Position-robust multiple microphone noise estimation techniques

• US 10,242,689 B2
• Filed: 09/17/2015
• Issued: 03/26/2019
• Est. Priority Date: 09/17/2015
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel IP Corporation (Intel Corporation)
• Inventors: Chatlani, Navin
• Primary Examiner(s): Opsasnick, Michael N
• Application Number:
  US14/857,087
• Publication Number:
  US 20170084288A1
• Time in Patent Office: 1,286 Days
• Field of Search: None
• CPC Class Codes: G10L 2021/02165 Two microphones, one receiving mainly the noise signal and the other one mainly the speech signal
• CPC Class Codes: G10L 21/0216 characterised by the method used for estimating noise
• CPC Class Codes: G10L 21/0232 Processing in the frequency domain
• CPC Class Codes: G10L 21/0264 characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
• CPC Class Codes: G10L 25/84 for discriminating voice from noise
• CPC Class Codes: H04R 2410/05 Noise reduction with a separate noise microphone
• CPC Class Codes: H04R 2499/11 Transducers incorporated or for use in hand-held devices, e.g. mobile phones, PDA's, camera's
• CPC Class Codes: H04R 2499/15 Transducers incorporated in visual displaying devices, e.g. televisions, computer displays, laptops
• CPC Class Codes: H04R 25/407 Circuits for combining signals of a plurality of transducers
• CPC Class Codes: H04R 3/005 for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407

Abstract

Techniques are disclosed for position-robust multiple microphone noise estimation techniques. The position-robust noise estimation techniques can be used when receiving speech including diffuse noise sources, which is commonly encountered in noisy environments. The position-robust noise estimation techniques include detecting speech using the power level difference (PLD) and the coherence statistics (CS) between two microphone input signals. This multi-dimensional approach results in dual microphone noise estimation which is not affected by the position of the audio input device, resulting in more accurate detection of speech periods and more accurate noise estimation results. The position-robust noise estimate obtained from the techniques can then be used as part of a noise reduction system to reduce the levels of noise in noisy speech signals.

Claims

1. A method for noise estimation and reduction in an audio signal, the method comprising:

determining the power level difference (PLD) between a first microphone input signal and a second microphone input signal for a given time period by subtracting the absolute value of the second microphone input signal from the absolute value of the first microphone input signal, the PLD determination further comprising compensating for at least one of bias or mismatch between the first and second microphones, wherein a coherence value exists between the first and second microphone input signals, and an average coherence value is determined using coherence values for a plurality of frequency bins in the given time period;

determining if speech is detected in the first microphone input signal in the given time period, wherein speech is detected if the PLD between the first and second microphone input signals is a positive value, wherein speech is also detected if the PLD between the first and second microphone input signals is not a positive value but the average coherence value between the first and second microphone input signals is greater than or equal to a predetermined coherence value threshold, and wherein speech is not detected if the PLD between the first and second microphone input signals is not a positive value and the average coherence value between the first and second microphone input signals is less than the predetermined coherence value threshold;

calculating a noise power estimate based on whether speech is detected in the first microphone input signal in the given time period;

calculating a gain using the noise power estimate; and

performing noise reduction on the first microphone input signal using the gain to produce a speech signal that has reduced noise or is completely free of noise.

2. The method of claim 1, wherein the average coherence value is determined over all frequency bins in the given time period.

3. The method of claim 1, wherein when speech is detected, calculating the noise power estimate for the given time period includes using a single channel noise estimate technique.

4. The method of claim 3, wherein calculating the noise power estimate for the given time period includes using the noise power estimate for a previous time period.

5. The method of claim 3, further comprising performing at least one other process to further reduce noise in the first microphone input signal.

6. The method of claim 1, wherein when speech is not detected, calculating the noise power estimate for the given time period includes using the coherence value between the first and second microphone input signals.

7. The method of claim 6, wherein calculating the noise power estimate for the given time period includes using the noise power estimate for a previous time period.

8. The method of claim 6, further comprising performing at least one other process to further reduce noise in the first microphone input signal.

9. The method of claim 1, wherein the coherence value between the first and second microphone input signals is determined using cross power spectral densities and auto power spectral densities of the first and second microphone input signals.

