Abstract: The invention provides an electronic apparatus. The electronic apparatus includes a casing, an electronic unit, a cable-winding device, a first speaker, and a second speaker. The first speaker is electrically coupled to the electronic unit by a first cable. The second speaker is electrically coupled to the electronic unit by a second cable. When the first speaker and the second speaker are respectively associated with a first recess and a second recess, the first cable and the second cable are wound back in the cable-winding device, and the electronic unit is capable of broadcasting an audio signal at a first power via the first speaker and the second speaker; when the first speaker and the second speaker are pulled out of the casing, the electronic unit is capable of broadcasting the audio signal at a second power via the first speaker and the second speaker.

Abstract: An electronic device can be operated to detect noise, such as wind noise. A microphone signal is generated by a microphone. Autocorrelation coefficients are determined based on the microphone signal. Gradient values are determined from the autocorrelation coefficients.

Abstract: A sound input from sound sources existing in a plurality of directions is accepted and converted into a signal on a frequency axis. A suppressing function to suppress the converted signal on a frequency axis is computed, an amplitude component of a signal on a frequency axis is multiplied by the computed suppressing function and the converted signal on a frequency axis is corrected. A phase component of each converted signal on a frequency axis is computed for each frequency and a difference of phase components is computed. A probability value indicative of probability of existence of a sound source in a predetermined direction is specified based on the computed difference and a suppressing function to suppress a sound input from a sound source other than a sound source in a predetermined direction is computed based on the specified probability value.

Abstract: An amplitude suppression quantity denoting a noise suppression level of a current frame is calculated in an amplitude suppression quantity calculating unit (20), a perceptual weight distributing pattern of both a spectral subtraction quantity and a spectral amplitude suppression quantity is determined in a perceptual weight pattern adjusting unit (21), the spectral subtraction quantity and the spectral amplitude suppression quantity given by the perceptual weight distributing pattern are corrected according to a frequency band SN ratio in a perceptual weight correcting unit (7), a noise subtracted spectrum is calculated from an amplitude spectrum, a noise spectrum and a corrected spectral subtraction quantity in a spectrum subtracting unit (8), and a noise suppressed spectrum is calculated from the noise subtracted spectrum and a corrected spectral amplitude suppression quantity in a spectrum suppressing unit (9).

Abstract: A method and apparatus for de-noising weak bio-signals having a relatively low signal to noise ratio utilizes an iterative process of de-noising a data set comprised of a new set of frames. The method separately performs a non-linear de-noising operation on each of the component frames and combines the resultant de-noised frames to form a combined resultant de-noised input signal. The method is preferably carried out in a digital processor.

Abstract: A method is presented for eliminating an unwanted signal (e.g., background music, interference, etc.) from a mixture of a desired signal and the unwanted signal via time-frequency masking. Given a mixture of the desired signal and the unwanted signal, the goal of the present invention is to eliminate or at least reduce the effects of the unwanted signal to obtain an estimate of the desired signal.

Abstract: Techniques for enhancing the sound quality of computer telephony systems are provided. In general, digital signals including telephony sounds are converted from the time domain to the frequency domain. If noise is detected in the frequency domain conversion of the digital signals, the noise is removed utilizing a filter. The noise detection and filtering can be performed in software so that enhanced audio quality can be achieved at a relatively low cost and with flexibility for very diverse environments.

Abstract: A system and method are disclosed for enhancing audio signals by nonlinear spectral operations. Successive portions of the audio signal are processed using a subband filter bank. A nonlinear modification is applied to the output of the subband filter bank for each successive portion of the audio signal to generate a modified subband filter bank output for each successive portion. The modified subband filter bank output for each successive portion is processed using an appropriate synthesis subband filter bank to construct a modified time-domain audio signal. High modulation frequency portions of the audio signal may be emphasized or de-emphasized, as desired. The modification may be applied within one or more frequency bands.

