activity
20152022
most citedAutomatic tagging using deep convolutional neural networks

224 citations · 650 across the 25 of their papers we have counts for

collaborators

28 papers

cs.SD2022★ 3 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★ 12 cited

DDX7: Differentiable FM Synthesis of Musical Instrument Sounds

Franco Caspe, Andrew McPherson, Mark Sandler

FM Synthesis is a well-known algorithm used to generate complex timbre from a compact set of design primitives. Typically featuring a MIDI interface, it is usually impractical to c…

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.SD2021★ 4 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…

eess.AS2020★ 3 cited

A New Dataset for Amateur Vocal Percussion Analysis

Alejandro Delgado, SKoT McDonald, Ning Xu +1

The imitation of percussive instruments via the human voice is a natural way for us to communicate rhythmic ideas and, for this reason, it attracts the interest of music makers. Sp…