activity
20182022
most citedA Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis

105 citations · 109 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CV2022

Where Is My Mind (looking at)? Predicting Visual Attention from Brain Activity

Victor Delvigne, Noé Tits, Luca La Fisca +5

Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, artificial intelligence and medicine. One of the most common…

cs.SD2021

Analysis and Assessment of Controllability of an Expressive Deep Learning-based TTS system

Noé Tits, Kevin El Haddad, Thierry Dutoit

In this paper, we study the controllability of an Expressive TTS system trained on a dataset for a continuous control. The dataset is the Blizzard 2013 dataset based on audiobooks…

cs.CL2020

Modulated Fusion using Transformer for Linguistic-Acoustic Emotion Recognition

Jean-Benoit Delbrouck, Noé Tits, Stéphane Dupont

This paper aims to bring a new lightweight yet powerful solution for the task of Emotion Recognition and Sentiment Analysis. Our motivation is to propose two architectures based on…

eess.AS20203 cited

ICE-Talk: an Interface for a Controllable Expressive Talking Machine

Noé Tits, Kevin El Haddad, Thierry Dutoit

ICE-Talk is an open source web-based GUI that allows the use of a TTS system with controllable parameters via a text field and a clickable 2D plot. It enables the study of latent s…

eess.AS2020

Laughter Synthesis: Combining Seq2seq modeling with Transfer Learning

Noé Tits, Kevin El Haddad, Thierry Dutoit

Despite the growing interest for expressive speech synthesis, synthesis of nonverbal expressions is an under-explored area. In this paper we propose an audio laughter synthesis sys…

cs.CL2020105 cited

A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis

Jean-Benoit Delbrouck, Noé Tits, Mathilde Brousmiche +1

Understanding expressed sentiment and emotions are two crucial factors in human multimodal language. This paper describes a Transformer-based joint-encoding (TBJE) for the task of…