Audio Encoding and Decoding Using Conditional Quantizers

Abstract

Some methods can involve frames that encoded audio data including transformation coefficient data.The transformation coefficient data can include index data and tail number data.The tail number data may include the coded tail value of the boundary between the boundary between the uniform or uneven quantitative interval.At least part of the index profile data can be reconstructed to reconstruct the tail value.Based on index profile data, statistical data on pre -quantified tail values can be inferred.Index profile data can include index differential data.Some such index differential data can be pairs, but in the alternative method, you can estimate more than two index differential data points.In each frequency segment, the tail numerical reconstruction can depend on the index differential data, for example, depending on the index difference.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to U.S. Provisional Patent Application No. 61 / 638,090, filed April 25, 2012, and U.S. Utility Patent Application No. 13 / 560,144, filed July 27, 2012, the entire contents of which applications are hereby incorporated by reference incorporated. technical field [0003] The present disclosure relates to encoding an audio signal or decoding an encoded audio signal. In particular, the present disclosure relates to quantization and inverse quantization processes. Background technique [0004] Advances in digital encoding and decoding processes for audio and video data continue to have a significant impact on the delivery of entertainment content. Despite the increasing capacity of memory devices and the widespread availability of increasingly higher bandwidth data delivery, there is continued pressure to minimize the amount of data to be stored and / or transmitted. Audio and video data are ...

AI Technical Summary

Problems solved by technology

Such an approach enables less data to be encoded, but involves relatively greater complexity on the decoder side

Similarly, while the lossy mantissa encoding process allows for substantial data compression, some information about the original mantissa value is lost during the encoding process, especially during the mantissa quantization process

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