5 citations · 8 across the 15 of their papers we have counts for
16 papers
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…
LLM-as-a-Judge for Evaluating System Responses in Conversational Music Recommendation
Seungheon Doh, Bruno Sguerra, Sergio Oramas +2
Conversational Recommendation Systems (CRS) aim to achieve two primary objectives: recommending relevant items and generating natural language responses. While recommendation accur…
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…
Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries
Marion Baranes, Romain Hennequin, Elena V. Epure
Although annotated music descriptor datasets for user queries are increasingly common, few consider the user's intent behind these descriptors, which is essential for effectively m…
Scalable Music Cover Retrieval Using Lyrics-Aligned Audio Embeddings
Joanne Affolter, Benjamin Martin, Elena V. Epure +2
Music Cover Retrieval, also known as Version Identification, aims to recognize distinct renditions of the same underlying musical work, a task central to catalog management, copyri…
Music Recommendation with Large Language Models: Challenges, Opportunities, and Evaluation
Elena V. Epure, Yashar Deldjoo, Bruno Sguerra +2
Music Recommender Systems (MRSs) have long relied on an information retrieval framing, where progress is measured mainly through accuracy on retrieval-oriented subtasks. While effe…
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…
Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Alessandro B. Melchiorre, Elena V. Epure, Shahed Masoudian +4
Natural language interfaces offer a compelling approach for music recommendation, enabling users to express complex preferences conversationally. While Large Language Models (LLMs)…
AI-Generated Song Detection via Lyrics Transcripts
Markus Frohmann, Elena V. Epure, Gabriel Meseguer-Brocal +2
The recent rise in capabilities of AI-based music generation tools has created an upheaval in the music industry, necessitating the creation of accurate methods to detect such AI-g…
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…
Harnessing High-Level Song Descriptors towards Natural Language-Based Music Recommendation
Elena V. Epure, Gabriel Meseguer-Brocal, Darius Afchar +1
Recommender systems relying on Language Models (LMs) have gained popularity in assisting users to navigate large catalogs. LMs often exploit item high-level descriptors, i.e. categ…
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,…
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…
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…