Low bit-rate universal audio coder

摘要

A biologically-inspired process for universal audio coding based on neural spikes is presented. The process is based on the generation of sparse two-dimensional time-frequency representations of audio signals, called spikegrams. The spikegrams are generated by projecting the audio signal onto a set of over-complete adaptive gamma-chirp kernels. A masking model is applied to the spikegrams to remove inaudible spikes and to increase the coding efficiency. In respect of one aspect of the invention, the masked spikegram is then quantized using a genetic-algorithm-based quantizer (or its simplified linear version). The values are then differentially coded using graph based optimization and entropy coded afterwards.