activity
20162022
most citedExplaining Deep Convolutional Neural Networks on Music Classification

32 citations · 45 across the 10 of their papers we have counts for

collaborators
Showing cs.SDShow all

8 papers · 1 filter

cs.SD20223 cited

Rigid-Body Sound Synthesis with Differentiable Modal Resonators

Rodrigo Diaz, Ben Hayes, Charalampos Saitis +2

Physical models of rigid bodies are used for sound synthesis in applications from virtual environments to music production. Traditional methods such as modal synthesis often rely o…

cs.SD2022

Deep Embeddings for Robust User-Based Amateur Vocal Percussion Classification

Alejandro Delgado, Emir Demirel, Vinod Subramanian +2

Vocal Percussion Transcription (VPT) is concerned with the automatic detection and classification of vocal percussion sound events, allowing music creators and producers to sketch…

cs.SD2021

Learning Models for Query by Vocal Percussion: A Comparative Study

Alejandro Delgado, SkoT McDonald, Ning Xu +2

The imitation of percussive sounds via the human voice is a natural and effective tool for communicating rhythmic ideas on the fly. Thus, the automatic retrieval of drum sounds usi…

cs.SD20214 cited

Transfer Learning for Piano Sustain-Pedal Detection

Beici Liang, György Fazekas, Mark Sandler

Detecting piano pedalling techniques in polyphonic music remains a challenging task in music information retrieval. While other piano-related tasks, such as pitch estimation and on…

cs.SD2019

Spectral Visibility Graphs: Application to Similarity of Harmonic Signals

Delia Fano Yela, Dan Stowell, Mark Sandler

Graph theory is emerging as a new source of tools for time series analysis. One promising method is to transform a signal into its visibility graph, a representation which captures…

cs.SD2018

Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation

Delia Fano Yela, Dan Stowell, Mark Sandler

Kernel Additive Modelling (KAM) is a framework for source separation aiming to explicitly model inherent properties of sound sources to help with their identification and separatio…