US7209567B1 — Communication system with adaptive noise suppress…

Claim 1

Independent Claim 231 words

A method of reducing noise in a communication system, the method comprising: averaging an input sound signal's magnitude spectrum over multiple time frames to reduce musical noise; determining an average magnitude of a noise spectrum while speech is not present on the input sound signal, wherein the average magnitude is determined for each of a plurality of discrete frequencies of the noise spectrum; determining a maximum ratio of noise to average noise over each of a plurality of sub-bands; determining a running average of the maximum ratio of noise to average noise over each sub-band; receiving an indication that speech may be present on the input sound signal; and for each of a plurality of frames while receiving the indication that speech may be present on the input sound signal; detecting whether speech is present; while speech is detected, estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency; and while speech is not detected, estimating the speech signal magnitude to be zero.

Claim 2

Independent Claim 231 words

A method of reducing noise in a communication system, the method comprising: averaging an input sound signal's magnitude spectrum over multiple time frames to reduce musical noise; determining an average magnitude of a noise spectrum while speech is not present on the input sound signal, wherein the average magnitude is determined for each of a plurality of discrete frequencies of the noise spectrum; determining a maximum ratio of noise to average noise over each of a plurality of sub-bands; determining a running average of the maximum ratio of noise to average noise over each sub-band; receiving an indication that speech may be present on the input sound signal; and for each of a plurality of frames while receiving the indication that speech may be present on the input sound signal; detecting whether speech is present; while speech is detected, estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency; and while speech is not detected, estimating the speech signal magnitude to be zero.

Claim 3

Dependent Claim 29 words

The method of claim 1 wherein receiving an indication that speech may be present further comprises receiving an indication that a push-to-talk button has been pressed on a microphone.

Claim 4

Dependent Claim 75 words

The method of claim 1 wherein determining an input sound signal magnitude spectrum further comprises: low-pass filtering the input sound signal; sampling m/2 samples of the input sound signal and appending those m/2 samples to a previous m/2 samples, thereby producing m samples; windowing the m samples to produce a windowed signal of m points; and zero padding the windowed signal of m points by m points to produce a frame of 2 m points.

Claim 5

Dependent Claim 21 words

The method of claim 3 , wherein windowing the m samples further comprises windowing the m samples using a hamming window.

Claim 6

Dependent Claim 16 words

The method of claim 1 , wherein the sub-bands are chosen according to the Bark scale.

Claim 7

Independent Claim 223 words

A method of reducing noise in a communication system, the method comprising: receiving an input sound signal containing noise; framing the input sound signal by performing, for each frame: sampling m/2 samples of the input sound signal and appending those m/2 samples to a previous m/2 samples, thereby producing m samples; windowing the m samples to produce a windowed signal of m points; zero padding the windowed signal of m points by m points to produce a frame of 2 m points; determining an average magnitude of the input sound signal for each of a plurality of discrete frequencies while speech is not present in the input sound signal; dividing the input sound signal spectrum into a plurality of frequency sub-bands; determining which of the frequency sub-bands contain only noise; removing by a larger proportion the frequency sub-bands containing only noise from the spectrum; and estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency.

Claim 8

Independent Claim 223 words

A method of reducing noise in a communication system, the method comprising: receiving an input sound signal containing noise; framing the input sound signal by performing, for each frame: sampling m/2 samples of the input sound signal and appending those m/2 samples to a previous m/2 samples, thereby producing m samples; windowing the m samples to produce a windowed signal of m points; zero padding the windowed signal of m points by m points to produce a frame of 2 m points; determining an average magnitude of the input sound signal for each of a plurality of discrete frequencies while speech is not present in the input sound signal; dividing the input sound signal spectrum into a plurality of frequency sub-bands; determining which of the frequency sub-bands contain only noise; removing by a larger proportion the frequency sub-bands containing only noise from the spectrum; and estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency.

Claim 9

Dependent Claim 20 words

The method of claim 6 , wherein windowing the m samples comprises windowing the m samples using a hamming window.

