Online Source Separation

• US 20130121506A1
• Filed: 12/22/2011
• Published: 05/16/2013
• Est. Priority Date: 09/23/2011
• Status: Active Grant

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Inc.
• Inventors: Mysore, Gautham J., Smaragdis, Paris, Duan, Zhiyao
• Granted Patent: US 9,966,088 B2
• Time in Patent Office: Days
• US Class Current: 381/94.2
• CPC Class Codes: G10L 21/028 using properties of sound source

Abstract

Online source separation may include receiving a sound mixture that includes first audio data from a first source and second audio data from a second source. Online source separation may further include receiving pre-computed reference data corresponding to the first source. Online source separation may also include performing online separation of the second audio data from the first audio data based on the pre-computed reference data.

Claims

1. A method, comprising:

receiving a sound mixture that includes first audio data from a first source and second audio data from a second source;

receiving pre-computed reference data corresponding to the first source; and

performing online separation of the second audio data from the first audio data based on the pre-computed reference data.

2. The method of claim 1, wherein said performing online separation is performed in real-time.

3. The method of claim 1, wherein said performing online separation includes modeling the second audio data with a plurality of basis vectors.

4. The method of claim 1, wherein said performing online separation includes:

determining that a frame of the sound mixture includes audio data other than the first audio data; and

separating the second audio data from the first audio data for the frame.

5. The method of claim 4, wherein said separating includes:

for the frame, determining spectral bases for the second source and determining a plurality of weights for each of the first and second sources; and

updating a dictionary for the second source with the determined spectral bases and updating a set of weights with the determined plurality of weights for each of the first and second sources.

6. The method of claim 1, wherein said performing online separation includes:

determining that a frame of the sound mixture does not include second audio data; and

bypassing updating a dictionary for the second source for the frame.

7. The method of claim 1, wherein said performing online separation is performed using probabilistic latent component analysis (PLCA).

8. The method of claim 1, further comprising reconstructing a signal that includes the second audio data based on said online separation.

9. The method of claim 1, wherein the pre-computed reference data includes a plurality of spectral basis vectors of the first source.

10. The method of claim 1, wherein the pre-computed reference data is computed from different audio data than the first audio data, wherein the different audio data is of a same source type as the first source.

11. The method of claim 1, wherein the sound mixture includes audio data from N sources including the first and second sources, further comprising:

receiving pre-computed reference data corresponding to each of the N sources other than the second source;

wherein said performing online separation further includes separating the second audio data from audio data from each of the other N−

1 sources based on the pre-computed reference data corresponding to each of the other N−

1 sources.

12. The method of claim 1, wherein the first audio data is a spectrogram of a signal from the first source, wherein each segment of the spectrogram is represented by a convex combination of spectral components of the pre-computed reference data.

13. The method of claim 1, wherein the first source is a non-stationary noise source.

14. A non-transitory computer-readable storage medium storing program instructions, wherein the program instructions are computer-executable to implement:

receiving a sound mixture that includes first audio data from a first source and second audio data from a second source;

receiving a pre-computed dictionary corresponding to the first source; and

performing online separation of the second audio data from the first audio data based on the pre-computed dictionary.

15. The non-transitory computer-readable storage medium of claim 14, wherein said performing online separation is performed in real-time.

16. The non-transitory computer-readable storage medium of claim 14, wherein said performing online separation includes modeling the second audio data with a plurality of basis vectors.

17. The non-transitory computer-readable storage medium of claim 14, wherein to implement said performing online separation, the program instructions are further computer-executable to implement:

determining that a frame of the sound mixture includes audio data other than the first audio data; and

separating the second audio data from the first audio data for the frame.

18. The non-transitory computer-readable storage medium of claim 14, wherein to implement said separating, the program instructions are further computer-executable to implement:

for the frame, determining spectral bases for the second source and determining a plurality of weights for each of the first and second sources; and

updating a dictionary for the second source with the determined spectral bases and updating a set of weights with the determined plurality of weights for each of the first and second sources.

19. The non-transitory computer-readable storage medium of claim 14, wherein to implement said performing online separation, the program instructions are further computer-executable to implement:

determining that a frame of the sound mixture does not include second audio data; and

bypassing updating a dictionary for the second source for the frame.

20. A system, comprising:

at least one processor; and

a memory comprising program instructions, wherein the program instructions are executable by the at least one processor to;

receive a sound mixture having first audio data from a first source and second audio data from a second source;

receive pre-computed reference data corresponding to the first source; and

perform online separation of the second audio data from the first audio data based on the pre-computed reference data.