activity
20232026
most citedPath Neural Networks: Expressive and Accurate Graph Neural Networks

4 citations · 7 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2026

Fast and Accurate Quotation Attribution in Literary Texts

Gaspard Michel, Hugo Attali, Elena V. Epure

Attributing quotations to their speakers in literary texts remains an open challenge. Standard methods, which independently predict a speaker mention for each quotation, are effici…

cs.CL2026

GraphLit: Learning Text-Enriched Dynamic Character Network Representations for Literary Study

Gaspard Michel, Elena V. Epure, Romain Hennequin +2

Methods to represent literary texts as graphs or sequences of graphs mainly focus on representing character interactions, and often overlook another crucial aspect: the textual con…

cs.CL2026

S-VoCAL: A Dataset and Evaluation Framework for Inferring Speaking Voice Character Attributes in Literature

Abigail Berthe-Pardo, Gaspard Michel, Elena V. Epure +1

With recent advances in Text-to-Speech (TTS) systems, synthetic audiobook narration has seen increased interest, reaching unprecedented levels of naturalness. However, larger gaps…

eess.AS2025

Computational Narrative Understanding for Expressive Text-to-Speech

Gaspard Michel, Elena V. Epure, Christophe Cerisara

Recent advances in text-to-speech (TTS) have been driven by large, multi-domain speech corpora, yet the expressive potential of audiobook data remains underexamined. We argue that…

cs.CL2024

Evaluating LLMs for Quotation Attribution in Literary Texts: A Case Study of LLaMa3

Gaspard Michel, Elena V. Epure, Romain Hennequin +1

Large Language Models (LLMs) have shown promising results in a variety of literary tasks, often using complex memorized details of narration and fictional characters. In this work,…

cs.CL2024★ 2 cited

Improving Quotation Attribution with Fictional Character Embeddings

Gaspard Michel, Elena V. Epure, Romain Hennequin +1

Humans naturally attribute utterances of direct speech to their speaker in literary works. When attributing quotes, we process contextual information but also access mental represe…

cs.CL2024

Distinguishing Fictional Voices: a Study of Authorship Verification Models for Quotation Attribution

Gaspard Michel, Elena V. Epure, Romain Hennequin +1

Recent approaches to automatically detect the speaker of an utterance of direct speech often disregard general information about characters in favor of local information found in t…

cs.CL2023★ 1 cited

Automatic Annotation of Direct Speech in Written French Narratives

Noé Durandard, Viet-Anh Tran, Gaspard Michel +1

The automatic annotation of direct speech (AADS) in written text has been often used in computational narrative understanding. Methods based on either rules or deep neural networks…

cs.LG2023★ 4 cited

Path Neural Networks: Expressive and Accurate Graph Neural Networks

Gaspard Michel, Giannis Nikolentzos, Johannes Lutzeyer +1

Graph neural networks (GNNs) have recently become the standard approach for learning with graph-structured data. Prior work has shed light into their potential, but also their limi…