AI-Based Affective Music Generation Systems: A Review of Methods, and
Challenges
- URL: http://arxiv.org/abs/2301.06890v1
- Date: Tue, 10 Jan 2023 11:08:39 GMT
- Title: AI-Based Affective Music Generation Systems: A Review of Methods, and
Challenges
- Authors: Adyasha Dash, Kat R. Agres
- Abstract summary: Artificial intelligence-based approaches have become popular for creating affective music generation systems.
Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation systems may have a significant impact.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Music is a powerful medium for altering the emotional state of the listener.
In recent years, with significant advancement in computing capabilities,
artificial intelligence-based (AI-based) approaches have become popular for
creating affective music generation (AMG) systems that are empowered with the
ability to generate affective music. Entertainment, healthcare, and
sensor-integrated interactive system design are a few of the areas in which
AI-based affective music generation (AI-AMG) systems may have a significant
impact. Given the surge of interest in this topic, this article aims to provide
a comprehensive review of AI-AMG systems. The main building blocks of an AI-AMG
system are discussed, and existing systems are formally categorized based on
the core algorithm used for music generation. In addition, this article
discusses the main musical features employed to compose affective music, along
with the respective AI-based approaches used for tailoring them. Lastly, the
main challenges and open questions in this field, as well as their potential
solutions, are presented to guide future research. We hope that this review
will be useful for readers seeking to understand the state-of-the-art in AI-AMG
systems, and gain an overview of the methods used for developing them, thereby
helping them explore this field in the future.
Related papers
- Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G [58.440115433585824]
Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces.
While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks.
This paper revisits the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems.
arXiv Detail & Related papers (2024-04-29T04:51:05Z) - Position Paper: Agent AI Towards a Holistic Intelligence [53.35971598180146]
We emphasize developing Agent AI -- an embodied system that integrates large foundation models into agent actions.
In this paper, we propose a novel large action model to achieve embodied intelligent behavior, the Agent Foundation Model.
arXiv Detail & Related papers (2024-02-28T16:09:56Z) - Computational Copyright: Towards A Royalty Model for Music Generative AI [8.131016672512835]
generative AI has given rise to pressing copyright challenges, especially within the music industry.
This paper focuses on the economic aspects of these challenges, emphasizing that the economic impact constitutes a central issue in the copyright arena.
We propose viable royalty models for revenue sharing on AI music generation platforms.
arXiv Detail & Related papers (2023-12-11T18:57:20Z) - Generative AI [20.57872238271025]
"generative AI" refers to computational techniques that are capable of generating seemingly new, meaningful content.
The widespread diffusion of this technology with examples such as Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work and communicate with each other.
arXiv Detail & Related papers (2023-09-13T08:21:59Z) - Selected Trends in Artificial Intelligence for Space Applications [69.3474006357492]
This chapter focuses on differentiable intelligence and on-board machine learning.
We discuss a few selected projects originating from the European Space Agency's (ESA) Advanced Concepts Team (ACT)
arXiv Detail & Related papers (2022-12-10T07:49:50Z) - The Role of AI in Drug Discovery: Challenges, Opportunities, and
Strategies [97.5153823429076]
The benefits, challenges and drawbacks of AI in this field are reviewed.
The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods are also discussed.
arXiv Detail & Related papers (2022-12-08T23:23:39Z) - A Survey on Artificial Intelligence for Music Generation: Agents,
Domains and Perspectives [10.349825060515181]
We describe how humans compose music and how new AI systems could imitate such process.
To understand how AI models and algorithms generate music, we explore, analyze and describe the agents that take part of the music generation process.
arXiv Detail & Related papers (2022-10-25T11:54:30Z) - Software Engineering for AI-Based Systems: A Survey [8.550158373713906]
There is limited synthesized knowledge on Software Engineering approaches for building, operating, and maintaining AI-based systems.
SE for AI-based systems is an emerging research area, where more than 2/3 of the studies have been published since 2018.
The most studied properties of AI-based systems are dependability and safety.
arXiv Detail & Related papers (2021-05-05T11:22:08Z) - Towards an Interface Description Template for AI-enabled Systems [77.34726150561087]
Reuse is a common system architecture approach that seeks to instantiate a system architecture with existing components.
There is currently no framework that guides the selection of necessary information to assess their portability to operate in a system different than the one for which the component was originally purposed.
We present ongoing work on establishing an interface description template that captures the main information of an AI-enabled component.
arXiv Detail & Related papers (2020-07-13T20:30:26Z) - Artificial Musical Intelligence: A Survey [51.477064918121336]
Music has become an increasingly prevalent domain of machine learning and artificial intelligence research.
This article provides a definition of musical intelligence, introduces a taxonomy of its constituent components, and surveys the wide range of AI methods that can be, and have been, brought to bear in its pursuit.
arXiv Detail & Related papers (2020-06-17T04:46:32Z) - Bias in Data-driven AI Systems -- An Introductory Survey [37.34717604783343]
This survey focuses on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful Machine Learning (ML) algorithms.
If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features like race, sex, etc.
arXiv Detail & Related papers (2020-01-14T09:39:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.