A joint encoder-decoder framework for supporting energy efficient audio decoding
In comparison with the relatively slow progress of battery technology, semiconductor memory has improved much more rapidly, making storage a less critical limiting factor in designing low power embedded systems such as PDAs. To exploit such technology trends, we present a novel framework, a joint encoder-decoder framework (JEDF), which allows the decoder to tradeoff energy and memory consumption without sacrificing playback quality. We employ sum-of-powers-of-two (SOPOT) technique, an approximate signal processing (ASP) technique, in an MPEG AAC decoder to reduce the computational workload. The SOPOT introduces additional ASP noise (in the decoder) on top of the quantization noise introduced in the process of lossy compression (in the encoder). The sum of these two kinds of noise may become audible when it exceeds the masking threshold. We tackle this problem from a new perspective: the proposed JEDF allows the ASP and quantization noises to be shaped jointly to match the masking threshold. In the case that the perceptual room between the masking threshold and the quantization noise is insufficient for the ASP noise, the JEDF can reduce the quantization noise level which results in an increase in bitrate. To implement the proposed scheme, we have developed two new techniques: (1) SOPOT truncation noise shaping; (2) truncation noise allocation based on a perceptual model. Experimental results show the effectiveness of our approach.
energy efficiency joint encoder-decoder framework (jedf) sopot workload reduction joint asp and quantization noise shaping