Noise estimation apparatus of obtaining suitable estimated value about sub-band noise power and noise estimating method

1. A noise estimation apparatus of estimating a noise included in an input signal, comprising:

at least one sub-band noise estimator estimating a noise included in a sub-band input signal, obtained by dividing the input signal by sub-bands; wherein

said sub-band noise estimator comprises:

a power calculator calculating a sub-band input power of the sub-band input signal;

a probability model holder holding information on probability model obtained by modelizing stationarity of the noise; and

an a posteriori probability maximizer calculating an instantaneous estimated value of a sub-band noise power on a basis of the sub-band input power, an estimated value of the sub-band noise power outputted from said sub-band noise estimator and the information on the probability model held in said probability model holder, so as to maximize a posteriori probability of the sub-band noise power, and wherein

the information on the probability model includes information on:

a likelihood function with regard to a posteriori signal-to-noise ratio (SNR) on a basis of a predictive a posteriori SNR; and

a priori probability of the a posteriori SNR under a condition where averaged a posteriori SNR is established.

2. The noise estimation apparatus in accordance with claim 1 , wherein said sub-band noise estimator further comprises a smoother temporally-smoothing the instantaneous estimated value of the sub-band noise power to derive the estimated value of the sub-band noise power.

3. The noise estimation apparatus in accordance with claim 1 , wherein the a posteriori SNR is a value determined by dividing the sub-band input power by an estimated value of the sub-band noise power at a same time as the sub-band input power,

the predictive a posteriori SNR is a value determined by dividing the sub-band input power by the estimated value of the past sub-band noise power before a predetermined time; and wherein

the averaged a posteriori SNR is a temporally-smoothed a posteriori SNR calculated from at least two or more past a posteriori SNRs.

4. The noise estimation apparatus in accordance with claim 1 , wherein the a posteriori SNR is a value determined by dividing the sub-band input power by an estimated value of the sub-band noise power at a same time as the sub-band input power,

the predictive a posteriori SNR is a value determined by dividing the sub-band input power by the estimated value of the past sub-band noise power before a predetermined time, and wherein

the averaged a posteriori SNR is a single past posteriori SNR before a predetermined time.

5. The noise estimation apparatus in accordance with claim 1 , wherein the likelihood function takes a maximum value when the a posteriori SNR is equal to the predictive posteriori SNR and wherein

the likelihood function converges to zero as a difference between the a posteriori SNR and the predictive a posteriori SNR is increased.

6. The noise estimation apparatus in accordance with claim 5 , wherein, as the likelihood function, a normal distribution or a generalized normal distribution is applied.

7. The noise estimation apparatus in accordance with claim 1 , wherein, in a case where the a posteriori SNR is defined as non-negative, the a priori probability is maximized when the a posteriori SNR is equals to zero and converges to zero as the a posteriori SNR is increased.

8. The noise estimation apparatus in accordance with claim 7 , wherein, as the a priori probability, an exponential distribution is applied.

9. The noise estimation apparatus in accordance with claim 8 , wherein a speed parameter of the exponential distribution has a negative proportional relationship or an inverse proportional relationship to the averaged a posteriori SNR.

10. The noise estimation apparatus in accordance with claim 1 , wherein said a posteriori probability maximizer comprises:

a first delay delaying the estimated value of the sub-band noise power;

a second delay delaying the sub-band input power;

an a posteriori SNR calculator calculating the a posteriori SNR on a basis of the estimated value of the sub-band noise power delayed by the first delay and the sub-band input power delayed by the second delay;

a smoother calculating the averaged a posteriori SNR by temporally-smoothing the a posteriori SNR;

a coefficient determiner determining a noise amplification coefficient on a basis of the information on probability model and the averaged a posteriori SNR;

a multiplier multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

a comparator comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output an instantaneous estimated value of the sub-band noise power.

11. The noise estimation apparatus in accordance with claim 1 , wherein said a posteriori probability maximizer comprises:

a first delay delaying the estimated value of the sub-band noise power;

a second delay delaying the sub-band input power;

an a posteriori SNR calculator calculating the a posteriori SNR on a basis of the estimated value of the sub-band noise power delayed by said first delay and the sub-band input power delayed by said second delay;

a coefficient determiner determining a noise amplification coefficient on a basis of the information on probability model and the a posteriori SNR;

a multiplier multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

a comparator comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output an instantaneous estimated value of the sub-band noise power.

