Unsupervised pre-training for learning speech representations: Wav2Vec and Wav2Vec2.0

Speaker: Laura Herrera Abstract: These papers (https://arxiv.org/pdf/1904.05862.pdf and https://arxiv.org/pdf/2006.11477.pdf) explore unsupervised learning from raw audio for speech recognition.A large amount of labelled data is not always available, consequently wav2vec uses a causal convolutional network trained with large amounts of unlabelled… Read More

Alicia Lozano Díez returns to UAM as Assistant Professor after almost two years in the prestigious research group Speech@FIT (Brno University of Technology, Czech Republic)

Alicia has made a postdoctoral research stay funded by the European Union under program H2020 Marie Slodowska-Curie Individual Fellowship. The project “Robust End-To-End SPEAKER recognition based on deep learning and attention models” (ETE SPEAKER, 843627) she has developed between 2019… Read More