GMask

The GMask block produces `cleaned' speech, the present data mask and the probability of the present mask, using the noisy speech and the noise means and variance estimates. This block is intended to be used together with blocks such as the AdaptiveNoiseEstimation block which produce estimates of the noise mean and variance. It is assumed that the noisy data is spectral data, that the distribution of the estimated noise is Normal, and that the channels are independent.

The `cleaned' speech (out1) is simply the noisy speech minus the noise mean estimate. The probability of present data (out3) is P(estimated_SNR<NOISE_THRESHOLD), and the present data mask (out2) is computed as P(estimated_SNR<NOISE_THRESHOLD) > PROBABILITY_THRESHOLD.

WARNING: the cleaned speech may contain negative values!"

Inputs	Meaning	Sample	1-D frame	2-D frame
in1	noisy data	Yes	Yes	Yes
in2	estimate of noise mean	Yes	Yes	Yes
in3	estimate of noise variance	Yes	Yes	Yes

Outputs	Meaning
out1	`cleaned' speech
out2	present data mask
out3	present data probability

Parameters	Type	Default	Meaning
NOISE_THRESHOLD	Float	6.952	Noise level threshold in dB (See above)
PROBABILITY_THRESHOLD	Float	0.600	Probability threshold for out2 (See above)