469 citations · 808 across the 29 of their papers we have counts for
34 papers
A study on human-agent teaming through spoken interaction: the impact of human individual traits and agent characteristics
Lara Gauder, Martin Bernardo Meza, Javier Krick +4
Human-agent teams are collaborative systems where humans and agents work interdependently to achieve shared goals. The success of such teams is associated with the human's percepti…
Uncovering shortcut learning in audio classifiers by discovering recurring concepts in temporal explanations
Cecilia Bolaños, Luciana Ferrer, Magdalena Fuentes
Correlations between events in machine learning datasets may result in shortcut learning, where models learn to predict the target event based on the presence of a correlated event…
Unsupervised Approaches for Global Prosodic Embedding Extraction
Martin Meza, Luciana Ferrer, Pablo Riera
Prosody is central to oral communication, conveying information like the emotional state of the speaker and cues needed for meaning disambiguation. Many self-supervised models of s…
Better audio representations are more brain-like: linking model-brain alignment with performance in downstream auditory tasks
Leonardo Pepino, Pablo Riera, Juan Kamienkowski +1
Artificial neural networks are increasingly powerful models of brain computation, yet it remains unclear whether improving their performance in downstream tasks also makes their in…
Benchmarking Time-localized Explanations for Audio Classification Models
Cecilia Bolaños, Leonardo Pepino, Martin Meza +1
Most modern approaches for audio processing are opaque, in the sense that they do not provide an explanation for their decisions. For this reason, various methods have been propose…
Beyond Global Metrics: A Fairness Analysis for Interpretable Voice Disorder Detection Systems
Mariel Estevez, Cyntia Bonomi, Dayana Ribas +2
We conducted a comprehensive analysis of an Automatic Voice Disorders Detection (AVDD) system using existing voice disorder datasets with available demographic metadata. The study…
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…
The Unreliability of Acoustic Systems in Alzheimer's Speech Datasets with Heterogeneous Recording Conditions
Lara Gauder, Pablo Riera, Andrea Slachevsky +3
Automated speech analysis is a thriving approach to detect early markers of Alzheimer's disease (AD). Yet, recording conditions in most AD datasets are heterogeneous, with patients…
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…
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…
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…
EnCodecMAE: Leveraging neural codecs for universal audio representation learning
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 and environmental so…
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…
Deployment of Image Analysis Algorithms under Prevalence Shifts
Patrick Godau, Piotr Kalinowski, Evangelia Christodoulou +5
Domain gaps are among the most relevant roadblocks in the clinical translation of machine learning (ML)-based solutions for medical image analysis. While current research focuses o…
Phone and speaker spatial organization in self-supervised speech representations
Pablo Riera, Manuela Cerdeiro, Leonardo Pepino +1
Self-supervised representations of speech are currently being widely used for a large number of applications. Recently, some efforts have been made in trying to analyze the type of…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Analysis and Comparison of Classification Metrics
Luciana Ferrer
A variety of different performance metrics are commonly used in the machine learning literature for the evaluation of classification systems. Some of the most common ones for measu…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Study on the Fairness of Speaker Verification Systems on Underrepresented Accents in English
Mariel Estevez, Luciana Ferrer
Speaker verification (SV) systems are currently being used to make sensitive decisions like giving access to bank accounts or deciding whether the voice of a suspect coincides with…
A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition
Luciana Ferrer, Diego Castan, Mitchell McLaren +1
Spoken language recognition (SLR) refers to the automatic process used to determine the language present in a speech sample. SLR is an important task in its own right, for example,…
Impact of class imbalance on chest x-ray classifiers: towards better evaluation practices for discrimination and calibration performance
Candelaria Mosquera, Luciana Ferrer, Diego Milone +2
This work aims to analyze standard evaluation practices adopted by the research community when assessing chest x-ray classifiers, particularly focusing on the impact of class imbal…
A transfer learning based approach for pronunciation scoring
Marcelo Sancinetti, Jazmin Vidal, Cyntia Bonomi +1
Phone-level pronunciation scoring is a challenging task, with performance far from that of human annotators. Standard systems generate a score for each phone in a phrase using mode…
Study of positional encoding approaches for Audio Spectrogram Transformers
Leonardo Pepino, Pablo Riera, Luciana Ferrer
Transformers have revolutionized the world of deep learning, specially in the field of natural language processing. Recently, the Audio Spectrogram Transformer (AST) was proposed f…
Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings
Leonardo Pepino, Pablo Riera, Luciana Ferrer
Emotion recognition datasets are relatively small, making the use of the more sophisticated deep learning approaches challenging. In this work, we propose a transfer learning metho…