no code implementations • 15 Nov 2023 • Nadine Kroher, Helena Cuesta, Aggelos Pikrakis
We are investigating the broader concept of using AI-based generative music systems to generate training data for Music Information Retrieval (MIR) tasks.
no code implementations • 13 Oct 2021 • Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller
This paper aims to automatically detect COVID-19 patients by analysing the acoustic information embedded in coughs.
1 code implementation • 21 Sep 2020 • Pritish Chandna, Helena Cuesta, Emilia Gómez
Unison singing is the name given to an ensemble of singers simultaneously singing the same melody and lyrics.
1 code implementation • 9 Sep 2020 • Helena Cuesta, Brian McFee, Emilia Gómez
This paper addresses the extraction of multiple F0 values from polyphonic and a cappella vocal performances using convolutional neural networks (CNNs).
no code implementations • 17 Aug 2020 • Darius Petermann, Pritish Chandna, Helena Cuesta, Jordi Bonada, Emilia Gomez
However, most of the research has been focused on a typical case which consists in separating vocal, percussion and bass sources from a mixture, each of which has a distinct spectral structure.
no code implementations • 10 Apr 2019 • Helena Cuesta, Emilia Gómez, Pritish Chandna
We observe, however, that the scenario of multiple singers for each choir part (i. e. unison singing) is far more challenging.
no code implementations • 9 Jul 2018 • Emilia Gómez, Merlijn Blaauw, Jordi Bonada, Pritish Chandna, Helena Cuesta
This paper summarizes some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques.