Text-and-audio methods

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• Catalina Cangea (Google DeepMind)
• Tuesday 30 January 2024, 13:00-14:00
• Lecture Theatre 2, Computer Laboratory, William Gates Building.

If you have a question about this talk, please contact Mateja Jamnik.

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.

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This talk is part of the Artificial Intelligence Research Group Talks (Computer Laboratory) series.

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