Telecommunications speech signal improvement by reduction of residual noise

In a telecommunications network carrying incoming signals having both speech and noise energy, a method including iterative estimations using an LPC speech model for processing said signals at a selected point in said network to reduce said noise energy, comprising the steps of:

• converting said incoming signals to a time-series of spectral energy data frames;
• reducing in an initial stage comprising said LPC speech model the noise energy in each said frame, thereby creating noise-reduced data frames having residual low-amplitude non-stationary noise appearing randomly in data frames as false formant pickets or other noise components of varying amplitudes;
• making an estimate of the noise power spectrum for each said data frame;
• identifying in successive said data frames any said pickets at or below a threshold amplitude set at a defined distance above said noise power spectrum estimate for each said data frame.
• comparing the amplitude of each identified picket in a given data frame to the amplitudes of corresponding said pickets in time-adjacent data frames to determine which has the minimum amplitude;
• combining said noise-minimized frames with said noise-reduced frames;
• and substituting said minimum value for the amplitude of each said identified picket;
• and
• transmitting the combined signal through said network.

In a telecommunications network carrying incoming signals having both speech and noise energy, a method for processing said signals at a selected point in said network to reduce said noise energy, comprising the steps of:

• converting said incoming signals to a time-series of special energy data frames;
• using an iterated filter based on an LPC speech modal with filter-order adjustments, iteratively processing said data frames to create a new filter for each iteration of a current frame, a noise power spectra estimate for each frame and a noise-reduced output speech signal for each iteration, thereby also creating residual low-amplitude non-stationary noise appearing randomly in data frame pickets at false formant or other noise components;
• detecting noise-only frames and in response thereto updating said noise power spectrum estimate only during said noise-only frames;
• identifying in successive said data frames from the output speech signal of said iterative filter any said pickets at or below a threshold amplitude set at a defined distance above said noise power spectrum estimate for each said data frame;
• comparing the amplitude of each identified picket in a given data frame to the amplitudes of corresponding said pickets in time-adjacent data frames to determine which has the minimum amplitude;
• substituting said minimum value for the amplitude of each said identified picket;
• combining said noise-minimized frames with said noise-reduced frames;
• and
• transmitting the combined signal through said network.