Despite significant advances in deep models for music generation, the us...
We present SingSong, a system that generates instrumental music to accom...
Machine learning approaches now achieve impressive generation capabiliti...
The development of generative Machine Learning (ML) models in creative
p...
Deep learning models are mostly used in an offline inference fashion.
Ho...
What audio embedding approach generalizes best to a wide range of downst...
Deep generative models applied to audio have improved by a large margin ...
A key aspect of machine learning models lies in their ability to learn
e...
In recent years, the deep learning community has largely focused on the
...
Modern approaches to sound synthesis using deep neural networks are hard...
Creativity is a deeply debated topic, as this concept is arguably
quinte...
Granular sound synthesis is a popular audio generation technique based o...
Recent studies show the ability of unsupervised models to learn invertib...
Current state-of-the-art results in Music Information Retrieval are larg...
Deep learning models have provided extremely successful solutions in mos...
Timbre is a set of perceptual attributes that identifies different types...
Extraction of symbolic information from signals is an active field of
re...
Recent researches on Automatic Chord Extraction (ACE) have focused on th...
This paper studies the prediction of chord progressions for jazz music b...
In this work, we introduce a system for real-time generation of drum sou...
The ubiquity of sound synthesizers has reshaped music production and eve...
Generative models have thrived in computer vision, enabling unprecedente...
This article introduces the Projective Orchestral Database (POD), a
coll...
Generative models have been successfully applied to image style transfer...
Timbre spaces have been used in music perception to study the perceptual...
Timbre spaces have been used in music perception to study the relationsh...