Abstract: A gain adjusting method and a gain adjusting device for adjusting gain of a processed voice signal that is obtained by signal processing an input voice signal are disclosed. According to the gain adjusting method, a masking property of the processed voice signal is computed, and gain is adjusted for every frequency if the frequency is masked according to the masking property, while canceling a difference between the processed voice signal and the input voice signal where the frequency is not masked.

Abstract: Embodiments of a multiple-input multiple-output (MIMO) communication system and methods for beamforming using polar-cap codebooks are generally described herein. Other embodiments may be described and claimed. In some embodiments, beamforming is based on codewords of a polar-cap codebook which represents deviations in the channel with respect to codewords of a full-manifold codebook.

Abstract: A first band analyzer divides an acoustic signal received from a sound playback system through an input unit into frequency bands, and generates a first band level. An acoustic signal estimator estimates the band level of the original acoustic signal at the input unit, and generates a second band level for each band. A processor extracts an external noise component which is contained in the acoustic signal using the first band level and the second band level. The external noise can be accurately estimated with less computation than in the related art.

Abstract: The present invention provides method and apparatus that improve processing of acoustic signals by reducing acoustic feedback in an acoustic system. An aspect of the invention is a multi-channel digital feedback reducer (DFR) system that comprises a plurality of channel elements. Each channel element comprises a notch filter configuration having an adaptive notch filter and an operative notch filter. The operative notch filter processes a signal received from an acoustic input device and provides the processed signal to an acoustic output device, in which acoustic feedback between the acoustic input device and the acoustic output device is ameliorated. If acoustic feedback is detected by a channel element, the channel element informs other channel elements of the multi-channel DFR system about the detected feedback to ensure that all channel elements may incorporate the same notch filters. During the notification, the other channel elements may continue searching for feedback on the associated channels.

Abstract: The disclosure includes description of a method of noise reduction according to one possible implementation. An audio signal is sampled at a sample rate f. The audio signal is converted to a digital signal in the time domain. For each of a series of frames of time, the digital signal in the time domain is converted to a digital signal in frequency domain for the frame of time. The converting includes determining a set of frequency domain values. The frequency domain values in the set are created by a set of digital filters, and the digital filters are related to each other by a constant ratio of filter bandwidth to center frequency, related to a perceptual scale for audio processing. A set of minimum magnitude frequency domain values is obtained. These values include, at each frequency represented by the frequency domain values, a frequency domain value having a minimum magnitude from among frequency domain values for such frequency over a time interval spanning multiple frames of time.

Abstract: A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal.

Abstract: A signal encoding apparatus (10) limits an inputted time series signal to a low frequency band signal having a certain cut-off frequency or less to include the low frequency band signal into code train for outputting encoded low frequency band code train. In addition, the signal encoding apparatus (10) adaptively determines aliasing frequency fa, shift frequency fsh or tone•noise synthesis information r used for generation of high frequency band signal at the decoding side to include these information into code train outputted along with high frequency band spectrum envelope information as high frequency band generation information.

Abstract: A howling control apparatus and howling control method for controlling time up to the cancellation of howling suppression according to a howling occurrence situation, thereby eliminating the repetition of howling suppression and cancellation. A howling detecting section (104) detects howling based on the band level and the band level average value and measures time for which no howling occurs, a waiting time setting section (105) decides waiting time to be set this time from time for which no howling occurs and a previous waiting time, and a gain control section (106) causes a gain that is set to a howling suppressing section (107) to be retuned to a normal value during the waiting time.

Abstract: Techniques are provided to suppress noise and interference using an array microphone and a combination of time-domain and frequency-domain signal processing. In one design, a noise suppression system includes an array microphone, at least one voice activity detector (VAD), a reference generator, a beam-former, and a multi-channel noise suppressor. The array microphone includes multiple microphones—at least one omni-directional microphone and at least one uni-directional microphone. Each microphone provides a respective received signal. The VAD provides at least one voice detection signal used to control the operation of the reference generator, beam-former, and noise suppressor. The reference generator provides a reference signal based on a first set of received signals and having desired voice signal suppressed. The beam-former provides a beam-formed signal based on a second set of received signals and having noise and interference suppressed.

