Efficient architectures of MDCT/IMDCT implementation for MPEG audio codec
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Parametric dictionary design for sparse coding
IEEE Transactions on Signal Processing
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IEEE Transactions on Audio, Speech, and Language Processing
Adaptive signal modeling based on sparse approximations for scalable parametric audio coding
IEEE Transactions on Audio, Speech, and Language Processing
Pattern Recognition Letters
How sparsely can a signal be approximated while keeping its class identity?
Proceedings of 3rd international workshop on Machine learning and music
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AMR'09 Proceedings of the 7th international conference on Adaptive multimedia retrieval: understanding media and adapting to the user
Auditory-inspired sparse representation of audio signals
Speech Communication
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Signal Processing
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This paper investigates the use of sparse overcomplete decompositions for audio coding. Audio signals are decomposed over a redundant union of modified discrete cosine transform (MDCT) bases having eight different scales. This approach produces a sparser decomposition than the traditional MDCT-based orthogonal transform and allows better coding efficiency at low bitrates. Contrary to state-of-the-art low bitrate coders, which are based on pure parametric or hybrid representations, our approach is able to provide transparency. Moreover, we use a bitplane encoding approach, which provides a fine-grain scalable coder that can seamlessly operate from very low bitrates up to transparency. Objective evaluation, as well as listening tests, show that the performance of our coder is significantly better than a state-of-the-art transform coder at very low bitrates and has similar performance at high bitrates. We provide a link to test soundfiles and source code to allow better evaluation and reproducibility of the results.