May 2022
We introduce a new source separation dataset, Divide and Remaster (DnR), for training and testing algorithms aiming at separating monaural audio signals into speech, music, and sound effects/background stems.
conference
dataset
source separation
merl
May 2022
We present an interactive music source separation system allowing a user to specify the spatial location of the instruments of interest. We explore various conditioning mechanisms ranging from simple concatenation to positional encoding and AdaIN.
conference
source separation
interactive system
August 2020
Thrilled to announce that our paper entitled "Deep Learning Based Source Separation Applied to Choir Ensembles" has been accepted to the 21st International Society for Music Information Retrieval Conference !
conference
music information retrieval
source separation
October 2021
Our paper entitled "HARP-Net: Hyper-Autoencoded Reconstruction Propagation for Scalable Neural Audio Coding" has been accepted to the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics !
conference
neural audio coding
autoencoder
January 2020
In this second part, we explore network conditioning for source separation tasks, using the sources' fundamental frequency as control input.
conditioned u-net
source separation
film layer
January 2020
Musical source separation for SATB choral recordings, performed in both the waveform and spectral domain.
python
source separation
tensorflow
March 2020
Source count for audio signals via multi-fundamental frequency contour analysis.
python
f0 estimation
tensorflow
January 2016
Fun and creative music making app; with csJam, you can improvise, perform, sequence, and compose with a variety of synthetic and sampled instruments.
csound
iPad app
objective-c
step-sequencer
May 2016
An iPad app exploring different spectral synthesis and processing techniques, such as convolution, morphing and cross synthesis from a practical perspective.
csound
iPad app
objective-c
spectral processing
February 2020
System designed in PureData, which assimilates and learns from musical performances using Markov models.
pure data
performance
markov model
March 2015
iPad app exploiting musical concepts such as question-answer, motifs, and transposition to generate music algorithmically in interaction with its user.
csound
iPad app
objective-c
generative music
March 2015
Various physical model systems using noise as their sole signal source in order to generate various sound effects.
max/msp
noise-based
physical model
September 2015
A simple yet powerful program written in C for algorithmic music generation.