Abstract: An adaptive noise suppression system includes an input A/D converter, an analyzer, a filter, and a output D/A converter. The analyzer includes both feed-forward and feedback signal paths that allow it to compute a filtering coefficient, which is input to the filter. In these paths, feed-forward signal are processed by a signal to noise ratio estimator, a normalized coherence estimator, and a coherence mask. Also, feedback signals are processed by a auditory mask estimator. These two signal paths are coupled together via a noise suppression filter estimator. A method according to the present invention includes active signal processing to preserve speech-like signals and suppress incoherent noise signals. After a signal is processed in the feed-forward and feedback paths, the noise suppression filter estimator then outputs a filtering coefficient signal to the filter for filtering the noise out of the speech and noise digital signal.

Abstract: In correcting the sound field, the loudspeakers 6FL to 6WF are sounded by the noise. The attenuation factors of the inter-band attenuators ATF11 to ATFki for adjusting gains of the band-pass filters BPF11 to BPFki to the frequency in respective channels are corrected based on detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. Then, the attenuation factors of the channel-to-channel attenuators ATG1 to ATG5 are corrected based on the detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. Then, the delay times of the delay circuits DLY1 to DLY5 are corrected based on the detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. Then, the attenuation factor of the channel-to-channel attenuator ATGk is corrected based on the detection result of the reproduced sound of the loudspeaker 6WF as the subwoofer, whereby the levels of the reproduced sounds reproduced by the loudspeakers 6FL to 6WF are adjusted to be made flat over the audio frequency band.

Abstract: In the noise suppression apparatus, a spectrum correction gain calculation unit calculates the noise amplitude spectrum correction gain and the noise removal spectrum correction gain using the input amplitude spectrum, noise amplitude spectrum and respective coefficients; a spectrum deduction unit deducts the product of the noise amplitude spectrum and the noise amplitude spectrum correction gain from the input amplitude spectrum and outputs the result as a first noise removal spectrum; a spectrum suppression unit multiplies the first noise removal spectrum by the noise removal spectrum correction gain and outputs the result as a second noise removal spectrum; finally a frequency/time conversion unit converts the second noise removal spectrum into a time domain signal.

Abstract: A method for reducing noise in a voice signal, and a voice operated system utilizing the same are presented. A noise component in a compressed digital signal representative of the voice signal is determined, and subtracted from the compressed digital signal.

Abstract: A multichannel source activity detection system, e.g., a voice activity detection (VAD) system, and method that exploits spatial localization of a target audio source is provided. The method includes the steps of receiving a mixed sound signal by at least two microphones; Fast Fourier transforming each received mixed sound signal into the frequency domain; filtering the transformed signals to output a signal corresponding to a spatial signature of a source; summing an absolute value squared of the filtered signal over a predetermined range of frequencies; and comparing the sum to a threshold to determine if a voice is present. Additionally, the filtering step includes multiplying the transformed signals by an inverse of a noise spectral power matrix, a vector of channel transfer function ratios, and a source signal spectral power.

Abstract: A system and method facilitating signal enhancement utilizing mixture models is provided. The invention includes a signal enhancement adaptive system having a speech model, a noise model and a plurality of adaptive filter parameters. The signal enhancement adaptive system employs probabilistic modeling to perform signal enhancement of a plurality of windowed frequency transformed input signals received, for example, for an array of microphones. The signal enhancement adaptive system incorporates information about the statistical structure of speech signals. The signal enhancement adaptive system can be embedded in an overall enhancement system which also includes components of signal windowing and frequency transformation.

Abstract: In the MPEG2 Advanced Audio Coder (AAC) standard, Temporal Noise Shaping (TNS) is currently implemented by defining one filter for a given frequency band, and then switching to another filter for the adjacent frequency band when the signal structure in the adjacent band is different than the one in the previous band. The AAC standard limits the number of filters used to either one filter for a “short” block or three filters for a “long” block. In cases where the need for additional filters is present but the limit of permissible filters has been reached, the remaining frequency spectra are simply not covered by TNS. This current practice is not an effective way of deploying TNS filters for most audio signals. We propose two solutions to deploy TNS filters in order to get the entire spectrum of the signal into TNS. The first method involves a filter bridging technique and complies with the current AAC standard. The second method involves a filter clustering technique.

