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A Survey on Deep Reinforcement Learning for Audio-Based Applications

arXiv 2101.00240 ↗First posted 1 Jan 2021cs.SD cs.LG eess.AScited by 17

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Abstract (arXiv)

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. 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 application in the real world. In this article, we conduct a comprehensive survey on the progress of DRL in the audio domain by bringing together the research studies across different speech and music-related areas. 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 challenges faced by audio-based DRL agents and highlighting open areas for future research and investigation.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 160 of its 300 references that are in the map. First posted on arXiv 1 Jan 2021.

Builds on

160 of 300 references.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 4; 2024: 5; 2025: 2; 2026: 1.

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  1. 2023Transformers in Speech Processing: A Surveycited by 38
  2. 2024MusicRL: Aligning Music Generation to Human Preferencescited by 32
  3. 2021Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminabilitycited by 19
  4. 2024xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memoriescited by 18
  5. 2023Transformers in Reinforcement Learning: A Surveycited by 11
  6. 2024Diversity-Rewarded CFG Distillationcited by 9
  7. 2022Semi-supervised cross-lingual speech emotion recognitioncited by 3
  8. 2025Automated Detection of Sport Highlights from Audio and Video Sourcescited by 3
  9. 2023FLASH-RL: Federated Learning Addressing System and Static Heterogeneity using Reinforcement Learningcited by 2
  10. 2024Audio-Driven Reinforcement Learning for Head-Orientation in Naturalistic Environmentscited by 2
  11. 2021Hierarchical RNNs-Based Transformers MADDPG for Mixed Cooperative-Competitive Environmentscited by 1
  12. 2025A Synergistic Framework of Nonlinear Acoustic Computing and Reinforcement Learning for Real-World Human-Robot Interactioncited by 1
5 more
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  4. 2024RLEEGNet: Integrating Brain-Computer Interfaces with Adaptive AI for Intuitive Responsiveness and High-Accuracy Motor Imagery Classificationcited by 0
  5. 2026Fast and Highly Expressive Policy Learning for Offline Reinforcement Learning via Bootstrapped Flow Q-Learningcited by 0