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 !
In this second part, we explore network conditioning for source separation tasks, using the sources' fundamental frequency as control input.
Musical source separation for SATB choral recordings, performed in both the waveform and spectral domain.
Source count for audio signals via multi-fundamental frequency contour analysis.
Extending the concept of audio mosaicing to a multi-band approach.
An iPad app exploring different spectral synthesis and processing techniques, such as convolution, morphing and cross synthesis from a practical perspective.
Fun and creative music making app; with csJam, you can improvise, perform, sequence, and compose with a variety of synthetic and sampled instruments.
iPad app exploiting musical concepts such as question-answer, motifs, and transposition to generate music algorithmically in interaction with its user.
System designed in PureData, which assimilates and learns from musical performances using Markov models.
A simple yet powerful program written in C for algorithmic music generation.
Various physical model systems using noise as their sole signal source in order to generate various sound effects.