Real-Time Perceptual Moving-Horizon Multiple-Description Audio Coding

A novel scheme for perceptual coding of audio for robust and real-time communication is designed and analyzed. As an alternative to PCM, DPCM, and more general noise-shaping converters, we propose to use psychoacoustically optimized noise-shaping quantizers based on the moving-horizon principle. In moving-horizon quantization, a few samples look-ahead is allowed at the encoder, which makes it possible to better shape the quantization noise and thereby reduce the resulting distortion over what is possible with conventional noise-shaping techniques. It is first shown that significant gains over linear PCM can be obtained without introducing a delay and without requiring postprocessing at the decoder, i.e., the encoded samples can be stored as, e.g., 16-bit linear PCM on CD-ROMs, and played out on standards-compliant CD players. We then show that multiple-description coding can be combined with moving-horizon quantization in order to combat possible erasures on the wireless link without introducing additional delays

Quantization of filter bank frame expansions through moving horizon optimization

This paper describes a novel approach to quantization in oversampled filter banks. The new technique is based on moving horizon optimization, does not rely on an additive white noise quantization model and allows stability to be explicitly enforced in the associated nonlinear feedback loop. Moreover, the quantization structure proposed here includes ΣΔ and linear predictive subband quantizers as a special case and, in general, outperforms them