50 citations · 62 across the 7 of their papers we have counts for
10 papers
Social-MAE: A Transformer-Based Multimodal Autoencoder for Face and Voice
Hugo Bohy, Minh Tran, Kevin El Haddad +2
Human social behaviors are inherently multimodal necessitating the development of powerful audiovisual models for their perception. In this paper, we present Social-MAE, our pre-tr…
A New Perspective on Smiling and Laughter Detection: Intensity Levels Matter
Hugo Bohy, Kevin El Haddad, Thierry Dutoit
Smiles and laughs detection systems have attracted a lot of attention in the past decade contributing to the improvement of human-agent interaction systems. But very few considered…
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…
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…
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…
The Theory behind Controllable Expressive Speech Synthesis: a Cross-disciplinary Approach
Noé Tits, Kevin El Haddad, Thierry Dutoit
As part of the Human-Computer Interaction field, Expressive speech synthesis is a very rich domain as it requires knowledge in areas such as machine learning, signal processing, so…
Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis
Noé Tits, Fengna Wang, Kevin El Haddad +2
The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques. Producing realistic speech becomes possible now. As a consequence…
Exploring Transfer Learning for Low Resource Emotional TTS
Noé Tits, Kevin El Haddad, Thierry Dutoit
During the last few years, spoken language technologies have known a big improvement thanks to Deep Learning. However Deep Learning-based algorithms require amounts of data that ar…
The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems
Adaeze Adigwe, Noé Tits, Kevin El Haddad +2
In this paper, we present a database of emotional speech intended to be open-sourced and used for synthesis and generation purpose. It contains data for male and female actors in E…
ASR-based Features for Emotion Recognition: A Transfer Learning Approach
Noé Tits, Kevin El Haddad, Thierry Dutoit
During the last decade, the applications of signal processing have drastically improved with deep learning. However areas of affecting computing such as emotional speech synthesis…