Claim 10

Dependent Claim 22 words

The method of claim 6 , further comprising performing a Fourier transform on the input signal prior to performing the spectral subtraction.

Claim 11

Dependent Claim 25 words

The method of claim 6 , further comprising performing a smoothing operation on the output signal to remove transients produced from a digital-to-analog conversion operation.

Claim 12

Independent Claim 193 words

A method of reducing noise in a communication system, the method comprising: determining an average magnitude of a noise spectrum while speech is not present on an input sound signal, wherein the average magnitude is determined for each of a plurality of discrete frequencies of the noise spectrum; determining a maximum ratio of noise to average noise over each of a plurality of sub-bands; determining a running average of the maximum ratio of noise to average noise over each sub-band; receiving an indication that speech may be present on the input sound signal; and for each of a plurality of frames while receiving the indication that speech may be present on the input sound signal, estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency.

Claim 13

Independent Claim 193 words

A method of reducing noise in a communication system, the method comprising: determining an average magnitude of a noise spectrum while speech is not present on an input sound signal, wherein the average magnitude is determined for each of a plurality of discrete frequencies of the noise spectrum; determining a maximum ratio of noise to average noise over each of a plurality of sub-bands; determining a running average of the maximum ratio of noise to average noise over each sub-band; receiving an indication that speech may be present on the input sound signal; and for each of a plurality of frames while receiving the indication that speech may be present on the input sound signal, estimating a speech signal magnitude for each discrete frequency by subtracting from the input sound signal magnitude for that discrete frequency the average noise for that discrete frequency multiplied by the lesser of (a) a ratio of a sum of noise-corrupted speech to a sum of average noise for the frequency sub-band containing that discrete frequency and (b) the running average of the maximum ratio of noise to average noise for the frequency sub-band containing that discrete frequency.

Claim 14

Dependent Claim 32 words

The method of claim 10 , further comprising determining which of the frequency sub-bands contain only noise, and removing by a larger proportion the frequency sub-bands containing only noise from the spectrum.

Claim 15

Independent Claim 237 words

A method of reducing noise in a communication system, the method comprising: designating a plurality of frequency sub-bands for a signal spectrum of interest; designating a plurality of frequency bins for each of said sub-bands; during an initialization/update mode, determining, for each bin, an average magnitude of noise in said system over a first set of time frames; obtaining, for each sub-band, a noise sum equal to the sum of the average noise magnitudes for the bins in the sub-band; for each of said frames in said first set, a) determining the ratio of noise to said average noise for each bin; b) determining for each sub-band, the maximum ratio of noise to said average noise for the bins therein; determining a running average of said maximum ratio for each sub-band; and during a noise reduction mode, for each frame in a second set of time frames, a) obtaining, for each sub-band, an input signal sum equal to the sum of the magnitudes of an input sound signal for the bins in the sub-band; b) determining the ratio of said input signal sum to said noise sum; and c) estimating a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) the ratio of said input signal sum to said noise sum; and iv) said running average.

Claim 16

Independent Claim 237 words

A method of reducing noise in a communication system, the method comprising: designating a plurality of frequency sub-bands for a signal spectrum of interest; designating a plurality of frequency bins for each of said sub-bands; during an initialization/update mode, determining, for each bin, an average magnitude of noise in said system over a first set of time frames; obtaining, for each sub-band, a noise sum equal to the sum of the average noise magnitudes for the bins in the sub-band; for each of said frames in said first set, a) determining the ratio of noise to said average noise for each bin; b) determining for each sub-band, the maximum ratio of noise to said average noise for the bins therein; determining a running average of said maximum ratio for each sub-band; and during a noise reduction mode, for each frame in a second set of time frames, a) obtaining, for each sub-band, an input signal sum equal to the sum of the magnitudes of an input sound signal for the bins in the sub-band; b) determining the ratio of said input signal sum to said noise sum; and c) estimating a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) the ratio of said input signal sum to said noise sum; and iv) said running average.

