most citedFusion approaches for emotion recognition from speech using acoustic and text-based features

57 citations · 59 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Good practices for evaluation of machine learning systems

Luciana Ferrer, Odette Scharenborg, Tom Bäckström

Many development decisions affect the results obtained from ML experiments: training data, features, model architecture, hyperparameters, test data, etc. Among these aspects, argua…

stat.ML20242 cited

Evaluating Posterior Probabilities: Decision Theory, Proper Scoring Rules, and Calibration

Luciana Ferrer, Daniel Ramos

Most machine learning classifiers are designed to output posterior probabilities for the classes given the input sample. These probabilities may be used to make the categorical dec…

cs.LG202457 cited

Fusion approaches for emotion recognition from speech using acoustic and text-based features

Leonardo Pepino, Pablo Riera, Luciana Ferrer +1

In this paper, we study different approaches for classifying emotions from speech using acoustic and text-based features. We propose to obtain contextualized word embeddings with B…

cs.LG2024

On the Stability of a non-hyperbolic nonlinear map with non-bounded set of non-isolated fixed points with applications to Machine Learning

Roberta Hansen, Matias Vera, Lautaro Estienne +2

This paper deals with the convergence analysis of the SUCPA (Semi Unsupervised Calibration through Prior Adaptation) algorithm, defined from a first-order non-linear difference equ…

cs.CL2023

Mispronunciation detection using self-supervised speech representations

Jazmin Vidal, Pablo Riera, Luciana Ferrer

In recent years, self-supervised learning (SSL) models have produced promising results in a variety of speech-processing tasks, especially in contexts of data scarcity. In this pap…