A method of speech signal compression, by variable rate coding of frames of digitized speech samples, comprising the steps of: determining a level of speech activity for a frame of digitized speech samples; selecting an encoding rate from a set of rates based upon said determined level of speech activity within said frame; coding said frame according to a predetermined coding format for said selected rate wherein each rate has a corresponding different coding format; providing for said frame a corresponding output data packet at said selected rate.

Variable rate vocoder

Apparatus for reducing acoustic background noise for use with a telephone handset (10) or a boom microphone device (100) or a boom headset (401) or the like. The apparatus includes first (12) and second (14) microphones which are arranged such that the first microphone (12) receives a desired speech input and the background noise present in the vicinity of the speech, and the second microphone (14) receives substantially only the background noise. The background noise from the second microphone (14) is converted into a corresponding electrical signal and substracted (16) from a signal corresponding to the speech and background noise obtained from the first microphone (12) so as to produce a signal representing substantially the speech.

Noise cancellation apparatus

A hearing compensation system for the hearing impaired comprises a plurality of bandpass filters having an input connected to an input transducer and each bandpass filter having an output connected to the input of one of a plurality of multiplicative AGC circuits whose outputs are summed together and connected to the input of an output transducer. The multiplicative AGC circuits attenuate acoustic signals having a constant background level without the loss of speech intelligibility. The identification of the background noise portion of the acoustic signal is made by the constancy of the envelope of the input signal in each of the several frequency bands. The background noise that will be suppressed includes multi-talker speech babble, fan noise, feedback whistle, fluorescent light hum, and white noise.

Hearing aid device incorporating signal processing techniques

A hearing aid system utilizes digital signal processing to correct for the hearing deficit of a particular user and to maximize the intelligibility of the desired audio signal relative to noise. An analog signal from a microphone is converted to digital data which is operated on by a digital signal processor, with the output of the digital signal processor being converted back to an analog signal which is amplified and provided to the user. The digital signal processor includes a time varying spectral filter having filter coefficients which can be varied on a quasi-real time basis to spectrally shape the signal to match the hearing deficit of the user and to accommodate ambient signal and noise levels. The coefficients of the spectral filter are determined by estimating the energy in several frequency bands within the frequency range of the input signal, and using those energy estimates to calculate desired gains for the frequency bands and corresponding spectral filter coefficients. The spectral energy analysis may be carried out using pairs of high pass and low pass digital filters in cascade relation, with the output of each low pass filter being provided to the next pair of high pass and low pass filters. The rate at which output data is provided from the filters in each pair may be reduced from the sample rate of input data by one half for succeeding pairs of filters in the cascade to thereby reduce the computation time required.

Adaptive, programmable signal processing and filtering for hearing aids

A spectral subtraction noise suppression method in a frame based digital communication system is described. Each frame includes a predetermined number N of audio samples, thereby giving each frame N degrees of freedom. The method is performed by a spectral subtraction (150) function H(φ) which is based on an estimate (140) Ζv(φ) of the power spectral density of background noise of non-speech frames and an estimate (130) Ζx(φ) of the power spectral density of speech frames. Each speech frame is approximated (120) by a parametric model that reduces the number of degrees of freedom to less than N. The estimate Ζx(φ) of the power spectral density of each speech frame is estimated (130) from the approximative parametric model.

Spectral subtraction noise suppression method

An improved noise suppression system (400) is disclosed which performs speech quality enhancement upon speech-plus-noise signal available at the input (205) to generate a clean speech signal at the output (265) by spectral gain modification. The noise suppression system of the present invention includes a background noise estimator (420) which generates and stores an estimate of the background noise power spectral density based upon pre-processed speech (215), as determined by the detected minima of the post-processed speech energy level. This post-processed speech (255) may be obtained directly from the output of the noise suppression system, or may be simulated by multiplying the pre-processed speech energy (225) by the channel gain values of the modification signal (245). This technique of implementing post-processed signal to generate the background noise estimate (325) provides a more accurate measurement of the background noise energy since it is based upon much cleaner speech signal. As a result, the present invention performs acoustic noise suppression in high ambient noise backgrounds with significantly less voice quality degradation.

Noise suppression system

An improved noise suppression system (800) is disclosed which performs speech quantity enhancement upon the speech-plus-noise signal available at the input (205) to generate a clean speech signal at the output (265) by spectral gain modification. The improvements of the present invention include the addition of a signal-to-noise ratio (SNR) threshold mechanism (830) to reduce background noise flutter by offsetting the gain rise of the gain tables until a certain SNR threshold is reached, the use of a voice metric calculator (810) to produce more accurate background noise estimates via performing the update decision based on the overall voice-like characteristics in the channels and the time interval since the last update, and the use of a channel SNR modifier (820) to provide immunity to narrowband noise bursts through modification of the SNR estimates based on the voice metric calculation and the channel energies.

Joseph Barlo

Papers

Noise suppression system

Improved noise suppression system