Prof. Gerald Schuller will report on the potential transformative role of perceptual loss functions and distance metrics in enhancing audio and acoustic machine learning models, and their applications. He will cover theoretical foundations of perceptual loss functions, which mimic human auditory perception, and also more abstract, higher-level representations, and explore how these functions, along with novel distance metrics, significantly improve the performance of audio processing tasks. Applications involving loss functions for room impulse responses, audio similarity, and audio representations for cochlear implants will be discussed.

Prof. Marina Bosi will be hosting his visit.

Join us in Zoom if you cannot make it in person!