Abstract
With the development and advancement of information technology, artificial intelligence (AI) and machine learning (ML) are applied in every sector of life. Among these applications, music is one of them which has gained attention in the last couple of years. The music industry is revolutionized with AIbased innovative and intelligent techniques. 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. Sounds in the games are very effective and can be made more attractive by implementing AI approaches. The quality of sounds in the game directly impacts the productivity and experience of the player. With computer-assisted technologies, the game designers can create sounds for different scenarios or situations like horror and suspense and provide gamer 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, good quality of knowledge about musicology is essential. Due to AIM, there are a lot of intelligent and interactive tools available for the efficiency and effective learning of music. The 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 become evidence for researchers to devise novel solutions in the field.
Optimizing progressive query-by-example over pre-clustered large image databases