Dual-microphone frequency amplitude response self-calibration

• US 9,532,139 B1
• Filed: 12/20/2012
• Issued: 12/27/2016
• Est. Priority Date: 09/14/2012
• Status: Active Grant

• Current Assignee: Cirrus Logic Incorporated
• Original Assignee: Cirrus Logic Incorporated
• Inventors: Lu, Yang, Zhou, Dayong, Hendrix, Jon D., Alderson, Jeffrey
• Primary Examiner(s): Zhang, Leshui
• Application Number:
  US13/721,832
• Time in Patent Office: 1,468 Days
• Field of Search: 381/1, 381/13, 381/56, 381/57, 381/58, 381/61, 381/317, 381/318, 381/320, 381/321, 381 711- 7114, 381/73.1, 381/83, 381/84, 381/91, 381/92, 381/93, 381/94.1, 381/94.2, 381/94.3, 381/94.5, 381/94.6, 381/94.7, 381/94.9, 381/95, 381 97-103, 381/120, 381/121, 381/122, 381111-115, 700/94, 455/135, 455/226.3, 455/310, 379/22.08, 379/392.01, 37940601-40616, 704224-226, 704/E17.014, 704/203, 704/205
• US Class Current: 1/1
• CPC Class Codes: G10K 11/16 Methods or devices for protecting against, or for damping, noise or other acoustic waves in general G10K11/36 takes precedence
• CPC Class Codes: G10K 11/17823 Reference signals, e.g. ambient acoustic environment
• CPC Class Codes: G10K 11/1783 handling or detecting of non-standard events or conditions, e.g. changing operating modes under specific operating conditions
• CPC Class Codes: G10K 11/17855 for improving speed or power requirements
• CPC Class Codes: G10K 11/17881 the reference signal being an acoustic signal, e.g. recorded with a microphone
• CPC Class Codes: G10K 11/17885 additionally using a desired external signal, e.g. pass-through audio such as music or speech
• CPC Class Codes: G10K 2210/1081 Earphones, e.g. for telephones, ear protectors or headsets
• CPC Class Codes: G10K 2210/503 Diagnostics; Stability; Alarms; Failsafe
• CPC Class Codes: H04R 1/1083 Reduction of ambient noise active noise reduction per se G10K11/175; protective devices for the ear, e.g. providing acoustic protection A61F11/06
• CPC Class Codes: H04R 2410/05 Noise reduction with a separate noise microphone
• CPC Class Codes: H04R 2460/01 Hearing devices using active noise cancellation
• 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 3/005 for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407

Abstract

A frequency domain method and system for online self-calibrating microphone frequency amplitude response based on noise floor (minima) tracking are disclosed. A cellular telephone or other system with dual microphones may self-calibrate itself on-the-fly. The system selects one of the microphones as a reference and calibrates the frequency response of the two microphones using the first microphone as a reference, so that they have a matched frequency amplitude response. To achieve this on-the-fly calibration, the system uses background noise for calibration purposes. The signal power spectra of the noise minima at the two microphones is used to calibrate the respective microphone frequency response. The system may then adapt the frequency amplitude responses of the two microphones so that the power spectral density from each microphone matches the other, and the system is then calibrated. This calibration could occur any time the device is receiving a noise minima and could be done continuously as the device is being used.

Claims

1. In a multiple microphone system having at least two microphones, a method of self-calibration, comprising:

receiving ambient noise signals from the at least two microphones;

tracking noise minima in a time domain for each of the ambient noise signals from the at least two microphones by tracking the noise minima of each of the ambient noise signals from the at least two microphones for a predetermined number of frequency bins;

calculating an amplitude calibration value based on a ratio of the noise minima of each of the ambient noise signals from two of the at least two microphones by calculating the amplitude calibration value for each of the predetermined number of frequency bins based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones; and

altering gain of at least one of the at least two microphones to calibrate one of the at least two microphones relative to another of the at least two microphones based on the amplitude calibration value.

2. The method of claim 1, further comprising:

comparing the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones with a predetermined value,

if the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones is greater than the predetermined value, determining that one or more of the at least two microphones is broken, malfunctioning, or clogged, and

notifying a user that one or more of the at least two microphones is broken, malfunctioning, or clogged.

3. The method of claim 1, wherein calculating the amplitude calibration value for each frequency bin further comprises smoothing amplitude calibration value changes over time by multiplying the amplitude calibration value by a predetermined smoothing factor.

4. The method of claim 3, wherein calculating the amplitude calibration value for each frequency bin based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones further comprises calculating a value g[k] as follows:

g[k]=alpha*g[k]+(1-alpha)*xMinEnv[k]/yMinEnv[k]

where xMinEnv[k] represents a minima level for a particular frequency bin k for a signal x from one of the at least two microphones and yMinEnv[k] represents a minima level for a particular frequency bin k for the signal y from another of the at least two microphones and alpha represents the predetermined smoothing factor.

5. A self-calibrating multiple microphone system, comprising at least two microphones, comprising:

the at least two microphones each receiving at least ambient noise signals;

a noise minima tracker receiving the ambient noise signals from each of the at least two microphones and tracking noise minima in a time domain for each of the ambient noise signals from the at least two microphones by tracking the noise minima of each of the ambient noise signals from the at least two microphones for a predetermined number of frequency bins;

a calibrator calculating an amplitude calibration value based on a ratio of the noise minima of each of the ambient noise signals from two of the at least two microphones by calculating the amplitude calibration value for each of the predetermined number of frequency bins based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones; and

an input filter coupled to at least one of the at least two microphones having a gain profile altered by the calculated amplitude calibration value to calibrate one of the at least two microphones relative to another of the at least two microphones.

6. The system of claim 5, further comprising:

a microphone condition detector comparing the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones with a predetermined value, and if the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones is greater than the predetermined value, determining that one or more of the at least two microphones is malfunctioning, broken, or clogged, and notifying a user that one or more of the at least two microphones is malfunctioning, broken, or clogged.

7. The system of claim 5, wherein calculating the amplitude calibration value for each frequency bin further includes smoothing amplitude calibration value changes over time by multiplying the amplitude calibration value by a predetrmined smoothing factor.

8. The system of claim 7, wherein the calibrator calculates the amplitude calibration value for each frequency bin based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones as g[k] as follows:

g[k]=alpha*g[k]+(1-alpha)*xMinEnv[k]/yMinEnv[k]

where xMinEnv[k] represents a minima level for a particular frequency bin k for a signal x from one of the at least two microphones and yMinEnv[k] represents a minima level for a particular frequency bin k for the signal y from another of the at least two microphones and alpha represents the predetermined smoothing factor.

9. A self-calibrating cellular telephone including at least two microphones, comprising:

the at least two microphones on the self-calibrating cellular telephone each receiving at least ambient noise signals;

a noise minima tracker receiving the ambient noise signals from each of the at least two microphones and tracking noise minima in a time domain for each of the ambient noise signals from the at least two microphones by tracking the noise minima of each of the ambient noise signals from the at least two microphones for a predetermined number of frequency bins;

a calibrator calculating an amplitude calibration value based on a ratio of the noise minima of each of the ambient noise signals from two of the at least two microphones by calculating the amplitude calibration value for each of the predetermined number of frequency bins based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones; and

an input filter coupled to at least one of the at least two microphones having a gain profile altered by the calculated amplitude calibration value to calibrate one of the at least two microphones relative to another of the at least two microphones.

10. The self-calibrating cellular telephone of claim 9, further comprising:

a microphone condition detector comparing the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones with a predetermined value, and if the amplitude calibration value based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones is greater than the predetermined value, determining that one or more of the at least two microphones is malfunctioning, broken, or clogged, and notifying a user that one or more of the at least two microphones is malfunctioning, broken, or clogged.

11. The self-calibrating cellular telephone of claim 9, wherein calculating the amplitude calibration value for each frequency bin further includes smoothing amplitude calibration value changes over time by multiplying the amplitude calibration value by a predetermined smoothing factor.

12. A self-calibrating cellular telephone including at least two microphones, comprising:

the at least two microphones on the self-calibrating cellular telephone each receiving audio signals including ambient noise signals;

a noise minima tracker receiving the ambient noise signals from the at least two microphones and tracking noise minima for each of the ambient noise signals from the at least two microphones;

a calibrator calculating an amplitude calibration value based on a ratio of the noise minima of each of the ambient noise signals from two of the at least two microphones; and

an input filter coupled to at least one of the at least two microphones having a gain profile altered by the calculated amplitude calibration value to calibrate one of the at least two microphones relative to another of the at least two microphones,

wherein the noise minima tracker tracks the noise minima of each of the ambient noise signals from the at least two microphones for a predetermined number of frequency bins,

wherein the calibrator calculates the amplitude calibration value for each frequency bin based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones,

wherein calculating the amplitude calibration value for each frequency bin further includes smoothing amplitude calibration value changes over time by multiplying the amplitude calibration value by a predetermined smoothing factor, and

wherein the calibrator calculates the amplitude calibration value for each frequency bin based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones as g[k] as follows;

g[k]=alpha*g[k]+(1-alpha)*xMinEnv[k]/yMinEnv[k]

where xMinEnv[k] represents a minima level for a particular frequency bin k for a signal x from one of the at least two microphones and yMinEnv[k] represents a minima level for a particular frequency bin k for the signal y from another of the at least two microphones and alpha represents the predetermined smoothing factor.

13. A self-calibrating cellular telephone including at least two microphones, comprising:

the at least two microphones on the self-calibrating cellular telephone each receiving audio signals including ambient noise signals;

a noise minima tracker receiving the ambient noise signals from the at least two microphones and tracking noise minima for each of the ambient noise signals from the at least two microphones;

a calibrator calculating an amplitude calibration value based on a ratio of the noise minima of each of the ambient noise signals from two of the at least two microphones; and

an input filter coupled to at least one of the at least two microphones having a gain profile altered by the calculated amplitude calibration value to calibrate one of the at least two microphones relative to another of the at least two microphones,

wherein the noise minima tracker tracks the noise minima of each of the ambient noise signals from the at least two microphones for a predetermined number of frequency bins,

wherein the calibrator calculates the amplitude calibration value for each frequency bin based on the ratio of the noise minima of each of the ambient noise signals from the two of the at least two microphones as g[k] as follows;

g[k]=alpha*g[k]+(1-alpha)*xMinEnv[k]/yMinEnv[k]

where xMinEnv[k] represents a minima level for a particular frequency bin k for a signal x from one of the at least two microphones and yMinEnv[k] represents a minima level for a particular frequency bin k for the signal y from another of the at least two microphones and alpha represents a predetermined smoothing factor.