Voice activity detection apparatus and method

• US 20060253283A1
• Filed: 05/08/2006
• Published: 11/09/2006
• Est. Priority Date: 05/09/2005
• Status: Active Grant

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Jabloun, Firas
• Granted Patent: US 7,596,496 B2
• Time in Patent Office: Days
• 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

Abstract

A voice activity detection method comprising the steps of (a) Estimating in a noise power estimator the noise power within a signal having a speech component and a noise component, and (b) Calculating a likelihood ratio for the presence of speech in the signal from the estimated power of noise signals from step (a) and a complex Gaussian statistical model.

Claims

1. A voice activity detection method comprising the steps of

(a) Estimating in a noise power estimator the noise power within a signal having a speech component and a noise component

(b) Calculating a likelihood ratio for the presence of speech in the signal from the estimated power of noise signals from step (a) and a complex Gaussian statistical model.

2. A voice activity detection method as claimed in claim 1 wherein the likelihood ratio in step (b) is restricted using a non-linear function to a predetermined interval.

3. A voice activity detection method as claimed in claim 2 wherein the likelihood ratio is restricted by the function

{overscore (Ψ

)}(t)=1−

min(1,e<sup>−

Ψ

(t)</sup>)

where Ψ

(t) is the likelihood ratio

4. A voice activity detection method as claimed in claim 1, wherein the noise power estimator uses a quantile based estimation method to estimate the noise power.

5. A voice activity detection method as claimed in claim 4, wherein the noise power estimate is smoothed using a first order recursive function.

6. A voice activity detection method as claimed in claim 1, wherein the signal is analysed over K+1 frequency bands and for each time frame the noise power estimate is only updated over a sub-set of the K+1 frequency bands.

7. A voice activity detection method as claimed in claim 6, wherein the noise estimate is updated over all K+1 frequency bands by interpolation from the sub-set of updated frequency bands.

9. A voice activity detection method as claimed in claim 1, wherein the likelihood ratio is compared to a threshold value in order to detect the presence or absence of speech.

10. A voice activity detection method as claimed in claim 1, wherein the likelihood ratio is determined by the following equation

${\Lambda }_{}$

k = P ⁡

( X k | H 1 , k ) P ⁡

( X k | H 0 , k ) = 1 1 + ξ

k ⁢

exp ⁢

{ γ

k ⁢

ξ

k 1 + ξ

k }

wherein hypothesis H₀ represents the absence of speech;

hypothesis H₁ represents the presence of speech;

λ

_N,k and λ

_S,k are the noise and speech variances at frequency index k respectively; and

γ

_k and ξ

_k, are defined as

${\mathrm{\gamma <br><br>}}_k=\frac{{<br><br>X_k<br><br>}^2}{{\mathrm{\lambda <br><br>}}_{N,k}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{and}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\xi <br><br>}}_k=\frac{{\mathrm{\lambda <br><br>}}_{S,k}}{{\mathrm{\lambda <br><br>}}_{N,k}}.$

11. A voice activity detection method as claimed in claim 10, wherein a smoothed likelihood ratio is calculated by the following equation

Ψ

_k(t)=κ

Ψ

_k(t−

1)+(1−

κ

)log Λ

_k(t)

where κ

is a smoothing factor and t is the time frame index.

12. A voice activity detection method as claimed in claim 11, wherein the geometric mean of the smoothed likelihood ratio is calculated as

$\Psi$

⁡

( t ) = 1 K ⁢

∑

k = 0 K - 1 ⁢

Ψ

k ⁡

( t )

and Ψ

(t) is used to determine the presence of speech.

15. Processor control code to, when running, implement the method of claim 1.

16. A carrier carrying the processor control code of claim 15.

20. A voice activity detection system comprising a voice activity detector configured to implement the method of claim 1, and a noise estimator for providing a noise estimate to the voice activity detector for a signal including a noise component and a speech component.

8. A voice activity detection method comprising the steps of

(a) estimating the noise power within a signal having a speech component and a noise component

(b) calculating a likelihood ratio for the presence of speech in the signal from the estimated power of noise signals from step (a) and a complex Gaussian statistical model

(c) updating the noise power estimate based on the likelihood ratio calculated in step (b)

wherein the likelihood ratio is restricted using a non-linear function to a predetermined interval.

13. A voice activity detector comprising a likelihood ratio calculator for calculating a likelihood ratio for the presence of speech in a noisy signal using an estimate of the noise power in the noisy signal and a complex Gaussian statistical model wherein the noise power estimate is calculated independently of the VAD.

17. Processor control code to, when running, implement the voice activity detector of claim 13.

18. A carrier carrying the processor control code of claim 17.

19. A voice activity detection system comprising a voice activity detector according to claim 13 and a noise estimator for providing a noise estimate to the voice activity detector for a signal including a noise component and a speech component.

14. A voice activity detector comprising a likelihood ratio calculator for calculating a likelihood ratio for the presence of speech in a noisy signal using an estimate of the noise power in the noisy signal and a complex Gaussian statistical model wherein the likelihood ratio is used to update the noise estimate within the detector and wherein the likelihood ratio is restricted using a non-linear function to a predetermined interval.