1 citations · 1 across the 2 of their papers we have counts for
3 papers
eess.AS2026
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…
eess.AS2023★ 1 cited
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…
eess.AS2023
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…