Abstract: A self-adaptive graphic equalizer operable to equalize the affects of an audio system on an audio signal includes an adaptive graphic equalizer having a plurality of equalizing filters, where the plurality of equalizing filters have different center frequencies equidistant from one another and spanning a predetermined audio bandwidth. Each equalizing filter is operable to filter an ith sub-band of the audio signal. A plurality of first filters are coupled to the audio system, each first filter is operable to filter an ith sub-band of an output signal of the audio system. A plurality of second filters are operable to filter an ith sub-band of the audio signal. A gain adjuster is operable to adjust the ith sub-band of the adaptive graphic equalizer in response to a difference in the ith sub-band of the filtered output signal from the plurality of first filters and the ith sub-band of the filtered audio signal from the plurality of second filters.

Abstract: A method and apparatus for de-noising weak bio-signals having a relatively low signal to noise ratio utilizes an iterative process of de-noising a data set comprised of a new set of frames. The method separately performs a non-linear de-noising operation on each of the component frames and combines the resultant de-noised frames to form a combined resultant de-noised input signal. The method is preferably carried out in a digital processor.

Abstract: A method and apparatus for de-noising weak bio-signals having a relatively low signal to noise ratio utilizes an iterative process of wavelet de-noising a data set comprised of a new set of frames of wavelet coefficients partially generated through a cyclic shift algorithm. The method preferably operates on a data set having 2N frames, and the iteration is performed N?1 times. The resultant wavelet coefficients are then linearly averaged and an inverse discrete wavelet transform is performed to arrive at the de-noised original signal. The method is preferably carried out in a digital processor.

Abstract: A noise suppressor device for attaining perceptually preferable noise suppression is disclosed. The device minimizes reduction in quality even in the presence of increased noises. The device is adaptable for use in voice communications systems and speech recognition systems employed in a variety of kinds of noisy environments. The device includes a spectrum subtracter and a spectrum amplitude suppressor that operate on the basis of perceptual weights.

Abstract: A method for noise suppression is described, wherein noisy input signals in a multiple input audio processing device are subjected to adaptations and summed and wherein the noise frequency components of the noisy input signals in the summed input signals are estimated based on individually kept noise frequency components and on said adaptations. Advantageously the method may be applied if a spectral subtraction like technique is applied in a multi input beamformer. Only one spectral frequency transformation is necessary, which reduces the number of necessary calculations.

Abstract: The present invention relates to a method of automatically setting each of frequencies in each of a plurality of wireless microphone-receivers simultaneously used in the same area, based on the combinations of simultaneously usable frequencies. Each of microphone-receivers 10A to 10N is mutual-communicatably connected by a connecting cable CA. One and the other microphone-receivers are designated as a master microphone-receiver 10A and slave microphone-receivers 10B to 10N, respectively. First, an empty channel-information is sent from the master microphone-receiver 10A to a first slave microphone-receiver 10B and the frequency of the empty channel-information is set in the first slave microphone-receiver 10B. The empty channel-information is renewed in the master microphone-receiver.

Abstract: The present invention relates to a method with which speech is captured in a noisy environment with as high a speech quality as possible. To this end, a compact array of, for example, two single microphones is combined to form one system through signal processing methods consisting of adaptive beam formation and spectral subtraction. Through the combination with a spectral subtraction, the reference signal of the beam former is freed from speech signal components to the extent that a reference signal of the interference is formed and the beam former produces high gains.

Abstract: To improve the speech comprehensibility given treatment with a hearing aid device, during the operation of the hearing aid device speech signal levels and noise signal levels are determined in a plurality of frequency bands of an input signal. An automatic adjustment of the amplification follows, dependent on the determined signal level and the signal frequency. The determination of amplification parameters thereby ensues under inclusion of a loudness model and a speech comprehensibility model.

