Allabakash Tamboli
@sggs.ac.in
SGGS INSTITUTE OF ENGINEERING AND TECHNOLOGY VISHNUPURI NANDED, ASSOCIATE PROFESSOR
SGGS Institute of Engineering and Technology
EDUCATION
Ph.D. in Electronics and Telecommunication Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Allabakash Isak Tamboli and Rajendra D. Kokate
Springer Science and Business Media LLC
Allabakash Isak Tamboli and Rajendra D. Kokate
Walter de Gruyter GmbH
Abstract Musical pitch estimation is used to recognize the musical note pitch or the fundamental frequency (F 0) of an audio signal, which can be applied to a preprocessing part of many applications, such as sound separation and musical note transcription. In this work, a method for musical note recognition based on the classification framework has been designed using an optimization-based neural network (OBNN). A broad range of survey and research was reviewed, and all revealed the methods to recognize the musical notes. An OBNN is used here in recognizing musical notes. Similarly, we can progress the effectiveness of musical note recognition using different methodologies. In this document, the most modern investigations related to musical note recognition are effectively analyzed and put in a nutshell to effectively furnish the traits and classifications.