Abstract
Pitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation with audio front end used for extraction of instantaneous frequency and power of signal components. A thorough results analysis is performed and major advantages and shortcomings of this method are identified, leading to a wide array of suggestions for future improvement While IFE exhibits an instantaneous temporal resolution, a comparison is made against state-of-the-art pitch estimators operating on time windows, proving a comparable degree of prediction accuracy (up to 6% accuracy improvement) while maintaining the advantage of higher temporal resolution.
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/HSI52170.2021.9538713
- License
- Copyright (2021 IEEE)
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Blok M., Banaś J., Pietrołaj M.: IFE: NN-aided Instantaneous Pitch Estimation// / : , 2021,
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/hsi52170.2021.9538713
- Sources of funding:
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- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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