Published November 30, 2020 | Version v1
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Singer Identification using Autocorrelation Method

  • 1. PhD student in the Electronics and Communication Engineering Department, Birla Institute of Technology, Deemed University.
  • 2. Professor Electronics and Communication Engineering Department, Birla Institute of Technology, Deemed University.
  • 1. Publisher

Description

songs are the compositions embedding voice and different instrument’s sound. Different human emotions can be created by playing the appropriate song .autocorrelation algorithm is used here to find out singer identification. In the first experiment three singers with three hindi songs (vocal) are taken as data set. Tempo is used as musical features. Then autocorrelation is proposed on concerning a total of three singers. Using bartlett test we have found the most significant autocorrelation values of those songs of three singers. In second experiment three singers with one hindi song (vocal) are taken as data set. Here rms is used as musical features. Then autocorrelation is proposed on concerning those three singers. Using bartlett test we have found the insignificant autocorrelation values of the song of three singers. The first experiment is used to identify the singers for each song. Here three singers identify their own identification test giving most significant values of their songs .the second experiment gives the insignificant value. The insignificance values of musical features of three singers does not give the singer’s identification test.

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Is cited by
Journal article: 2277-3878 (ISSN)

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ISSN
2277-3878
Retrieval Number
100.1/ijrte.C4672099320