10 citations · 18 across the 9 of their papers we have counts for
6 papers · 1 filter
Towards Training Music Taggers on Synthetic Data
Nadine Kroher, Steven Manangu, Aggelos Pikrakis
Most contemporary music tagging systems rely on large volumes of annotated data. As an alternative, we investigate the extent to which synthetically generated music excerpts can im…
Can MusicGen Create Training Data for MIR Tasks?
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. To kick off this line of…
Improving Post-Processing of Audio Event Detectors Using Reinforcement Learning
Petros Giannakopoulos, Aggelos Pikrakis, Yannis Cotronis
We apply post-processing to the class probability distribution outputs of audio event classification models and employ reinforcement learning to jointly discover the optimal parame…
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments
Petros Giannakopoulos, Aggelos Pikrakis, Yannis Cotronis
In this work we apply deep reinforcement learning to the problems of navigating a three-dimensional environment and inferring the locations of human speaker audio sources within, i…
A Deep Reinforcement Learning Approach to Audio-Based Navigation in a Multi-Speaker Environment
Petros Giannakopoulos, Aggelos Pikrakis, Yannis Cotronis
In this work we use deep reinforcement learning to create an autonomous agent that can navigate in a two-dimensional space using only raw auditory sensory information from the envi…
Exploratory Analysis of a Large Flamenco Corpus using an Ensemble of Convolutional Neural Networks as a Structural Annotation Backend
Nadine Kroher, Aggelos Pikrakis
We present computational tools that we developed for the analysis of a large corpus of flamenco music recordings, along with the related exploratory findings. The proposed computat…