learning -- Extended Version

no code implementations9 Nov 2021 Safa Alsaidi, Amandine Decker, Esteban Marquer, Pierre-Alexandre Murena, Miguel Couceiro

We demonstrate our model's competitive performance on analogy detection and resolution over multiple languages.

A Neural Approach for Detecting Morphological Analogies

no code implementations9 Aug 2021 Safa Alsaidi, Amandine Decker, Puthineath Lay, Esteban Marquer, Pierre-Alexandre Murena, Miguel Couceiro

In fact, symbolic approaches were developed to solve or to detect analogies between character strings, e. g., the axiomatic approach as well as that based on Kolmogorov complexity.

On the Transferability of Neural Models of Morphological Analogies

no code implementations9 Aug 2021 Safa Alsaidi, Amandine Decker, Puthineath Lay, Esteban Marquer, Pierre-Alexandre Murena, Miguel Couceiro

Analogical proportions are statements expressed in the form "A is to B as C is to D" and are used for several reasoning and classification tasks in artificial intelligence and natural language processing (NLP).

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