Text-and-audio methods

Abstract

This talk supports the R255 Advanced Topics in Machine Learning course module on Multimodal Learning and provides a bird’s eye view of the rapidly evolving text-audio landscape, with a focus on music as a primary example of audio data. I will first present types of tasks that exist in this space, then discuss data curation challenges and follow with an overview of some existing retrieval and generation methods, including a quick primer on diffusion models. Finally, I will describe current evaluation metrics and their limitations.

Dr Cătălina Cangea

Quantitative Researcher

Quantitative researcher with 9 years of ML experience, most recently co-lead of Generative Music at Google DeepMind, with a PhD from the University of Cambridge, and inhaler of music :) Motivated by contributing ML-based knowledge and improvements to real-world systems!