From the 1 of 16 linked papers with an AI index.
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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…
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…
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…
Double Entendre: Robust Audio-Based AI-Generated Lyrics Detection via Multi-View Fusion
Markus Frohmann, Gabriel Meseguer-Brocal, Markus Schedl +1
The rapid advancement of AI-based music generation tools is revolutionizing the music industry but also posing challenges to artists, copyright holders, and providers alike. This n…
Synthetic Lyrics Detection Across Languages and Genres
Yanis Labrak, Markus Frohmann, Gabriel Meseguer-Brocal +1
In recent years, the use of large language models (LLMs) to generate music content, particularly lyrics, has gained in popularity. These advances provide valuable tools for artists…
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,…