Abstract: Techniques for canceling echo and suppressing noise using an array microphone and signal processing. In one system, at least two microphones form an array microphone and provide at least two microphone input signals. Each input signal may be processed by an echo canceller unit to provide a corresponding intermediate signal having some echo removed. An echo cancellation control unit receives the intermediate signals and derives a first gain used for echo cancellation. A noise suppression control unit provides at least one control signal used for noise suppression based on background noise detected in the intermediate signals. An echo cancellation and noise suppression unit derives a second gain based on the control signal(s), cancels echo in a designated intermediate signal based on the first gain, and suppresses noise in this intermediate signal based on the second gain. The signal processing may be performed in the frequency domain.

Abstract: A method and apparatus for speaker recognition is provided that matches the noise in training data to noise in testing data using spectral addition. Under spectral addition, the mean and variance for a plurality of frequency components are adjusted in the training data and the test data so that each mean and variance is matched in a resulting matched training signal and matched test signal. The adjustments made to the training data and test data add to the mean and variance of the training data and test data instead of subtracting from the mean and variance.

Abstract: Disclosed is an apparatus for cancelling far endpoint echo signals in audio signals transmitted from a near endpoint to a far endpoint. In one embodiment, the apparatus includes a near endpoint analysis filter bank operable to divide a near endpoint signal into a plurality of near endpoint subband signals, a far endpoint analysis filter bank operable to divide a far endpoint signal into a plurality of far endpoint subband signals, and a background signal power estimator operable to determine background noise at the near end.

Abstract: A speech processing apparatus and method are provided for processing an input speech signal to compensate for the effects of noise in the input speech signal. The method and apparatus divide the input speech signal into a plurality of sequential time frames and a set of spectral parameters are extracted for each time frame, which parameters are representative of the input signal during the time frame. The system then processes the input speech by scaling the parameters for each frame in dependence upon a measure of the signal to noise ratio for the input frame. In this way, the effects of additive noise on the input signal can be reduced.

Abstract: An apparatus comprising an input, a noise cancellation circuit, an audio circuit and a mixing circuit. The input may be configured to receive one or more input signals. The noise cancellation circuit may be configured to generate a first processed audio signal having reduced noise in response to the input signals. The audio circuit may be configured to generate a second audio signal from a digital source. The mixing circuit may mix the processed audio signal and the second audio signals to generate an output signal.

Abstract: A method and system for reducing the undesirable noise in a communication signal is provided. Designed specifically to address the problem of telephone communications where the desired speech signal is contaminated by background noise, this invention employs digital signal processing of the communication signal to selectively emphasize, buffer, amplify, and smooth the components of the signal, thereby enhancing the signal quality (signal to noise ratio) of the presented communication signal.

Abstract: In correcting the sound field, loudspeakers 6FL to 6WF are sounded by the noise. The attenuation factors of the inter-band attenuators ATF11 to ATFki for adjusting gains of the band-pass filters BPF11 to BPFki to the frequency in respective channels are corrected based on detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. The attenuation factors of channel-to-channel attenuators ATG1 to ATG5 are corrected based on the detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. The delay times of delay circuits DLY1 to DLY5 are corrected based on the detection results of the reproduced sounds of the loudspeakers 6FL to 6WF. The attenuation factor of a channel-to-channel attenuator ATGk is corrected based on the detection result of the reproduced sound of the loudspeaker 6WF as the subwoofer. Therefore, the levels of the reproduced sounds reproduced by the loudspeakers 6FL to 6WF are adjusted to be made flat over the audio frequency band.

Abstract: Disclosed is a method of denoising signal mixtures so as to extract a signal of interest, the method comprising receiving a pair of signal mixtures, constructing a time-frequency representation of each mixture, constructing a pair of histograms, one for signal-of-interest segments, the other for non-signal-of-interest segments, combining said histograms to create a weighting matrix, rescaling each time-frequency component of each mixture using said weighting matrix, and resynthesizing the denoised signal from the reweighted time-frequency representations.

