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Comparative Study of Mfcc and Mel Spectrogram for Raga Classification Using CNN

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Názov: Comparative Study of Mfcc and Mel Spectrogram for Raga Classification Using CNN
Autori: Dipti Joshi, Jyoti Pareek, Pushkar Ambatkar
Informácie o vydavateľovi: Zenodo
Rok vydania: 2023
Zbierka: Zenodo
Predmety: Raga identification, Music Information Retrieval, Feature extraction, Mfcc, Melspectrograms, CNN
Popis: Objectives: To perform a comparative study of the results of feature extraction done using two different methods, Mfcc and Mel spectrogram, and determine which method is more effective for implementing the CNN algorithm. Methods: This study uses the CNN model to classify ragas according to Indian classical music. Feature extraction, which is a major operation in the Music Information Retrieval (MIR) process, is done using Mfcc and Mel spectrogram methods. The major ragas chosen as subjects for feature extraction are Yaman, Bhairav, Bhairavi, Multani, and Dhanashree. Findings: After comparison and examination of results achieved from both techniques, we could conclude that the CNN model using the Mel spectrogram method outperforms the CNN model using Mfcc. Novelty: The majority of the research, we discovered was on Carnatic music. In contrast to earlier research, this research takes a novel approach by conducting experiments on a variety of Hindustani classical ragas which are different from other studies. Researchers interested in music as well as application users would benefit from this study. Our proposed feature extraction approach will be useful for initializing the CNN algorithm, which will help aspiring musicians recognize ragas and classify songs based on these ragas. Keywords: Raga identification; Music Information Retrieval; Feature extraction; Mfcc; Melspectrograms; CNN
Druh dokumentu: article in journal/newspaper
Jazyk: unknown
ISSN: 0974-5645
Relation: https://zenodo.org/records/13309959; oai:zenodo.org:13309959; https://doi.org/10.17485/IJST/v16i11.1809
DOI: 10.17485/IJST/v16i11.1809
Dostupnosť: https://doi.org/10.17485/IJST/v16i11.1809
https://zenodo.org/records/13309959
https://indjst.org/articles/comparative-study-of-mfcc-and-mel-spectrogram-for-raga-classification-using-cnn
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Prístupové číslo: edsbas.94D2DF83
Databáza: BASE
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  – Url: https://doi.org/10.17485/IJST/v16i11.1809#
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comparative Study of Mfcc and Mel Spectrogram for Raga Classification Using CNN
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dipti+Joshi%22">Dipti Joshi</searchLink><br /><searchLink fieldCode="AR" term="%22Jyoti+Pareek%22">Jyoti Pareek</searchLink><br /><searchLink fieldCode="AR" term="%22Pushkar+Ambatkar%22">Pushkar Ambatkar</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: Zenodo
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2023
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Zenodo
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Raga+identification%22">Raga identification</searchLink><br /><searchLink fieldCode="DE" term="%22Music+Information+Retrieval%22">Music Information Retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Mfcc%22">Mfcc</searchLink><br /><searchLink fieldCode="DE" term="%22Melspectrograms%22">Melspectrograms</searchLink><br /><searchLink fieldCode="DE" term="%22CNN%22">CNN</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Objectives: To perform a comparative study of the results of feature extraction done using two different methods, Mfcc and Mel spectrogram, and determine which method is more effective for implementing the CNN algorithm. Methods: This study uses the CNN model to classify ragas according to Indian classical music. Feature extraction, which is a major operation in the Music Information Retrieval (MIR) process, is done using Mfcc and Mel spectrogram methods. The major ragas chosen as subjects for feature extraction are Yaman, Bhairav, Bhairavi, Multani, and Dhanashree. Findings: After comparison and examination of results achieved from both techniques, we could conclude that the CNN model using the Mel spectrogram method outperforms the CNN model using Mfcc. Novelty: The majority of the research, we discovered was on Carnatic music. In contrast to earlier research, this research takes a novel approach by conducting experiments on a variety of Hindustani classical ragas which are different from other studies. Researchers interested in music as well as application users would benefit from this study. Our proposed feature extraction approach will be useful for initializing the CNN algorithm, which will help aspiring musicians recognize ragas and classify songs based on these ragas. Keywords: Raga identification; Music Information Retrieval; Feature extraction; Mfcc; Melspectrograms; CNN
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  Data: article in journal/newspaper
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  Data: 10.17485/IJST/v16i11.1809
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  Data: https://doi.org/10.17485/IJST/v16i11.1809<br />https://zenodo.org/records/13309959<br />https://indjst.org/articles/comparative-study-of-mfcc-and-mel-spectrogram-for-raga-classification-using-cnn
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  Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
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RecordInfo BibRecord:
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        Value: 10.17485/IJST/v16i11.1809
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Raga identification
        Type: general
      – SubjectFull: Music Information Retrieval
        Type: general
      – SubjectFull: Feature extraction
        Type: general
      – SubjectFull: Mfcc
        Type: general
      – SubjectFull: Melspectrograms
        Type: general
      – SubjectFull: CNN
        Type: general
    Titles:
      – TitleFull: Comparative Study of Mfcc and Mel Spectrogram for Raga Classification Using CNN
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          Name:
            NameFull: Dipti Joshi
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          Name:
            NameFull: Jyoti Pareek
      – PersonEntity:
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            NameFull: Pushkar Ambatkar
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              M: 01
              Type: published
              Y: 2023
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