RESPITE: The CASA Toolkit Page: Documentation: Block Library Index:AdaptiveNoiseEstimation |

AdaptiveNoiseEstimation

Initial noise mean, (mu), and variance, (var), estimates are produced from the first `NFRAMES` of data. After this the mean and variance estimates are subsequently updated with:

mu(t) = memory_factor*mu(t-1) + (1-memory_factor)*noisy(t) s(t) = memory_factor*s(t-1) + (1-memory_factor)*noisy(t)^2 var(t) = s(t) - mu(t)^2Updates are independent in each individual frequency channel.

The estimates are updated only if P(estimated_SNR<noisy_threshold) > probability_threshold.

Inputs |
Meaning | Sample | 1-D frame | 2-D frame |
---|---|---|---|---|

in1 |
noisy spectral data | Yes | Yes | Yes |

Outputs |
Meaning |
---|---|

out1 |
noise spectrum estimate |

out2 |
signal spectrum estimate |

out3 |
noise variance estimate |

Parameters |
Type | Default | Meaning |
---|---|---|---|

NFRAMES |
Integer | 10 | Number of initial frames to use for forming noise estimate |

NOISE_THRESHOLD |
Float | -6.952 | Noise level threshold in dB (See above) |

PROBABILITY_THRESHOLD |
Float | 0.600 | Probability threshold (See above) |

MEMORY_FACTOR |
Float | 0.995 | Used for means and variance tracking (See above) |

Documentation for CTKv1.1.4 - Last modified: Thu Jun 28 16:09:23 BST 2001