António Ramires — accepted AI-conference papers

2021

Loopnet: Musical Loop Synthesis Conditioned on Intuitive Musical Parameters

Pritish Chandna, António Ramires, Xavier Serra, Emilia Gómez

ICASSP 2021accepted

Loops, seamlessly repeatable musical segments, are a cornerstone of modern music production. Contemporary artists often mix and match various sampled or pre-recorded loops based on musical criteria such as rhythm, harmony and timbral texture to create compositions. Taking such criteria into account,…

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2020

Neural Percussive Synthesis Parameterised by High-Level Timbral Features

António Ramires, Pritish Chandna, Xavier Favory, Emilia Gómez, Xavier Serra

ICASSP 2020accepted

We present a deep neural network-based methodology for synthesising percussive sounds with control over high-level timbral characteristics of the sounds. This approach allows for intuitive control of a synthesizer, enabling the user to shape sounds without extensive knowledge of signal processing. W…

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