Speaker: Giuliano Lazzara. Abstract: Brief that focuses on people’s perception of Conversational Agents and proposes these technologies as a tool to deal with underestimated mental issues such as depression and anxiety. Referring to experiments done with “Woebot”, an automated conversational… Read More
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
Speaker: Sergio Segovia. Abstract: The core idea is to predict latent representations of the full input data based on a masked view of the input in a self-distillation setup using a standard Transformer architecture. Instead of predicting modality-specific targets such… Read More
Data Augmentation for Decoupled Calibration of Deep Neural Network Classifiers
Speaker: Sergio Márquez Carrero. Abstract: Modern Deep Neural Networks (DNN) have significantly outperformed those employed over a decade ago in terms of accuracy. Nonetheless, the outputs generated by these models are poorly calibrated, causing substantial issues in a variety of… Read More
Connectionist Temporal Classification (CTC) Speech Segmentation
Speaker: W. Fernando López Gavilanez. Abstract: Motivated by the lack of high-quality labeled data for specific scenarios, such as emergencies in the home environment, we explored a CTC-segmentation method to generate a specific-purpose speech dataset. The project seeks the quality improvement of… Read More