Song’s & Non-Song’s Pattern Classification Using Neural Network

Authors

  • Areeza Bhanbhro Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan
  • Abeer Mukhtiar Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan.
  • Muniba Memon Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan.
  • Akhtar Hussain Jalbani Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan.
  • Sunbul Bhangwar Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan.
  • Mohsin Ali Khokhar Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Pakistan.

DOI:

https://doi.org/10.62019/abbdm.v4i1.117

Keywords:

Song (musical or non-musical), Non-song, Pattern Classification, Back-propagation Multi-layer Perceptron Neural Network.

Abstract

The problem of pattern classification between musical or non-musical song audio snippets and non-songs is the main subject of this paper. The machine learning approach accomplishes the goal of automatically interpreting recordings to see if they are songs or not. There are two types of songs: musical and non-musical. This is due to the possibility that it could be difficult to discern between non-musical songs and non-song patterns. Thus, it is necessary to have such systems that differentiate between non-song patterns and songs, whether or not they are melodic. The extraction and selection of characteristics have made advantage of the preprocessing phases. The features that were obtained were pitch, intensity, length (duration), tempo, and sample rate. The Back-propagation Multi-layer Perceptron Neural Network model is used for both dataset testing and model training. This technique will distinguish between a musical or non-musical song and a non-musical piece (such conversation and speech). Training data for the dataset included recordings of speeches and dialogues in Hindi and Urdu for non-song audio files, as well as audio of various male and female singers from Pakistan and India for song audio files in Hindi and Urdu. When the classifier was evaluated using a range of audio samples, 90% of its classifications for songs and non-songs were accurate.

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Published

2024-03-04

How to Cite

Bhanbhro, A., Mukhtiar, A., Memon, M., Jalbani, A. H., Bhangwar, S., & Khokhar , M. A. (2024). Song’s & Non-Song’s Pattern Classification Using Neural Network. The Asian Bulletin of Big Data Management, 4(1). https://doi.org/10.62019/abbdm.v4i1.117