Signal adaptive noise filter

1. A noise filtering method for an incoming signal, comprising:

executing, by a processor coupled to a memory, a transformation operation on the incoming signal by distributing energy corresponding to each of a plurality of components of the incoming signal into a two-dimensional representation; and

executing, by the processor, a filtering operation on the plurality of components to determine real objects and remove noise within the incoming signal, the filtering operation utilizing at least one of a plurality of noise detection matrixes based on time, frequency, or direction.

2. The noise filtering method of claim 1 , wherein the noise filtering method comprises:

receiving, by the processor coupled, input data from at least two microphones to generate the incoming signal comprising a relative loudness; and

determining, by the processor, directions of plurality of components of the incoming signal based on the relative loudness.

3. The noise filtering method of claim 1 , wherein each value of the two-dimensional representation represents the energy corresponding to each of a plurality of components of the incoming signal across an x-axis representing a direction and a y-axis representing a frequency.

4. The noise filtering method of claim 1 , wherein the processor accesses a noise filter algorithm to transform input data from at least two microphones from a time domain to the frequency domain.

5. The noise filtering method of claim 1 , wherein the noise detection matrixes comprise a support matrix, a score matrix, and a threshold matrix.

6. The noise filtering method of claim 1 , wherein the processor utilizes machine learning to optimize execution time of the transformation and filtering operations.

7. The noise filtering method of claim 1 , wherein the processor utilizes feature learning from noise-free audio samples to remove the noise during the filtering operation.

8. A computer program product for noise filtering of an incoming signal, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause:

executing, by the processor coupled to a memory, a transformation operation on the incoming signal by distributing energy corresponding to each of a plurality of components of the incoming signal into a two-dimensional representation; and

executing, by the processor, a filtering operation on the plurality of components to determine real objects and remove noise within the incoming signal, the filtering operation utilizing at least one of a plurality of noise detection matrixes based on time, frequency, or direction.

9. The computer program product of claim 8 , wherein the program instructions are further executable by the processor to cause:

receiving, by the processor coupled, input data from at least two microphones to generate the incoming signal comprising a relative loudness; and

determining, by the processor, directions of plurality of components of the incoming signal based on the relative loudness.

10. The computer program product of claim 8 , wherein each value of the two-dimensional representation represents the energy corresponding to each of a plurality of components of the incoming signal across an x-axis representing a direction and a y-axis representing a frequency.

11. The computer program product of claim 8 , wherein the processor accesses a noise filter algorithm to transform input data from at least two microphones from a time domain to the frequency domain.

12. The computer program product of claim 8 , wherein the noise detection matrixes comprise a support matrix, a score matrix, and a threshold matrix.

13. The computer program product of claim 8 , wherein the processor utilizes machine learning to optimize execution time of the transformation and filtering operations.

14. The computer program product of claim 8 , wherein the processor utilizes feature learning from noise-free audio samples to remove the noise during the filtering operation.

15. A system, comprising a processor and a memory storing program instructions for noise filtering of an incoming signal thereon, the program instructions executable by the processor to cause the system to perform:

executing a transformation operation on the incoming signal by distributing energy corresponding to each of a plurality of components of the incoming signal into a two-dimensional representation; and

executing a filtering operation on the plurality of components to determine real objects and remove noise within the incoming signal, the filtering operation utilizing at least one of a plurality of noise detection matrixes based on time, frequency, or direction.

16. The system of claim 15 , wherein the program instructions are further executable by the processor to cause:

receiving, by the processor coupled, input data from at least two microphones to generate the incoming signal comprising a relative loudness; and

determining, by the processor, directions of plurality of components of the incoming signal based on the relative loudness.

17. The system of claim 15 , wherein each value of the two-dimensional representation represents the energy corresponding to each of a plurality of components of the incoming signal across an x-axis representing a direction and a y-axis representing a frequency.

18. The system of claim 15 , wherein the processor accesses a noise filter algorithm to transform input data from at least two microphones from a time domain to the frequency domain.

19. The system of claim 15 , wherein the noise detection matrixes comprise a support matrix, a score matrix, and a threshold matrix.

20. The system of claim 15 , wherein the processor utilizes machine learning to optimize execution time of the transformation and filtering operations.