Signal processing method and equipment

Abstract

Provided are a signal processing method and device, the method comprising: selecting M sub-bands from N sub-bands (110), the N sub-bands being obtained by dividing the frequency spectrum coefficient of the current frame of a signal, and the frequency range of the M sub-bands being lower than the frequency range of K sub-bands other than the M sub-bands in the N sub-bands; according to the performance information of the M sub-bands, determining to perform correction operation on the original envelope values of the M sub-bands (120), the performance information being used to indicate the energy characteristics and frequency spectrum characteristics of the M sub-bands; respectively correcting the original envelope values of the M sub-bands to obtain corrected envelope values of the M sub-bands (130); and according to the corrected envelope values of the M sub-bands and the original envelope values of the K sub-bands, conducting primary bit allocation for the N sub-bands (140). The signal processing method and device enable bit allocation to better satisfy the bit requirement of each sub-band, thus improving signal encoding and decoding performance.

Description

technical field [0001] The present invention relates to the field of signal processing, and in particular, to a method and device for processing signals. Background technique [0002] The current communication transmission pays more and more attention to the quality of voice or audio signal, so the requirements for signal coding and decoding are also getting higher and higher. In the existing frequency domain coding algorithm, the bits are usually directly allocated to each subband of the signal according to the size of the frequency domain envelope, and then each subband is encoded using the number of allocated bits. However, practice has shown that in these existing coding algorithms, the sub-bands in the low-frequency band have a great influence on the signal coding quality, so the sub-bands in the low-frequency band often become the bottleneck of signal coding performance, and the above-mentioned bit allocation method cannot be well adapted to The bit requirements of ea...

AI Technical Summary

Problems solved by technology

However, practice has shown that in these existing coding algorithms, the sub-bands in the low-frequency band have a great influence on the signal coding quality, so the sub-bands in the low-frequency band often become the bottleneck of signal coding performance, and the above-mentioned bit allocation method cannot be well adapted to Match the bit requirements of each sub-band, especially the sub-band of the low frequency band, resulting in poor coding quality of the signal

Correspondingly, the decoding performance of the signal is also poor

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