Dynamic range compression of audio signals consistent with recent time-varying loudness models

Cassidy, Ryan J.

doi:10.1109/icassp.2004.1326801

Cited by 6 publications

(3 citation statements)

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“…(1) is actually a first-order filtering and the coefficient β affects the attack and release times of DRC [6]. Therefore, the design in [3] used two different coefficients (β a & β r ) for attack and release operations respectively so that the attack and release times can be independently controlled. However, this approach introduces SPL measurement error [6].…”

Section: A Level Detectionmentioning

confidence: 99%

“…Recently, several researches have revealed DRC designs for digital hearing aids. A DRC algorithm based on time-varying loudness model of human perception was proposed in [3]. But [3] discussed little about the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

“…A DRC algorithm based on time-varying loudness model of human perception was proposed in [3]. But [3] discussed little about the computational complexity. Another fixed-point implementation of DRC is described in [4], which adopted Taylor's series to approximate nonlinear operations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Complexity-effective dynamic range compression for digital hearing aids

Chang

Kuo

Lin

et al. 2010

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

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Dynamic range compression (DRC) is an essential function in digital hearing aids, which have stringent power consumption constraints. This work minimized the complexity of the DRC algorithm through adopting functional approximation for those involved nonlinear operations. The tradeoff between computation reduction and approximation error was explored for reducing hardware cost without introducing audible artifact. Moreover, finite wordlength analysis is conducted for the wordlength minimization and further complexity saving. The experimental result shows that our design totally reduces 96% computing complexity of the straightforward implementation without introducing audible difference in the output signals. Compared with other approximation methods, our design also requires lower hardware complexity.

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Section: A Level Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%