Actually, what I really need is less papers with “all you need” in the title – and to share a (non-virtual) beer with you folks!! Here some of the papers I enjoyed, together with the papers we presented. You’ll see that I don’t include classification/tagging papers, I guess I need a break from my PhD topic 🙂 Enjoy!
Continue readingCategory Archives: Deep learning
Slides: Towards building an artistic discourse around music AI
On Thursday 13th May from 17:00 – 19:00 (CET) I’ll be part of the workshop ‘Exploring connections between AI and Music’. The live-streamed event is free to watch, and marks the presentation of the AI and Music Festival and its first activity (more information here). To prepare for it, I reviewed previous works by music AI artists and researchers. This slide deck contains a summary of how I perceive the current music AI scene.
Preprint: Upsampling Artifacts in Neural Audio Synthesis
Upsamplers are a key element for developing computationally efficient and high-fidelity neural audio synthesizers. Given their importance, together with the fact that the audio literature only provides sparse and unorganized insights, our work is aimed at advancing and consolidating our current understanding of neural upsamplers.
Continue readingSESQA: Semi-supervised Learning for Speech Quality Assessment
Can semi-supervised learning help us estimating accurate MOS quality estimates of speech? Yes, and not only that – its heads used for semi-supervised training can also convey relevant information related to the task.
Check our paper!
Continue readingThesis defence.. but as a jury member!
Now that I’m a doctor, I can be called to be part of a jury for helping to evaluate PhD students. Today was my first experience doing that, and it was double special because the other jury member was Axel Roebel — with whom I started my research career.
Thanks to Javier Nistal, Gaël Richard and Steffan Lattner for inviting me!