no code implementations • 27 Mar 2024 • Leonardo Pepino, Pablo Riera, Luciana Ferrer, Agustin Gravano
In this paper, we study different approaches for classifying emotions from speech using acoustic and text-based features.
1 code implementation • 14 Sep 2023 • Leonardo Pepino, Pablo Riera, Luciana Ferrer
The goal of universal audio representation learning is to obtain foundational models that can be used for a variety of downstream tasks involving speech, music or environmental sounds.
1 code implementation • 30 Jul 2023 • Jazmin Vidal, Pablo Riera, Luciana Ferrer
We compare two downstream approaches: 1) training the model for phone recognition (PR) using native English data, and 2) training a model directly for the target task using non-native English data.
no code implementations • 24 Feb 2023 • Pablo Riera, Manuela Cerdeiro, Leonardo Pepino, Luciana Ferrer
In this work, we analyze the spatial organization of phone and speaker information in several state-of-the-art speech representations using methods that do not require a downstream model.
1 code implementation • 13 Oct 2021 • Leonardo Pepino, Pablo Riera, Luciana Ferrer
Transformers have revolutionized the world of deep learning, specially in the field of natural language processing.
4 code implementations • 30 Apr 2021 • Martin Miguel, Pablo Riera, Diego Fernandez Slezak
It is intended for presenting any auditory stimuli and recording tapping response times with within 2 milliseconds precision (up to -2ms lag).
2 code implementations • 8 Apr 2021 • Leonardo Pepino, Pablo Riera, Luciana Ferrer
Emotion recognition datasets are relatively small, making the use of the more sophisticated deep learning approaches challenging.
no code implementations • 9 Feb 2021 • Lara Gauder, Leonardo Pepino, Pablo Riera, Silvina Brussino, Jazmín Vidal, Agustín Gravano, Luciana Ferrer
An automatic prediction of the level of trust that a user has on a certain system could be used to attempt to correct potential distrust by having the system take relevant actions like, for example, apologizing or explaining its decisions.
no code implementations • 30 Jul 2020 • Leonardo Pepino, Pablo Riera, Lara Gauder, Agustín Gravano, Luciana Ferrer
Research has shown that trust is an essential aspect of human-computer interaction directly determining the degree to which the person is willing to use the system.