106 citations · 385 across the 23 of their papers we have counts for
24 papers
Graph embeddings for Abusive Language Detection
Noé Cecillon, Vincent Labatut, Richard Dufour +1
Abusive behaviors are common on online social networks. The increasing frequency of antisocial behaviors forces the hosts of online platforms to find new solutions to address this…
WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection
Noé Cecillon, Vincent Labatut, Richard Dufour +1
With the spread of online social networks, it is more and more difficult to monitor all the user-generated content. Automating the moderation process of the inappropriate exchange…
Serial Speakers: a Dataset of TV Series
Xavier Bost, Vincent Labatut, Georges Linares
For over a decade, TV series have been drawing increasing interest, both from the audience and from various academic fields. But while most viewers are hooked on the continuous plo…
Remembering Winter Was Coming: Character-Oriented Video Summaries of TV Series
Xavier Bost, Serigne Gueye, Vincent Labatut +4
Today's popular TV series tend to develop continuous, complex plots spanning several seasons, but are often viewed in controlled and discontinuous conditions. Consequently, most vi…
Real to H-space Encoder for Speech Recognition
Titouan Parcollet, Mohamed Morchid, Georges Linarès +1
Deep neural networks (DNNs) and more precisely recurrent neural networks (RNNs) are at the core of modern automatic speech recognition systems, due to their efficiency to process i…
Abusive Language Detection in Online Conversations by Combining Content-and Graph-based Features
Noé Cecillon, Vincent Labatut, Richard Dufour +1
In recent years, online social networks have allowed worldwide users to meet and discuss. As guarantors of these communities, the administrators of these platforms must prevent use…
M2H-GAN: A GAN-based Mapping from Machine to Human Transcripts for Speech Understanding
Titouan Parcollet, Mohamed Morchid, Xavier Bost +1
Deep learning is at the core of recent spoken language understanding (SLU) related tasks. More precisely, deep neural networks (DNNs) drastically increased the performances of SLU…
Conversational Networks for Automatic Online Moderation
Etienne Papegnies, Vincent Labatut, Richard Dufour +1
Moderation of user-generated content in an online community is a challenge that has great socio-economical ramifications. However, the costs incurred by delegating this work to hum…
Constrained speaker diarization of TV series based on visual patterns
Xavier Bost, Georges Linares
Speaker diarization, usually denoted as the ''who spoke when'' task, turns out to be particularly challenging when applied to fictional films, where many characters talk in various…
Audiovisual speaker diarization of TV series
Xavier Bost, Georges Linarès, Serigne Gueye
Speaker diarization may be difficult to achieve when applied to narrative films, where speakers usually talk in adverse acoustic conditions: background music, sound effects, wide v…
Speech recognition with quaternion neural networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid +2
Neural network architectures are at the core of powerful automatic speech recognition systems (ASR). However, while recent researches focus on novel model architectures, the acoust…
Bidirectional Quaternion Long-Short Term Memory Recurrent Neural Networks for Speech Recognition
Titouan Parcollet, Mohamed Morchid, Georges Linarès +1
Recurrent neural networks (RNN) are at the core of modern automatic speech recognition (ASR) systems. In particular, long-short term memory (LSTM) recurrent neural networks have ac…
Quaternion Convolutional Neural Networks for Heterogeneous Image Processing
Titouan Parcollet, Mohamed Morchid, Georges Linarès
Convolutional neural networks (CNN) have recently achieved state-of-the-art results in various applications. In the case of image recognition, an ideal model has to learn independe…
Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition
Titouan Parcollet, Ying Zhang, Mohamed Morchid +4
Recently, the connectionist temporal classification (CTC) model coupled with recurrent (RNN) or convolutional neural networks (CNN), made it easier to train speech recognition syst…
Quaternion Recurrent Neural Networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid +4
Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due to their capability to learn short and long-term dependencies between the basic elements o…
Extraction and Analysis of Dynamic Conversational Networks from TV Series
Xavier Bost, Vincent Labatut, Serigne Gueye +1
Identifying and characterizing the dynamics of modern tv series subplots is an open problem. One way is to study the underlying social network of interactions between the character…
Graph-based Features for Automatic Online Abuse Detection
Etienne Papegnies, Vincent Labatut, Richard Dufour +1
While online communities have become increasingly important over the years, the moderation of user-generated content is still performed mostly manually. Automating this task is an…
Impact Of Content Features For Automatic Online Abuse Detection
Etienne Papegnies, Vincent Labatut, Richard Dufour +1
Online communities have gained considerable importance in recent years due to the increasing number of people connected to the Internet. Moderating user content in online communiti…
Automatic Text Summarization Approaches to Speed up Topic Model Learning Process
Mohamed Morchid, Juan-Manuel Torres-Moreno, Richard Dufour +2
The number of documents available into Internet moves each day up. For this reason, processing this amount of information effectively and expressibly becomes a major concern for co…
Parallel Long Short-Term Memory for Multi-stream Classification
Mohamed Bouaziz, Mohamed Morchid, Richard Dufour +2
Recently, machine learning methods have provided a broad spectrum of original and efficient algorithms based on Deep Neural Networks (DNN) to automatically predict an outcome with…
Narrative Smoothing: Dynamic Conversational Network for the Analysis of TV Series Plots
Xavier Bost, Vincent Labatut, Serigne Gueye +1
Modern popular TV series often develop complex storylines spanning several seasons, but are usually watched in quite a discontinuous way. As a result, the viewer generally needs a…
Learning to retrieve out-of-vocabulary words in speech recognition
Imran Sheikh, Irina Illina, Dominique Fohr +1
Many Proper Names (PNs) are Out-Of-Vocabulary (OOV) words for speech recognition systems used to process diachronic audio data. To help recovery of the PNs missed by the system, re…
Forecasting popularity of videos in YouTube
Cedric Richier, Rachid Elazouzi, Tania Jimenez +2
This paper proposes a new prediction process to explain and predict popularity evolution of YouTube videos. We exploit our recent study on the classification of YouTube videos in o…
Modelling View-count Dynamics in YouTube
Cédric Richier, Eitan Altman, Rachid Elazouzi +3
The goal of this paper is to study the behaviour of view-count in YouTube. We first propose several bio-inspired models for the evolution of the view-count of YouTube videos. We sh…