Multi channel audio processing

1. A method comprising:

receiving at least a first input audio signal representing a first audio channel and a second input audio signal representing a second audio channel, said first and second input audio signals jointly representing a spatial audio image of an acoustic space;

using an inter-channel prediction model between said first and second input audio signals to form at least one inter-channel parameter, said at least one inter-channel parameter being descriptive of a difference between said first and second audio channels, said inter-channel prediction model being a linear prediction model wherein a sample of said first input audio signal is predicted using a weighted linear combination of samples of said second input audio signal;

combining said first and second input audio signals into a downmix signal; and

providing an output signal comprising the downmix signal and said at least one inter-channel parameter for use in recreating said spatial audio image.

2. The method as claimed in claim 1 , further comprising:

using different inter-channel prediction models for different sub bands.

3. The method as claimed in claim 1 , further comprising:

using at least one selection criterion for selecting an inter-channel prediction model for use, wherein the at least one selection criterion is based upon a performance measure of the inter-channel prediction model.

4. The method as claimed in claim 3 , wherein the performance measure is prediction gain.

5. The method as claimed in claim 4 , wherein one selection criterion requires that the performance measure be greater than a first absolute threshold value.

6. The method as claimed in claim 4 , wherein one selection criterion requires that the performance measure is greater than a second relative threshold value dependent upon a performance value for another inter-channel prediction model.

7. The method as claimed in claim 1 , further comprising:

selecting an inter-channel prediction model for use from a plurality of inter-channel prediction models.

8. The method as claimed in claim 1 , further comprising:

using cross-correlation to determine at least one inter-channel parameter.

9. The method as claimed in claim 1 , wherein the inter-channel prediction model represents a predicted sample of an audio channel in terms of a history of an audio channel.

10. The method as claimed in claim 9 , further comprising:

minimizing a cost function for the predicted sample to determine an inter-channel prediction model; and

using the determined inter-channel prediction model to determine at least one inter-channel parameter.

11. The method as claimed in claim 10 , wherein the cost function is a difference between the predicted sample and an actual sample.

12. The method as claimed in claim 1 , wherein the inter-channel prediction model is one of an autoregressive model, a moving average model and an autoregressive moving average model.

13. The method as claimed in claim 1 , wherein the at least one inter-channel parameter comprises a time difference inter-channel parameter.

14. The method as claimed in claim 13 , further comprising:

determining a phase response of the inter-channel prediction model to determine a time difference inter-channel parameter.

15. The method as claimed in claim 1 , wherein the at least one inter-channel parameter comprises a level-difference inter-channel parameter.

16. The method as claimed in claim 15 , further comprising:

determining magnitude response of the inter-channel prediction model to determine a level-difference inter-channel parameter.

17. The method as claimed in claim 1 , further comprising:

providing an output signal comprising a downmixed signal and the at least one inter-channel parameter.

18. A computer program product comprising a non-transitory computer-readable storage medium bearing computer program code embodied therein for use with a processor, the computer program code comprising code for performing the method of claim 1 .

19. A computer program product comprising a non-transitory computer-readable storage medium bearing machine readable instructions embodied therein for use with a processor, the machine readable instructions comprising instructions for performing at least the following:

receive at least a first input audio signal representing a first audio channel and a second input audio signal representing a second audio channel, said first and second input audio signals jointly representing a spatial audio image of an acoustic space;

use an inter-channel prediction model between said first and second input audio signals to form at least one inter-channel parameter, said at least one inter-channel parameter being descriptive of a difference between said first and second audio channels, said inter-channel prediction model being a linear prediction model wherein a sample of said first input audio signal is predicted using a weighted linear combination of samples of said second input audio signal;

combine said first and second input audio signals into a downmix signal; and

provide an output signal comprising the downmix signal and said at least one inter-channel parameter for use in recreating said spatial audio image.

20. The computer program product as claimed in claim 19 , wherein the machine readable instructions further comprise instructions for performing:

use at least one selection criterion for selecting the inter-channel prediction model for use, wherein the at least one selection criterion is based upon a performance measure of the inter-channel prediction model.

21. The computer program product as claimed in claim 20 , wherein one selection criterion requires that the performance measure be greater than a threshold value.

22. The computer program product as claimed in claim 19 , wherein the machine readable instructions further comprise instructions for performing:

select an inter-channel prediction model for use from a plurality of inter-channel prediction models.

23. The computer program product as claimed in claim 19 , wherein the machine readable instructions further comprise instructions for performing:

use cross-correlation to determine at least one inter-channel parameter when no inter-channel prediction model is usable.

24. An apparatus comprising:

one or more processors; and

one or more memories including computer program code, the one or more memories and the computer program code configured, with the one or more processors, to cause the apparatus to perform at least the following:

receiving at least a first input audio signal representing a first audio channel and a second input audio signal representing a second audio channel, said first and second input audio signals jointly representing a spatial audio image of an acoustic space;

using an inter-channel prediction model between said first and second input audio signals to form at least one inter-channel parameter, said at least one inter-channel parameter being descriptive of a difference between said first and second audio channels, said inter-channel prediction model is being a linear prediction model wherein a sample of said first input audio signal is predicted using a weighted linear combination of samples of said second input audio signal;

combining said first and second input audio signals into a downmix signal; and

providing an output signal comprising the downmix signal and said at least one inter-channel parameter for use in recreating said spatial audio image.

25. The apparatus as claimed in claim 24 , wherein the one or more memories and the computer program code are further configured, with the one or more processors, to cause the apparatus to perform:

using at least one selection criterion for selecting an inter-channel prediction model for use, wherein the at least one selection criterion is based upon a performance measure of the inter-channel prediction model.

26. The apparatus as claimed in claim 24 , wherein the one or more memories and the computer program code are further configured, with the one or more processors, to cause the apparatus to perform:

selecting an inter-channel prediction model for use from a plurality of inter-channel prediction models.

27. The apparatus as claimed in claim 24 , wherein the one or more memories and the computer program code are further configured, with the one or more processors, to cause the apparatus to perform:

using cross-correlation to determine at least one inter-channel parameter when no inter-channel prediction model is usable.

28. The method as claimed in claim 1 , further comprising capturing said first and second input audio signals by first and second microphones to capture at least one sound source within said acoustic space.