Hybrid encoding method and apparatus for encoding speech or non-speech frames using different coding algorithms
First Claim
1. An audio encoding method, wherein the method comprises:
- determining sparseness of distribution in energy spectrums of N audio frames, wherein the N audio frames comprise a current audio frame, and N is a positive integer; and
determining, according to the sparseness of distribution, whether to use a first encoding method or a second encoding method to encode the current audio frame, wherein the first encoding method is based on time-frequency transform and transform coefficient quantization, the first encoding method is not based on linear prediction, and the second encoding method is a linear-predication-based encoding method,wherein the determining the sparseness of distribution comprises;
dividing an energy spectrum of each of the N audio frames into P spectral envelopes, wherein P is a positive integer, anddetermining a general sparseness parameter according to energy of the P spectral envelopes of each of the N audio frames, wherein the general sparseness parameter indicates the sparseness of distribution.
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Abstract
An audio encoding method and an apparatus are provided. The method includes: determining sparseness of distribution, on spectrums, of energy of N input audio frames (101), where the N audio frames include a current audio frame, and N is a positive integer; and determining, according to the sparseness of distribution, on the spectrums, of the energy of the N audio frames, whether to use a first encoding method or a second encoding method to encode the current audio frame (102), where the first encoding method is an encoding method that is based on time-frequency transform and transform coefficient quantization and that is not based on linear prediction, and the second encoding method is a linear-predication-based encoding method. The method can reduce encoding complexity and ensure that encoding is of relatively high accuracy.
19 Citations
18 Claims
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1. An audio encoding method, wherein the method comprises:
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determining sparseness of distribution in energy spectrums of N audio frames, wherein the N audio frames comprise a current audio frame, and N is a positive integer; and determining, according to the sparseness of distribution, whether to use a first encoding method or a second encoding method to encode the current audio frame, wherein the first encoding method is based on time-frequency transform and transform coefficient quantization, the first encoding method is not based on linear prediction, and the second encoding method is a linear-predication-based encoding method, wherein the determining the sparseness of distribution comprises; dividing an energy spectrum of each of the N audio frames into P spectral envelopes, wherein P is a positive integer, and determining a general sparseness parameter according to energy of the P spectral envelopes of each of the N audio frames, wherein the general sparseness parameter indicates the sparseness of distribution. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An audio encoder, comprising:
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a memory comprising instructions; and
one or more processors in communication with the memory, wherein the one or more processors execute the instructions to;obtain N audio frames, wherein the N audio frames comprise a current audio frame, and N is a positive integer; determine sparseness of distribution in energy spectrums of the N audio frames; and determine, according to the sparseness of distribution, whether to use a first encoding method or a second encoding method to encode the current audio frame, wherein the first encoding method is based on time-frequency transform and transform coefficient quantization, the first encoding method is not based on linear prediction, and the second encoding method is a linear-predication-based encoding method, wherein, to determine the sparseness of distribution, the one or more processors execute instructions to; divide an energy spectrum of each of the N audio frames into P spectral envelopes, and determine a general sparseness parameter according to energy of the P spectral envelopes of each of the N audio frames, wherein P is a positive integer, and the general sparseness parameter indicates the sparseness of distribution. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification