A survey on deep reinforcement learning for audio‑based applications

Latif, Siddique, Cuayahuitl, Heriberto, Pervez, Farrukh , Shamshad, Fahad, Shehbaz Ali, Hafiz and Cambria, Erik (2022) A survey on deep reinforcement learning for audio‑based applications. Artifcial Intelligence Review . ISSN 0269-2821

Full content URL: https://doi.org/10.1007/s10462-022-10224-2

Documents
A survey on deep reinforcement learning for audio‑based applications
Published Open Access manuscript
[img]
[Download]
[img]
Preview
PDF
Latif2022_Article_ASurveyOnDeepReinforcementLear.pdf - Whole Document
Available under License Creative Commons Attribution 4.0 International.

2MB
Item Type:Article
Item Status:Live Archive

Abstract

Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence (AI) by endowing autonomous systems with high levels of understanding of the real world. Currently, deep learning (DL) is enabling DRL to effectively solve various intractable problems in various fields including computer vision, natural language processing, healthcare, robotics, to name a few. Most importantly, DRL algorithms are also being employed in audio signal processing to learn directly from speech, music and other sound signals in order to create audio-based autonomous systems that have many promising applications in the real world. In this article, we conduct a comprehensive survey on the progress of DRL in the audio domain by bringing together research studies across different but related areas in speech and music. We begin with an introduction to the general field of DL and reinforcement learning (RL), then progress to the main DRL methods and their applications in the audio domain. We conclude by presenting important challenges faced by audio-based DRL agents and by highlighting open areas for future research and investigation. The findings of this paper will guide researchers interested in DRL for the audio domain.

Keywords:Deep learning, Reinforcement learning, Speech recognition
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G710 Speech and Natural Language Processing
Divisions:College of Science > School of Computer Science
ID Code:50054
Deposited On:11 Jul 2022 10:48

Repository Staff Only: item control page