• Roshan Borse
• Dipali Partale
• Prajwal Bhosale
• Swapanaja Kulkarni
• P.V KULKARNI

One practical requirement of the music copyright management is the estimation of music relative loudness, which is mostly ignored in existing music detection works. To solve this problem, the paper studies the joint task of music detection and music relative loudness estimation. To be specific, it is observed that the joint task has two characteristics, i.e., temporally and hierarchy, which could facilitate to obtain the solution. For example, a tiny fragment of audio is temporally related to its neighbour fragments because they may all belong to the same event, and the event classes of the fragment in the two tasks have a hierarchical relationship. Based on the above observation, we reformulate the joint task as hierarchical event detection and localization problem. To solve this problem, we further propose Hierarchical Regulated Iterative Networks (HRIN), which includes two variants, termed as HRIN-r (recurrent) and HRIN-cr, (convolutional recurrent) which are based on recurrent and convolutional recurrent modules. To enjoy the joint task’s characteristics, our models employ an iterative framework to achieve encouraging capability in temporal modelling while designing three hierarchical violation penalties to regulate hierarchy. Extensive experiments on the currently largest dataset (i.e., OpenBMAT) show that the promising performance of our HRIN in the segment-level and event-level evaluations. Index Terms—music detection, music relative loudness estimation, event detection, event localization, neural networks,

Music Separation, Convolutional Neural Network, Neural Network, Deep Learning, Recurrent Neural Network.

"A survey paper based on “MUSIC & SPEECH SEPARATION”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.d62-d65, November-2022, Available :http://www.jetir.org/papers/JETIR2211309.pdf

"A survey paper based on “MUSIC & SPEECH SEPARATION”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppd62-d65, November-2022, Available at : http://www.jetir.org/papers/JETIR2211309.pdf