Artificial Intelligence And Music Research Articles

A comprehensive overview of AI-enabled music classification and its influence in games

With the development and advancement of information technology, artificial intelligence (AI) and machine learning are applied in every sector of life. Among these applications, music is one that has gained attention in the last couple of years. AI-based innovative and intelligent techniques are revolutionising the music industry. It is very convenient for composers to compose music of high quality using these technologies. Artificial intelligence and music (AIM) is one of the emerging fields used to generate and manage sounds for different media like the Internet, games, etc. Sound effects in games are very effective and can be made more attractive by implementing AI approaches. The quality of the sounds in the game directly impacts the productivity and experience of the player. With computer-assisted technologies, game designers can create sounds for different scenarios or situations like horror and suspense and provide gamers with information. The practical and productive audio of a game can guide visually impaired people during other events in the game. For the better creation and composition of music, a good quality of knowledge about musicology is essential. Due to AIM, there are a lot of intelligent and interactive tools available for the efficient and effective learning of music. Learners can be provided with a very reliable and interactive environment based on artificial intelligence. The current study has considered presenting a detailed overview of the literature available in the area of research. The study has demonstrated literature analysis from various perspectives, which will provide evidence for researchers to devise novel solutions in the field.

AAAI 2000 Workshop Reports

The AAAI-2000 Workshop Program was held Sunday and Monday, 3031 July 2000 at the Hyatt Regency Austin and the Austin Convention Center in Austin, Texas. The 15 workshops held were (1) Agent-Oriented Information Systems, (2) Artificial Intelligence and Music, (3) Artificial Intelligence and Web Search, (4) Constraints and AI Planning, (5) Integration of AI and OR: Techniques for Combinatorial Optimization, (6) Intelligent Lessons Learned Systems, (7) Knowledge-Based Electronic Markets, (8) Learning from Imbalanced Data Sets, (9) Learning Statistical Models from Rela-tional Data, (10) Leveraging Probability and Uncertainty in Computation, (11) Mobile Robotic Competition and Exhibition, (12) New Research Problems for Machine Learning, (13) Parallel and Distributed Search for Reasoning, (14) Representational Issues for Real-World Planning Systems, and (15) Spatial and Temporal Granularity.

On the role of artificial intelligence in music research

Abstract This paper gives a partial overview of what is currently going on in the emerging field known as Artificial Intelligence and Music (AIM). In particular, it focuses on Artificial Intelligence (AI) research areas which, according to a personal view, can significantly influence current music research. The paper highlights how AIM is not a field in which AI technology is merely applied to music. Both music and the AI field can benefit from studies in this discipline: music is a complex experimental domain which can be particularly useful in the formulation and verification of theories about intelligence. This hypothesis is confirmed by the recent works in this field, and particularly by the papers included in this issue of Journal of New Music Research. This paper attempts to set them against an AI global view. The author focuses on the role of some knowledge representation paradigms, such as logic‐based formalisms and network representations. In particular, the role of time in AI formalisms is discussed. Another important related issue, scarcely considered in music research, regards planning and action theories. Furthermore, he discusses the necessity of integrating different formalisms into hybrid systems, to cope with the different complex problems existing in music activities. He emphasizes the importance of this topic showing, as a case study, some design issues on a particular music knowledge representation system.