Claim 17

Dependent Claim 43 words

The method of claim 12 , wherein operation in said initialization/update mode occurs in response to an indication that speech is not present in the input sound signal, and wherein operation in said noise reduction mode occurs in response to detection of speech.

Claim 18

Dependent Claim 30 words

The method of claim 13 , wherein said estimating function includes a weighted function of said ratio of said input signal sum to said noise sum and said running average.

Claim 19

Dependent Claim 35 words

The method of claim 14 , wherein said weighted function is a minimum function in which said ratio of said input signal sum to said noise sum and said running average are weighted and compared.

Claim 20

Dependent Claim 59 words

The method of claim 15 , wherein said speech signal magnitude estimate is the input sound signal magnitude for the given bin minus a value proportional to the product of said average noise for the bin and the lesser of the weighted values of said ratio of said input signal sum to said noise sum and said running average.

Claim 21

Dependent Claim 32 words

The method of claim 16 , further comprising determining which of the frequency sub-bands contain only noise, and removing by a larger proportion the frequency sub-bands containing only noise from the spectrum.

Claim 22

Independent Claim 210 words

A method of reducing noise in a communication system, the method comprising: designating a plurality of frequency sub-bands for a signal spectrum of interest; designating a plurality of frequency bins for each of said sub-bands; during an initialization/update mode, determining, for each bin, an average magnitude of noise in said system over a first set of time frames; obtaining an indication of noise strength for each sub-band; for each of said frames in said first set, determining a noise deviation for each sub-band by a) determining the ratio of noise to said average noise for each bin; b) determining, for the sub-band, the maximum ratio of noise to said average noise for the bins therein; and during a noise reduction mode, for each frame in a second set of time frames in which an input signal is received, a) obtaining an indication of input signal strength for each sub-band; b) determining a signal-to-noise ratio as the ratio of said input signal strength indication to said noise strength indication; and c) estimating a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) said signal-to-noise ratio; and iv) said noise deviation.

Claim 23

Independent Claim 210 words

A method of reducing noise in a communication system, the method comprising: designating a plurality of frequency sub-bands for a signal spectrum of interest; designating a plurality of frequency bins for each of said sub-bands; during an initialization/update mode, determining, for each bin, an average magnitude of noise in said system over a first set of time frames; obtaining an indication of noise strength for each sub-band; for each of said frames in said first set, determining a noise deviation for each sub-band by a) determining the ratio of noise to said average noise for each bin; b) determining, for the sub-band, the maximum ratio of noise to said average noise for the bins therein; and during a noise reduction mode, for each frame in a second set of time frames in which an input signal is received, a) obtaining an indication of input signal strength for each sub-band; b) determining a signal-to-noise ratio as the ratio of said input signal strength indication to said noise strength indication; and c) estimating a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) said signal-to-noise ratio; and iv) said noise deviation.

Claim 24

Dependent Claim 22 words

the method of claim 18 , wherein said estimating function includes a weighted function of said signal-to-noise ratio and said noise deviation.

Claim 25

Dependent Claim 27 words

The method of claim 19 , wherein said weighted function is a minimum function in which said signal-to-noise ratio and said noise deviation are weighted and compared.

Claim 26

Dependent Claim 44 words

The method of claim 20 , wherein said speech signal magnitude estimate is said input sound signal magnitude minus a value proportional to the product of said average noise and the lesser of the weighted values of said signal-to-noise ratio and said noise deviation.

Claim 27

Dependent Claim 28 words

The method of claim 18 , wherein the determination of said noise deviation includes calculating the running average of the maximum ratio of noise to said average noise.

Claim 28

Dependent Claim 47 words

The method of claim 18 , wherein said input signal strength indication is the sum of the input sound signal magnitudes for the bins in the sub-band, and wherein said noise strength indication is the sum of the average noise magnitudes for the bins in the sub-band.

