Robust downlink speech and noise detector

• US 8,326,620 B2
• Filed: 04/23/2009
• Issued: 12/04/2012
• Est. Priority Date: 04/30/2008
• Status: Active Grant

• Current Assignee: Malikie Innovations Limited (Key Patent Innovations Limited)
• Original Assignee: QNX Software Systems Limited (Canada) (Blackberry Limited)
• Inventors: Hetherington, Phillip A.
• Primary Examiner(s): Albertalli, Brian
• Application Number:
  US12/428,811
• Publication Number:
  US 20090276213A1
• Time in Patent Office: 1,321 Days
• Field of Search: None
• US Class Current: 704/233
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10
• CPC Class Codes: G10L 25/84 for discriminating voice from noise

Abstract

A voice activity detection process is robust to a low and high signal-to-noise ratio speech and signal loss. A process divides an aural signal into one or more bands. Signal magnitudes of frequency components and the respective noise components are estimated. A noise adaptation rate modifies estimates of noise components based on differences between the signal to the estimated noise and signal variability.

Claims

1. A voice activity detection process comprising:

dividing an aural signal into a high and a low frequency component that represent a voiced or unvoiced signal;

estimating signal magnitudes of the high and low frequency components;

estimating the magnitude of noise components in the high and low frequency components; and

adapting a noise adaptation rate that modifies the estimates of the noise components of the high and low frequency components based on differences between the high and low frequency components to the estimate of the noise components and a signal variability.

2. The voice activity detection of claim 1 further comprising converting sound waves into electrical signals.

3. The voice activity detection of claim 2 further comprising converting the electrical signals into an aural sound.

4. The voice activity detection of claim 2 further comprising substantially dampening a direct current bias from the aural signal before dividing the aural signal.

5. The voice activity detection of claim 2 where the adaptation rate is based on a rate of increase of an estimated noise in a downlink signal.

6. The voice activity detection of claim 2 where the adaptation rate is based on a difference factor with the estimated noise in a downlink signal.

7. The voice activity detection of claim 2 where the adaptation rate is based on a variability factor with the estimated noise in a downlink signal.

8. The voice activity detection of claim 5 where the adaptation rate is based on lost signal factor with the estimated noise in the downlink signal.

9. The voice activity detection of claim 5 where the adaptation rate is based on a difference factor with the estimated noise in the downlink signal.

10. The voice activity detection of claim 5 where the adaptation rate is based on a difference with the estimated noise in the downlink signal.

11. The voice activity detection of claim 5 where the adaptation rate is based on a variability factor with the estimated noise in the downlink signal.

12. The voice activity detection of claim 1 further comprising identifying a voiced signal based on the noise adaptation rate.

13. A voice activity detector comprising:

a filter configured to divide an aural signal into a plurality of components that represent a voiced or unvoiced signal;

a magnitude estimator configured to estimate signal magnitudes of the plurality of components;

a noise decision controller configured to adapt a noise adaptation rate that modifies the estimates of the noise components of the plurality of components based on differences between the plurality of frequency components to the estimate of the noise components and a signal variability.

14. The voice activity detector of claim 13 further comprising an input that converts sound waves into electrical signals that are processed by the filter.

15. The voice activity detector of claim 13 further comprising a direct current filter configured to substantially dampen a direct current bias from the aural signal before dividing the aural signal.

16. The voice activity detector of claim 13 further comprising a rise adaptation rate adjuster that generates a rate adjustment, where the adaptation rate is based on a rate of increase of an estimated noise in a downlink signal.

17. The voice activity detector of claim 13 further comprising a distance factor adjuster that generates a rate adjustment, where the adaptation rate is based on a difference factor with the estimated noise in a downlink signal.

18. The voice activity detector of claim 13 further comprising a variability factor adjuster that generates a rate adjustment, where the adaptation rate is based on a variability factor with the estimated noise in a downlink signal.

19. A voice activity detector comprising:

filter means configured to divide an aural signal into a plurality of components that represent a voiced or unvoiced signal;

a magnitude estimator device configured to estimate signal magnitudes of the plurality of components; and

noise decision means configured to adapt a noise adaptation rate that modifies the estimates of the noise components of the plurality of components based on differences between the plurality of frequency components to the estimate of the noise components and a signal variability.

20. The voice activity detector of claim 19 where the noise decision means separates a plurality of noise adjustment factors into different tasks that are processed by multiple processors in separate signal flow paths.

21. A voice activity detection process comprising:

dividing an aural signal into a high and a low frequency component that represent a voiced or unvoiced signal;

estimating signal magnitudes of the high and the low frequency components;

estimating the magnitude of the noise components in the high and the low frequency components;

setting an initial noise adaption rate to a first predetermined value when the estimated signal magnitudes of the high and the low frequency components are above the estimated noise components of the high and the low frequency components, and a second predetermined value when the estimated signal magnitudes of the high and the low frequency components are below the estimated noise components of the high and the low frequency components, where the first predetermined value and the second predetermined value are different; and

adapting the initial noise adaption rate that modifies the estimates of the noise components of the high and low frequency components based on differences between the high and low frequency components to the estimate of the noise components and a signal variability.