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US 10,650,836 B2Granted
Decomposing audio signals
AssigneeDolby Laboratories Licensing Corporation
InventorsJun Wang, Lie Lu
Life of this patent
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Abstract
Example embodiments disclosed herein relate to signal processing. A method for decomposing a plurality of audio signals from at least two different channels is disclosed. The method comprises obtaining a set of components that are weakly correlated, the set of components generated based on the plurality of audio signals. The method comprises extracting a feature from the set of components, and determining a set of gains associated with the set of components at least in part based on the extracted feature, each of the gains indicating a proportion of a diffuse part in the associated component. The method further comprises decomposing the plurality of audio signals by applying the set of gains to the set of components. Corresponding system and computer program product are also disclosed.
Claims19
A method for decomposing a plurality of audio signals from at least two different channels, the method comprising:
- obtaining a set of components C that are weakly correlated, the set of components generated based on the plurality of audio signals X by transforming one or more combinations of said plurality of audio signals
- by
-
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- extracting a feature from the set of components;
- determining a set of gains associated with the set of components at least in part based on the extracted feature, each of the gains indicating a proportion of a diffuse part in the an associated components, wherein each of the gains is determined by multiplying and scaling the extracted feature as a factor;
- and
- decomposing the plurality of audio signals by applying the set of gains to the set of components,
- wherein extracting the feature comprises at least the following:
- extracting a global feature related to the set of components, and
- wherein extracting the global feature comprises extracting the global feature based on power distributions of the components,
- characterized by
- obtaining the set of components further comprising obtaining a first set of components that are weakly correlated and a second set of components that are weakly correlated, the first set of components generated in a sub-band and the second set of components generated in a full band or in a time domain, and
- wherein extracting the global feature based on power distributions of the components comprises at least one of the following:
- determining a difference between a first power, λC1,f, and a second power, λC1,f, the first power of a first component, C1,f, having a largest power among the first set of components in a sub-band f and the second power of a second component, C1, having the largest power among the second set of components, wherein the difference between the first power, λC1,f, and the second power, λC1, is determined according to:
- Δλ=|Σf=1FλC1,f−λC1|,
- wherein f denotes a sub-band index and F denotes a total number of sub-bands;
- and
- determining a difference ΔD between a unit vector, αj, representing a position of the component, C1, having the largest power among the second set of components and a second unit vector, αj, representing the position of the first component, C1,f, having the largest power among the first set of components in the sub-band f
- by
- ΔD=1−Σj=1MΣi=1M(αj)i*(αj)i
- or
- ΔD=Σj=1MΣi=1M((αj)i−(αj)i)2,
- wherein M denotes a number of channels.
69 more elements
A system for decomposing a plurality of audio signals from at least two different channels, the system comprising:
- a component obtaining unit configured to obtain a set of components C that are weakly correlated, the set of components generated based on the plurality of audio signals X by transforming one or more combinations of said plurality of audio signals
- by
-
-
- C
- ⇀
- =
- [
- C
- 1
- …
- C
- M
- ]
- =
- [
- X
- 1
- …
- X
- M
- ]
- ·
- [
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- 1
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- M
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- a feature extracting unit configured to extract a feature from the set of components;
- a gain determining unit configured to determine a set of gains associated with the set of components at least in part based on the extracted feature, each of the gains indicating a proportion of a diffuse part in an associated component, wherein each of the gains is determined by multiplying and scaling the extracted feature as a factor;
- and
- a decomposing unit configured to decompose the plurality of audio signals by applying the set of gains to the set of components,
- wherein the feature extracting unit is further configured to do at least the following:
- extract a global feature related to the set of components, and
- wherein the feature extracting unit is further configured to extract the global feature based on power distributions of the components,
- characterized in that the component obtaining unit is further configured to:
- obtain a first set of components that are weakly correlated and a second set of components that are weakly correlated, the first set of components generated in a sub-band and the second set of components generated in a full band or in a time domain, and
- wherein the feature extracting unit is further configured to do at least one of the following:
- determine a difference between a first power, λC1,f, and a second power, λC1, the first power of a first component, C1,f, having a largest power among the first set of components in a sub-band f and the second power of a second component, C1, having the largest power among the second set of components, wherein the difference between the first power, λC1,f, and the second power, λC1, is determined according to:
- Δλ=|Σf=1FλC1,f−λC1|,
- wherein f denotes a sub-band index and F denotes a total number of sub-bands;
- and
- determine a difference ΔD between a unit vector, αj, representing a position of the component, C1, having the largest power among the second set of components and a second unit vector, αj, representing the position of the first component, C1,f, having the largest power among the first set of components in the sub-band f
- by
- ΔD=1−Σj=1MΣi=1M(αj)i*(αj)i
- or
- ΔD=Σj=1MΣi=1M((αj)i−(αj)i)2,
- wherein M denotes a number of channels.
69 more elements
Dependencies are inferred from the claim text.