Audio codec using adaptive sparse vector quantization with subband vector classification

Abstract

An audio coder/decoder ("codec") that is suitable for real-time applications due to reduced computational complexity, and a novel adaptive sparse vector quantization (ASVQ) scheme and algorithms for general purpose data quantization. The codec provides low bit-rate compression for music and speech, while being applicable to higher bit-rate audio compression. The codec includes an in-path implementation of psychoacoustic spectral masking, and frequency domain quantization using the novel ASVQ scheme and algorithms specific to audio compression. More particularly, the inventive audio codec employs frequency domain quantization with critically sampled subband filter banks to maintain time domain continuity across frame boundaries. The input audio signal is transformed into the frequency domain in which in-path spectral masking can be directly applied. This in-path spectral masking usually results in sparse vectors. The ASVQ scheme is a vector quantization algorithm that is particularly effective for quantizing sparse signal vectors. In the preferred embodiment, ASVQ adaptively classifies signal vectors into six different types of sparse vector quantization, and performs quantization accordingly. The ASVQ technique applies to general purpose data quantization as well as to quantization in the context of audio compression. The invention also includes a "soft clipping" algorithm in the decoder as a post-processing stage. The soft clipping algorithm preserves the waveform shapes of the reconstructed time domain audio signal in a frame- or block-oriented stateless manner while maintaining continuity across frame or block boundaries. The invention includes related methods, apparatus, and computer programs.