activity
20182020
most citedAudiovisual speaker diarization of TV series

18 citations · 33 across the 5 of their papers we have counts for

collaborators

9 papers

cs.IR2020

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…

cs.CV2019

Semantic and Visual Similarities for Efficient Knowledge Transfer in CNN Training

Lucas Pascal, Xavier Bost, Benoît Huet

In recent years, representation learning approaches have disrupted many multimedia computing tasks. Among those approaches, deep convolutional neural networks (CNNs) have notably r…

cs.MM2019

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…

cs.CL2019

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…

cs.CL20181 cited

Multiple topic identification in telephone conversations

Xavier Bost, Marc El Bèze, Renato De Mori

This paper deals with the automatic analysis of conversations between a customer and an agent in a call centre of a customer care service. The purpose of the analysis is to hypothe…

cs.MM20186 cited

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…