1 citations · 1 across the 4 of their papers we have counts for
5 papers
AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
Giovanni Bindi, Nils Demerlé, Rodrigo Diaz +18
Artificial Intelligence (AI) technologies such as deep learning are evolving very quickly bringing many changes to our everyday lives. To explore the future impact and potential of…
Mesostructures: Beyond Spectrogram Loss in Differentiable Time-Frequency Analysis
Cyrus Vahidi, Han Han, Changhong Wang +3
Computer musicians refer to mesostructures as the intermediate levels of articulation between the microstructure of waveshapes and the macrostructure of musical forms. Examples of…
Differentiable Time-Frequency Scattering on GPU
John Muradeli, Cyrus Vahidi, Changhong Wang +4
Joint time-frequency scattering (JTFS) is a convolutional operator in the time-frequency domain which extracts spectrotemporal modulations at various rates and scales. It offers an…
A Modulation Front-End for Music Audio Tagging
Cyrus Vahidi, Charalampos Saitis, György Fazekas
Convolutional Neural Networks have been extensively explored in the task of automatic music tagging. The problem can be approached by using either engineered time-frequency feature…
Timbre Space Representation of a Subtractive Synthesizer
Cyrus Vahidi, George Fazekas, Charalampos Saitis +1
In this study, we produce a geometrically scaled perceptual timbre space from dissimilarity ratings of subtractive synthesized sounds and correlate the resulting dimensions with a…