Abstract
Notation of a music piece is an extremely important resource for musicians. It requires mastery and experience to transcribe a piece accurately which lays the path for automatic music transcription systems to help budding musicians. A piece can be divided into two parts namely the background music (BGM) and lead melody. The BGM is an extremely important aspect of a piece. It is responsible for setting the mood of a composition and at the same time makes it complete. There are different musical instruments which are used in a composition both in the BGM and lead sections one of them being the bass guitar. It bonds with the percussion instruments to form the spinal cord of a piece. It is very much important to transcribe the bass section of a composition for understanding as well as performance. Prior to identification of the notes being played, it is essential to distinguish the different patterns/grooves. In this paper, a system is presented to differentiate bass grooves. Tests were carried out with 60K clips and a best accuracy of 98.46% was obtained.
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Acknowledgment
The authors would like to thank Mr. Pradip Ghosh and Mr. Subho Dey for their help with the musical technicalities and data collection. They also thank WWW.PresentationGO.com for the block diagram template.
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Mukherjee, H., Dhar, A., Obaidullah, S.M., Santosh, K.C., Phadikar, S., Roy, K. (2021). Segregating Bass Grooves from Audio: A Rotation Forest-Based Approach. In: Santosh, K.C., Gawali, B. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2020. Communications in Computer and Information Science, vol 1381. Springer, Singapore. https://doi.org/10.1007/978-981-16-0493-5_32
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DOI: https://doi.org/10.1007/978-981-16-0493-5_32
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