activity
20142023
most citedWave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation

75 citations · 156 across the 22 of their papers we have counts for

collaborators
Showing 2017Show all

2 papers · 1 filter

cs.LG2017

Adversarial Semi-Supervised Audio Source Separation applied to Singing Voice Extraction

Daniel Stoller, Sebastian Ewert, Simon Dixon

The state of the art in music source separation employs neural networks trained in a supervised fashion on multi-track databases to estimate the sources from a given mixture. With…

cs.AI2017★ 9 cited

Note Value Recognition for Piano Transcription Using Markov Random Fields

Eita Nakamura, Kazuyoshi Yoshii, Simon Dixon

This paper presents a statistical method for use in music transcription that can estimate score times of note onsets and offsets from polyphonic MIDI performance signals. Because p…