Abstract: An efficient approach for estimating scalefactors for use in the quantization of audio signal spectrum values is described. The scalefactor estimation approach can be implemented in multiple stages. A first stage estimates a distortion level for a selected scalefactor band spectrum value based on a received maximum tolerant distortion threshold and the spectrum values in the scalefactor band. A second stage determines an interim process value based on the previously estimated distortion level and generates a scalefactor for a selected scalefactor band spectrum value based on the generated interim process value and a statistically predetermined fraction. A third stage generates a scalefactor that applies to the whole scalefactor band based on the scalefactor generated for the selected scalefactor band spectrum value. The approach provides a performance gain of 40% over previous techniques, thereby reducing device power requirements and audio encoder bottlenecks.

Abstract: An advanced audio coding (AAC) encoder quantization architecture is described. The architecture includes an efficient, low computation complexity approach for estimating scalefactors in which a base scalefactor estimate is adjusted by a delta scalefactor estimate that is based, in part, on global scalefactor adjustments applied to the previously quantized/encoded frame. Using such feedback, the AAC encoder quantization architecture is able to produce scalefactor estimates that are very close to the actual scalefactor applied by the subsequent quantization and encoding process. The architecture further includes a frequency hole avoidance approach that reduces a magnitude of an estimated scalefactor to avoid generating frequency holes in quantized SFBs.

Abstract: An efficient approach for estimating scalefactors for use in the quantization of audio signal spectrum values is described. The scalefactor estimation approach can be implemented in multiple stages. A first stage estimates a distortion level for a selected scalefactor band spectrum value based on a received maximum tolerant distortion threshold and the spectrum values in the scalefactor band. A second stage determines an interim process value based on the previously estimated distortion level and generates a scalefactor for a selected scalefactor band spectrum value based on the generated interim process value and a statistically predetermined fraction. A third stage generates a scalefactor that applies to the whole scalefactor band based on the scalefactor generated for the selected scalefactor band spectrum value. The approach provides a performance gain of 40% over previous techniques, thereby reducing device power requirements and audio encoder bottlenecks.

Abstract: An advanced audio coding (AAC) encoder quantization architecture is described. The architecture includes an efficient, low computation complexity approach for estimating scalefactors in which a base scalefactor estimate is adjusted by a delta scalefactor estimate that is based, in part, on global scalefactor adjustments applied to the previously quantized/encoded frame. Using such feedback, the AAC encoder quantization architecture is able to produce scalefactor estimates that are very close to the actual scalefactor applied by the subsequent quantization and encoding process. The architecture further includes a frequency hole avoidance approach that reduces a magnitude of an estimated scalefactor to avoid generating frequency holes in quantized SFBs.