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Found 6 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.
Improving Post-Processing of Audio Event Detectors Using Reinforcement Learning
We apply post-processing to the class probability distribution outputs of audio event classification models and employ reinforcement learning to jointly discover the optimal parameters for various stages of a post-processing stack, such as the classification thresholds and the kernel sizes of median filtering algorithms used to smooth out model predictions.
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments
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, in the case where the only available information is the raw sound from the environment, as a simulated human listener placed in the environment would hear it.
A Deep Reinforcement Learning Approach to Audio-Based Navigation in a Multi-Speaker Environment
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 environment, a problem that has received very little attention in the reinforcement learning literature.
Online Co-movement Pattern Prediction in Mobility Data
In more detail, we split the original problem into two sub-problems, namely Future Location Prediction and Evolving Cluster Detection.
