Artificial Musical Intelligence: A Survey
–arXiv.org Artificial Intelligence
Computers have been used to analyze and create music since they were first introduced in the 1950s and 1960s. Beginning in the late 1990s, the rise of the Internet and large scale platforms for music recommendation and retrieval have made music an increasingly prevalent domain of machine learning and artificial intelligence research. While still nascent, several different approaches have been employed to tackle what may broadly be referred to as "musical intelligence." 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, with a particular emphasis on machine learning methods.
arXiv.org Artificial Intelligence
Jun-17-2020
- Country:
- North America > United States
- Maryland > Baltimore (0.04)
- Indiana (0.04)
- Washington > King County
- Seattle (0.04)
- Texas > Travis County
- Austin (0.14)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- California > San Mateo County
- Menlo Park (0.04)
- Europe
- United Kingdom
- Wales (0.04)
- England > Oxfordshire
- Oxford (0.04)
- Netherlands
- South Holland > The Hague (0.04)
- North Holland > Amsterdam (0.04)
- United Kingdom
- Asia > Middle East
- Jordan (0.04)
- North America > United States
- Genre:
- Research Report (1.00)
- Overview (1.00)
- Industry:
- Media > Music (1.00)
- Leisure & Entertainment (1.00)
- Education (0.93)
- Health & Medicine (0.92)
- Technology:
- Information Technology > Artificial Intelligence
- Cognitive Science > Problem Solving (1.00)
- Representation & Reasoning
- Uncertainty (1.00)
- Personal Assistant Systems (1.00)
- Agents (1.00)
- Machine Learning
- Neural Networks > Deep Learning (1.00)
- Reinforcement Learning (0.93)
- Evolutionary Systems (0.92)
- Statistical Learning > Support Vector Machines (0.68)
- Performance Analysis > Accuracy (0.67)
- Learning Graphical Models
- Undirected Networks > Markov Models (1.00)
- Directed Networks > Bayesian Learning (1.00)
- Information Technology > Artificial Intelligence