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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
Abstract
The paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves smoothing efficiency and allows one to localize noise pulses more accurately, leading to noticeable performance improvements compared to unidirectional processing.
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- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP) strony 5949 - 5953
- Language:
- English
- Publication year:
- 2013
- Bibliographic description:
- Niedźwiecki M., Ciołek M..: RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING, W: Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2013, IEEE,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/icassp.2013.6638806
- Verified by:
- Gdańsk University of Technology
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