An Effective Optimization-Based Neural Network for Musical Note Recognition

Musical pitch estimation is used to recognize the musical note pitch or the fundamental frequency (F0) 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 b...

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Main Authors: Tamboli Allabakash Isak, Kokate Rajendra D.
Format: Article
Language:English
Published: De Gruyter 2019-01-01
Series:Journal of Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1515/jisys-2017-0038
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spelling doaj-eab3ede618014993b3ef98ea81e1d2222021-09-06T19:40:37ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2019-01-0128117318310.1515/jisys-2017-0038An Effective Optimization-Based Neural Network for Musical Note RecognitionTamboli Allabakash Isak0Kokate Rajendra D.1Department of Electronics and Telecommunication, SGGSIE and T, Nanded, Maharshtra, IndiaDepartment of Instrumentation Engineering, Government College of Engineering, Jalgaon, Maharshtra, IndiaMusical pitch estimation is used to recognize the musical note pitch or the fundamental frequency (F0) 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.https://doi.org/10.1515/jisys-2017-0038audio signalneural networkmusical notesoptimization
collection DOAJ
language English
format Article
sources DOAJ
author Tamboli Allabakash Isak
Kokate Rajendra D.
spellingShingle Tamboli Allabakash Isak
Kokate Rajendra D.
An Effective Optimization-Based Neural Network for Musical Note Recognition
Journal of Intelligent Systems
audio signal
neural network
musical notes
optimization
author_facet Tamboli Allabakash Isak
Kokate Rajendra D.
author_sort Tamboli Allabakash Isak
title An Effective Optimization-Based Neural Network for Musical Note Recognition
title_short An Effective Optimization-Based Neural Network for Musical Note Recognition
title_full An Effective Optimization-Based Neural Network for Musical Note Recognition
title_fullStr An Effective Optimization-Based Neural Network for Musical Note Recognition
title_full_unstemmed An Effective Optimization-Based Neural Network for Musical Note Recognition
title_sort effective optimization-based neural network for musical note recognition
publisher De Gruyter
series Journal of Intelligent Systems
issn 0334-1860
2191-026X
publishDate 2019-01-01
description Musical pitch estimation is used to recognize the musical note pitch or the fundamental frequency (F0) 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.
topic audio signal
neural network
musical notes
optimization
url https://doi.org/10.1515/jisys-2017-0038
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