Speaker: Beltrán Labrador Serrano. Abstract: Based on https://arxiv.org/abs/2110.06500. In this talk we will comment the paper Differentially Private Fine-Tuning for Language Models, where the authors give simpler, sparser, and faster algorithms for differentially private fine-tuning of large-scale pre-trained language models,… Read More
Conformer Architecture for Sound Event Detection (DCASE)
Speaker: Sara Barahona Quirós. Abstract: Sound Event Detection is the task that is focused on automatizing the human’s ability of recognizing sound events in the environment. Over the last years, the creation of evaluations such as the Detection and Classification… Read More
MixMatch: A Holistic Approach to Semi-Supervised Learning
Speaker: Diego de Benito Gorrón. Abstract: This talk is an overview of a NIPS 2019 paper by David Berthelot et al. (Google Research) that proposes a novel method for Semi-supervised learning: MixMatch. “Semi-supervised learning has proven to be a powerful… Read More
Highly accurate protein structure prediction with AlphaFold
Speaker: Juan Ignacio Álvarez Trejos. Abstract: Based on https://www.nature.com/articles/s41586-021-03819-2. Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been… Read More
Whisper: Robust Speech Recognition via Large-Scale Weak Supervision
Speaker: Doroteo Torre Toledano. Abstract: Very recently (in Sept 2022) OpenAI has made freely available a speech recognition neural network called Whisper. One of the main differences with respect to the current state of the art is the use of… Read More
Dynamic Bayesian Networks for Temporal Prediction of Chemical Radioisotope Levels in Nuclear Power Plant Reactors
Speaker: Daniel Ramos Castro. Abstract: Radiation dose in nuclear power plant reactors is known to be dominated by the presence of radioisotopes in the primary loop of the reactor. In order to strictly control it in normal operation (e.g., cleaning… Read More
Automatic adventitious respiratory sound analysis: A systematic review
Speaker: Miguel Ángel Martínez Pay. Abstract: Based on https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177926. Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease, and pneumonia. This article contains a compilation… Read More
Training Speaker Recognition Systems with Limited Data
Speaker: Guillermo Recio. Abstract: Based on paper https://www.isca-speech.org/archive/pdfs/interspeech_2022/vaessen22_interspeech.pdf. This work considers training neural networks for speaker recognition with smaller datasets compared to contemporary work. For this purpose, they propose three subsets of the VoxCeleb2 dataset. Each of these subsets contains… Read More
Exploring sequence-to-sequence transformer-transducer models for keyword spotting
Speaker: Beltrán Labrador Serrano. Abstract: Beltrán’s final Google research internship presentation. This presentation introduces a transformer-transducer keyword spotting system that simultaneously optimizes ASR and keyword spotting losses using a sequence to sequence RNN-T loss. Each loss is further balanced using… Read More
Perceiver: General Perception with Iterative Attention
Speaker: Juan Ignacio Álvarez Trejos. Abstract: Biological systems perceive the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc. The perception models used in deep learning on the other hand are designed for… Read More