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Found 7 papers, 2 papers with code
Can MusicGen Create Training Data for MIR Tasks?
We are investigating the broader concept of using AI-based generative music systems to generate training data for Music Information Retrieval (MIR) tasks.
EIHW-MTG DiCOVA 2021 Challenge System Report
This paper aims to automatically detect COVID-19 patients by analysing the acoustic information embedded in coughs.
A Deep Learning Based Analysis-Synthesis Framework For Unison Singing
Unison singing is the name given to an ensemble of singers simultaneously singing the same melody and lyrics.
Multiple F0 Estimation in Vocal Ensembles using Convolutional Neural Networks
This paper addresses the extraction of multiple F0 values from polyphonic and a cappella vocal performances using convolutional neural networks (CNNs).
Deep Learning Based Source Separation Applied To Choir Ensembles
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.
A Framework for Multi-f0 Modeling in SATB Choir Recordings
We observe, however, that the scenario of multiple singers for each choir part (i. e. unison singing) is far more challenging.
Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners
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.