10. The method of claim 1, further comprising transforming the first and second microphone input signals into a plurality of time-frequency bins, the plurality of time-frequency bins used to determine the average coherence value over all frequency bins for the given time period.

11. The method of claim 1, wherein the coherence value threshold is user-configurable.

12. The method of claim 1, wherein increasing the coherence value threshold causes a decrease in the detection of speech.

13. The method of claim 1, wherein decreasing the coherence value threshold causes an increase in the detection of speech.

14. A non-transitory computer program product having instructions encoded thereon that when executed by one or more processors cause a process to be carried out, the process comprising:

determine the power level difference (PLD) between a first microphone input signal and a second microphone input signal for a given time period by subtracting the absolute value of the second microphone input signal from the absolute value of the first microphone input signal, the PLD determination further comprising compensating for at least one of bias or mismatch between the first and second microphones, wherein a coherence value exists between the first and second microphone input signals, and an average coherence value is determined using coherence values for a plurality of frequency bins in the given time period;

determine if speech is detected in the first microphone input signal in the given time period, wherein speech is detected if the PLD between the first and second microphone input signals is a positive value, wherein speech is also detected if the PLD between the first and second microphone input signals is not a positive value but the average coherence value between the first and second microphone input signals is greater than or equal to a predetermined coherence value threshold, and wherein speech is not detected if the PLD between the first and second microphone input signals is not a positive value and the average coherence value between the first and second microphone input signals is less than the predetermined coherence value threshold;

calculate a noise power estimate based on whether speech is detected in the first microphone input signal in the given time period;

calculate a gain using the noise power estimate; and

perform noise reduction on the first microphone input signal using the gain to produce a speech signal that has reduced noise or is completely free of noise.

15. The computer program product of claim 14, wherein when speech is detected, calculate the noise power estimate for the given time period includes using a single channel noise estimate technique.

16. The computer program product of claim 15, the process further comprising:

perform at least one other process to further reduce noise in the first microphone input signal.

17. The computer program product of claim 14, wherein when speech is not detected, calculate the noise power estimate for the given time period includes using the coherence value between the first and second microphone input signals.

18. The computer program product of claim 17, the process further comprising:

perform at least one other process to further reduce noise in the first microphone input signal.

19. The computer program product of claim 14, the process further comprising:

transform the first and second microphone input signals into a plurality of time-frequency bins, the plurality of time-frequency bins used to determine the average coherence value over all frequency bins for the given time period.

20. A system for noise estimation and reduction, the system comprising:

a first microphone configured to receive a first microphone input signal;

a second microphone configured to receive a second microphone input signal; and

at least one processor configured to;

determine the power level difference (PLD) between a first microphone input signal and a second microphone input signal for a given time period by subtracting the absolute value of the second microphone input signal from the absolute value of the first microphone input signal, the PLD determination further comprising compensating for at least one of bias or mismatch between the first and second microphones, wherein a coherence value exists between the first and second microphone input signals, and an average coherence value is determined using coherence values for a plurality of frequency bins in the given time period;

determine if speech is detected in the first microphone input signal in the given time period, wherein speech is detected if the PLD between the first and second microphone input signals is a positive value, wherein speech is also detected if the PLD between the first and second microphone input signals is not a positive value but the average coherence value between the first and second microphone input signals is greater than or equal to a predetermined coherence value threshold, and wherein speech is not detected if the PLD between the first and second microphone input signals is not a positive value and the average coherence value between the first and second microphone input signals is less than the predetermined coherence value threshold;

calculate a noise power estimate based on whether speech is detected in the first microphone input signal in the given time period;

calculate a gain using the noise power estimate; and

perform noise reduction on the first microphone input signal using the gain to produce a speech signal that has reduced noise or is completely free of noise.

21. The system of claim 20, wherein when speech is detected, calculate the noise power estimate for the given time period includes using a single channel noise estimate technique.

22. The system of claim 21, the processor further configured to:

perform at least one other process to further reduce noise in the first microphone input signal.

23. The system of claim 20, wherein when speech is not detected, calculate the noise power estimate for the given time period includes using the coherence value between the first and second microphone input signals.

24. The system of claim 23, the processor further configured to:

perform at least one other process to further reduce noise in the first microphone input signal.

25. A mobile computing device comprising the system of claim 20.