This paper is devoted to the development of a scalable parametric audio coder based on a matching pursuit algorithm with a frame-based psychoacoustic optimized wavelet packet dictionary. The main idea is to parameterize audio signal with a minimum number of non-negative elements. This can be done by applying sparse approximation such as matching pursuit algorithm. In contrast with current approaches in audio coding based on sparse approximation we introduce a model of dynamic dictionary forming for each frame of input audio signal individually based on wavelet packet decomposition and dynamic wavelet packet tree transformation with psychoacoustic model. Experimental results of developed encoder and comparison with modern popular audio encoders are provided.
Authors:
Petrovsky, Alexey; Herasimovich, Vadzim; Petrovsky, Alexander
Affiliation:
Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus
AES Convention:
138 (May 2015)
Paper Number:
9264
Publication Date:
May 6, 2015
Subject:
Audio Signal Processing
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.