12. A noise estimating method of estimating a noise included in an input signal, comprising a step of estimating a noise included in a sub-band input signal obtained by dividing the input signal by sub-bands, wherein

said step of estimating the noise further comprises sub-steps of:

calculating a sub-band input power of the sub-band input signal;

holding information on probability model obtained by modelizing stationarity of the noise, the information on the probability model including information on: a likelihood function with regard to a posteriori signal-to-noise ratio (SNR) on a basis of predictive a posteriori SNR; and a priori probability of the a posteriori SNR under a condition where averaged a posteriori SNR is established; and

calculating an instantaneous estimated value of a sub-band noise power on a basis of the sub-band input power, an estimated value of the sub-band noise power and the held information on the probability model, so as to maximize a posteriori probability of the sub-band noise power.

13. The noise estimating method in accordance with claim 12 , wherein said step further comprises a smoothing sub-step of temporally-smoothing the instantaneous estimated value of the sub-band noise power to derive the estimated value of the sub-band noise power.

14. The noise estimating method in accordance with claim 12 , wherein said sub-step of calculating the instantaneous estimated value of the sub-band noise power further comprises steps of:

delaying the estimated value of the sub-band noise power;

delaying the sub-band input power;

calculating the a posteriori SNR on a basis of the delayed estimated value of the sub-band noise power and the delayed sub-band input power;

calculating the averaged a posteriori SNR by temporally-smoothing the a posteriori SNR;

determining a noise amplification coefficient on a basis of the information on probability model and the averaged a posteriori SNR;

multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output the instantaneous estimated value of the sub-band noise power.

15. The noise estimating method in accordance with claim 12 , wherein said sub-step of calculating the instantaneous estimated value of the sub-band noise power further comprises steps of:

delaying the estimated value of the sub-band noise power;

delaying the sub-band input power;

calculating the a posteriori SNR on a basis of the delayed estimated value of the sub-band noise power and the delayed sub-band input power;

determining a noise amplification coefficient on a basis of the information on probability model and the a posteriori SNR;

multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output the instantaneous estimated value of the sub-band noise power.

16. A non-transitory computer-readable medium storing a noise estimating program, when executed by a computer, causing the computer to serve as at least one sub-band noise estimator and to perform a step of estimating a noise included in a sub-band input signal, obtained by dividing an input signal inputted to the computer by sub-bands;

wherein the noise estimating step further comprises sub-steps of:

calculating a sub-band input power of the sub-band input signal;

holding information on probability model obtained by modelizing stationarity of the noise; and

calculating an instantaneous estimated value of a sub-band noise power on a basis of the sub-band input power, an estimated value of the sub-band noise power outputted from the sub-band noise estimating step and the held information on the probability model, so as to maximize a posteriori probability of the sub-band noise power, and

wherein the held information on the probability model includes information on:

a likelihood function with regard to a posteriori signal-to-noise ratio (SNR) on a basis of predictive a posteriori SNR; and

a priori probability of a posteriori SNR under a condition where averaged a posteriori SNR is established.

17. The computer-readable medium in accordance with claim 16 , wherein said noise estimating step further comprising step of temporally-smoothing the instantaneous estimated value of the sub-band noise power to derive the estimated value of the sub-band noise power.

18. The computer-readable medium in accordance with claim 16 , wherein the sub-step of calculating an instantaneous estimated value of a sub-band noise power further comprises steps of:

delaying the estimated value of the sub-band noise power;

delaying the sub-band input power;

calculating the a posteriori SNR on a basis of the delayed estimated value of the sub-band noise power and the delayed sub-band input power;

calculating the averaged a posteriori SNR by temporally-smoothing the a posteriori SNR;

determining a noise amplification coefficient on a basis of the information on probability model and the averaged a posteriori SNR;

multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output the instantaneous estimated value of a sub-band noise power.

19. The computer-readable medium in accordance with claim 16 , wherein said sub-step of calculating the instantaneous estimated value of a sub-band noise power further comprises steps of:

delaying the estimated value of the sub-band noise power;

delaying the sub-band input power;

calculating the a posteriori SNR on a basis of the delayed estimated value of the sub-band noise power and the delayed sub-band input power;

determining a noise amplification coefficient on a basis of the information on probability model and the a posteriori SNR;

multiplying the delayed estimated value of the sub-band noise power by the noise amplification coefficient to derive a provisional estimated value of the sub-band noise power; and

comparing the provisional estimated value of the sub-band noise power with the sub-band input power to selectively output the instantaneous estimated value of a sub-band noise power.