963 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut national de recherche en sciences et technologies du numériqueFR300 papers
- Université de LorraineFR277 papers
- Centre National de la Recherche ScientifiqueFR269 papers
- Centre Inria de l'Université de LorraineFR87 papers
- Sorbonne UniversitéFR26 papers
- Institut Élie Cartan de LorraineFR19 papers
- Université Paris-SaclayFR18 papers
- MOCQUA: Modèles de calcul émergentsFR17 papers
- Laboratoire d'Informatique de Paris-NordFR16 papers
- Université Sorbonne Paris NordFR16 papers
- Institut de Recherche en Informatique de ToulouseFR13 papers
- National Institute of InformaticsJP13 papers
61 papers · 1 filter
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…
MILE-RefHumEval: A Reference-Free, Multi-Independent LLM Framework for Human-Aligned Evaluation
Nalin Srun, Parisa Rastin, Guénaël Cabanes +1
We introduce MILE-RefHumEval, a reference-free framework for evaluating Large Language Models (LLMs) without ground-truth annotations or evaluator coordination. It leverages an ens…
BEST-RQ-Based Self-Supervised Learning for Whisper Domain Adaptation
Raphaël Bagat, Irina Illina, Emmanuel Vincent
Automatic Speech Recognition (ASR) systems, despite large multilingual training, struggle in low-resource scenarios where labeled data is scarce. We propose BEARD (BEST-RQ Encoder…
QUARTZ : QA-based Unsupervised Abstractive Refinement for Task-oriented Dialogue Summarization
Mohamed Imed Eddine Ghebriout, Gaël Guibon, Ivan Lerner +1
Dialogue summarization aims to distill the core meaning of a conversation into a concise text. This is crucial for reducing the complexity and noise inherent in dialogue-heavy appl…
Towards Skeletal and Signer Noise Reduction in Sign Language Production via Quaternion-Based Pose Encoding and Contrastive Learning
Guilhem Fauré, Mostafa Sadeghi, Sam Bigeard +1
One of the main challenges in neural sign language production (SLP) lies in the high intra-class variability of signs, arising from signer morphology and stylistic variety in the t…
"Wait, did you mean the doctor?": Collecting a Dialogue Corpus for Topical Analysis
Amandine Decker, Vincent Tourneur, Maxime Amblard +1
Dialogue is at the core of human behaviour and being able to identify the topic at hand is crucial to take part in conversation. Yet, there are few accounts of the topical organisa…
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…
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation
Barbara Gendron, Gaël Guibon
The advent of deep learning models has made a considerable contribution to the achievement of Emotion Recognition in Conversation (ERC). However, this task still remains an importa…
With a Little Help from my (Linguistic) Friends: Topic Segmentation of Multi-party Casual Conversations
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. Understanding th…
Topic and genre in dialogue
Amandine Decker, Ellen Breitholtz, Christine Howes +1
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. In particular, the…
Tips for making the most of 64-bit architectures in langage design, libraries or garbage collection
Benoît Sonntag, Dominique Colnet
The 64-bit architectures that have become standard today offer unprecedented low-level programming possibilities. For the first time in the history of computing, the size of addres…
The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Research
Mohamed Abdalla, Jan Philip Wahle, Terry Ruas +4
Recent advances in deep learning methods for natural language processing (NLP) have created new business opportunities and made NLP research critical for industry development. As o…
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
Spandan Dey, Md Sahidullah, Goutam Saha
Automatic spoken language identification (LID) is a very important research field in the era of multilingual voice-command-based human-computer interaction (HCI). A front-end LID m…
Multi-Task Learning for Depression Detection in Dialogs
Chuyuan Li, Chloé Braud, Maxime Amblard
Depression is a serious mental illness that impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work exam…
The VoicePrivacy 2020 Challenge Evaluation Plan
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang +8
The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the…
The VoicePrivacy 2020 Challenge: Results and findings
Natalia Tomashenko, Xin Wang, Emmanuel Vincent +11
This paper presents the results and analyses stemming from the first VoicePrivacy 2020 Challenge which focuses on developing anonymization solutions for speech technology. We provi…
Improving Automatic Hate Speech Detection with Multiword Expression Features
Nicolas Zampieri, Irina Illina, Dominique Fohr
The task of automatically detecting hate speech in social media is gaining more and more attention. Given the enormous volume of content posted daily, human monitoring of hate spee…
Multilingual AMR-to-Text Generation
Angela Fan, Claire Gardent
Generating text from structured data is challenging because it requires bridging the gap between (i) structure and natural language (NL) and (ii) semantically underspecified input…
On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition
Christophe Cerisara, Pavel Kral, Ladislav Lenc
Dialogue act recognition is an important component of a large number of natural language processing pipelines. Many research works have been carried out in this area, but relativel…
Augmenting Transformers with KNN-Based Composite Memory for Dialogue
Angela Fan, Claire Gardent, Chloe Braud +1
Various machine learning tasks can benefit from access to external information of different modalities, such as text and images. Recent work has focused on learning architectures w…
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Leonardo F. R. Ribeiro, Yue Zhang, Claire Gardent +1
Recent graph-to-text models generate text from graph-based data using either global or local aggregation to learn node representations. Global node encoding allows explicit communi…
Evaluating Voice Conversion-based Privacy Protection against Informed Attackers
Brij Mohan Lal Srivastava, Nathalie Vauquier, Md Sahidullah +3
Speech data conveys sensitive speaker attributes like identity or accent. With a small amount of found data, such attributes can be inferred and exploited for malicious purposes: v…
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
Angela Fan, Claire Gardent, Chloe Braud +1
Query-based open-domain NLP tasks require information synthesis from long and diverse web results. Current approaches extractively select portions of web text as input to Sequence-…
Enhancing AMR-to-Text Generation with Dual Graph Representations
Leonardo F. R. Ribeiro, Claire Gardent, Iryna Gurevych
Generating text from graph-based data, such as Abstract Meaning Representation (AMR), is a challenging task due to the inherent difficulty in how to properly encode the structure o…