1 citations · 2 across the 3 of their papers we have counts for
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MAJEPPA: Morphing and Assessing in a Unified Piano Performance Space
Jinwen Zhou, Huan Zhang, Weixi Zhai +3
We present MAJEPPA, a self-supervised framework to learn piano performance representations that span the full skill spectrum, from beginner practice sessions to virtuoso concert re…
Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification
Simon W. McKnight, Aidan O. T. Hogg, Vincent W. Neo +1
This paper studies modulation spectrum features () and mel-frequency cepstral coefficients () in joint speaker diarization and identification (JSID). JSID is important as spe…
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
Aidan O. T. Hogg, Mads Jenkins, He Liu +3
An individualised head-related transfer function (HRTF) is very important for creating realistic virtual reality (VR) and augmented reality (AR) environments. However, acoustically…