Audio matching tracking device and tracking method thereof based on dictionary classification

Abstract

The invention discloses an audio matching tracking device based on dictionary classification, which comprises a signal decomposing unit and a signal reconstructing unit, wherein the signal decomposing unit comprises a dictionary building module, a signal classification module, a weight comparison module, a residual calculation module and a threshold control module; and the signal reconstructing unit comprises a reconstruction coefficient extraction module and a signal synthesis module. The invention also discloses a tracking method for the tracking device. through classifying the signals, different sparse dictionaries are adopted for different types of signals for MP algorithm, the irrelevant traversal times are reduced, and the calculation complexity is reduced; during a classification pre-processing process, an adapted sparse dictionary is judged through calculating the energy distribution interval of original signals; and the method reduces the dimension of the needed dictionary, the coding rate is improved, and the use effects are good.

Description

technical field [0001] The invention relates to the field of audio coding, in particular to an audio matching and tracking device based on dictionary classification. Background technique [0002] Sparse representation generally refers to using as few basis functions as possible to accurately represent the original signal, so as to capture the main features of the signal, and then essentially reduce the cost of signal processing. Matching pursuit (MP: Matching pursuit) is one of the widely used sparse representation algorithms. Its basic idea is to sequentially select the optimal atom from the over-complete dictionary in the iterative process, so that the approximation of the signal is more optimized. Since the over-complete dictionary base used by the MP algorithm to represent the signal can be flexibly selected according to the characteristics of the signal itself; and it adopts a greedy algorithm of repeated iterative approximation in the process of atom selection, which e...

AI Technical Summary

Problems solved by technology

The traditional matching pursuit algorithm is not suitable for real-time processing due to its high computational complexity

At present, a variety of fast matching and pursuit algorithms have been proposed, but most of them involve time-consuming optimization, or sacrifice the efficiency of sparse representation as compensation, and the calculation speed is difficult to meet the needs of large-scale problems.

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