Claim 29

Dependent Claim 32 words

The method of claim 18 , further comprising determining which of the frequency sub-bands contain only noise, and removing by a larger proportion the frequency sub-bands containing only noise from the spectrum.

Claim 30

Dependent Claim 215 words

An adaptive noise suppression device for a voice communication system, comprising: a signal input; a signal output; and a noise reduction processor connected between said signal input and signal output; wherein, during an initialization/update mode, for a plurality of frequency sub-bands each having a plurality of frequency bins, said processor is adapted to a) determine, for each bin, an average magnitude of noise over a first set of time frames; b) obtain an indication of noise strength for each sub-band; c) for each of said frames in said first set, determine a noise deviation for each sub-band based on the maximum ratio of noise to said average noise for each bin in the sub-band; and wherein, during a noise reduction mode, for each frame in a second set of time frames in which an input signal is received, said processor is adapted to a) obtain an indication of input signal strength for each sub-band; b) determine a signal-to-noise ratio as the ratio of said input signal strength indication to said noise strength indication; and c) estimate a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) said signal-to-noise ratio; and iv) said noise deviation.

Claim 31

Dependent Claim 215 words

An adaptive noise suppression device for a voice communication system, comprising: a signal input; a signal output; and a noise reduction processor connected between said signal input and signal output; wherein, during an initialization/update mode, for a plurality of frequency sub-bands each having a plurality of frequency bins, said processor is adapted to a) determine, for each bin, an average magnitude of noise over a first set of time frames; b) obtain an indication of noise strength for each sub-band; c) for each of said frames in said first set, determine a noise deviation for each sub-band based on the maximum ratio of noise to said average noise for each bin in the sub-band; and wherein, during a noise reduction mode, for each frame in a second set of time frames in which an input signal is received, said processor is adapted to a) obtain an indication of input signal strength for each sub-band; b) determine a signal-to-noise ratio as the ratio of said input signal strength indication to said noise strength indication; and c) estimate a speech signal magnitude for a given bin as a function of i) the input sound signal magnitude for the given bin; ii) said average noise for the given bin; iii) said signal-to-noise ratio; and iv) said noise deviation.

Claim 32

Dependent Claim 24 words

The noise suppression device of claim 25 , wherein said estimating function includes a weighted function of said signal-to-noise ratio and said noise deviation.

Claim 33

Dependent Claim 29 words

The noise suppression device of claim 26 , wherein said weighed function is a minimum function in which said signal-to-noise ratio and said noise deviation are weighted and compared.

Claim 34

Dependent Claim 46 words

The noise suppression device of claim 27 , wherein said speech signal magnitude estimate is said input sound signal magnitude minus a value proportional to the product of said average noise and the lesser of the weighed values of said signal-to-noise ratio and said noise deviation.

Claim 35

Dependent Claim 30 words

The noise suppression device of claim 25 , wherein said processor calculates the running average of the maximum ratio of noise to said average noise to determine said noise deviation.

Claim 36

Dependent Claim 49 words

The noise suppression device of claim 25 , wherein said input signal strength indication is the sum of the input sound signal magnitudes for the bins in the sub-band, and wherein said noise strength indication is the sum of the average noise magnitudes for the bins in the sub-band.

Claim 37

Dependent Claim 35 words

The noise suppression device of claim 25 , wherein said processor determines which of the frequency sub-bands contain only noise, and removes by a larger proportion the frequency sub-bands containing only noise from the spectrum.

Annuity Stage	Window Opens	Payment Deadline	Surcharge Period Until	Estimated Fee	Status
3.5 Years (Year 4)	2010-04-23	2010-10-23	2011-04-24	$2000.00	Window Closed / Lapsed
7.5 Years (Year 8)	2014-04-23	2014-10-23	2015-04-24	$3760.00	Window Closed / Lapsed
11.5 Years (Year 12)	2018-04-23	2018-10-23	2019-04-24	$7700.00	Window Closed / Lapsed

Communication system with adaptive noise suppression

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