Abstract: A sound masking system for a multi-occupant work area includes a masking signal generator generating incoherent masking sound signals loudspeaker modules interconnected in a daisy-chain fashion, with each loudspeaker module receiving the masking sound signals on input connections and transmitting them to a successive loudspeaker module on output connections. The connections on which the masking sound signals appear in each loudspeaker are shifted by the inter-loudspeaker connections, such that successive loudspeakers automatically emit different masking sound signals for improved diffuseness in the overall masking sound in the work area. Each loudspeaker module has one jack having the input connections and another jack having the output connections, and each jack receives a detachable cable such as telephone cable to connect adjacent loudspeaker modules. The masking sound signals are shifted by a cross connection network between the two jacks in each loudspeaker module.

Abstract: The invention relates to a process and a system for voice recognition in a noisy signal. In a preferred embodiment, the system (2) comprises modules for detecting speech (30) and for formulating a noise model (31), a module (40) for quantifying the energy level of the noise and for comparing with preestablished energy spans, a parameterization pathway (5) comprising an optional denoising module (51), with Wiener filter, a module (52) for calculating the spectral energy in Bark windows, a module (50, 530) for applying a configuration of shift values (531), by adding these values to the Bark coefficients, as a function of the quantification (40), so as to modify the parameterization, a module (54) for calculating vectors of parameters, and a block (6) for recognizing shapes, performing the voice recognition by comparison with vectors of parameters prerecorded during a learning phase.

Abstract: Dividing devices are provided for dividing an input information signal into a plurality of frequency bands, and a level detector is provided for detecting a level of a noise component of the information signal divided by the dividing device. A plurality of thresholds corresponding to the divided information signals are stored in a memory. One or more thresholds are selected from the threshold stored in the memory based on a detected result by the level detector. Attenuators are provided for comparing the information signals with a selected threshold and for attenuating an information signal the level of which is lower than the selected threshold.

Abstract: An input audio signal is analyzed to determine a power spectral density profile and the power spectral density profile is compared with at least one template profile. On the basis of the comparison, frequency bands of the input audio signal are selectively attenuated.

Abstract: A spectral enhancement system is disclosed that includes an input node for receiving an input signal, at least one broad band pass filter coupled to the input node and having a first band pass range, at least one non-linear circuit coupled to the filter for non-linearly mapping a broad band pass filtered signal by a first non-linear factor n, at least one narrow band pass filter coupled to the non-linear circuit and having a second band pass range that is narrower than the first band pass range, and an output node coupled to the narrow band pass filter for providing an output signal that is spectrally enhanced.

Abstract: A band-dividing unit is operable to extract a low frequency component from an input signal in order to generate overtones based on the extracted low frequency component, and is further operable to divide the extracted low frequency component into signals that belongs to different frequency bands. Each of overtone-generating units is disposed for corresponding one of the different frequency bands, and is operable to generate overtones based on an output signal from corresponding one of band pass filters. An adder adds the generated overtones to the input signal that has passed through a delay. The resulting acoustic signal is sent to the outside through a high-pass filter. One overtone-generating unit designed for a higher frequency band among the different frequency bands is set to produce the same or fewer overtones than another overtone-generating unit suited for a lower frequency band thereamong does.

Abstract: Method of suppressing audible noise in speech transmission by means of a multi-layer self-organizing fed-back neural network comprising a minima detection layer, a reaction layer, a diffusion layer and an integration layer, said layers defining a filter function F(f,T) for noise filtering.

Abstract: Initially, voice signal components (4) are extracted from the audio signal (1) in a procedure for determining a measure of quality (2) of an audio signal (1). Based on this signal, a reference signal (6) is then generated by means of noise suppression (7) and interruption interpolation (8). This signal is compared with the voice signal (4) and an intrusive quality value (10) is determined in this way. A further quality value (15) is determined by establishing and evaluating (12, 14) codec-related signal distortions in the voice signal (4). Another quality value (17) is generated from the information relating to the detected signal interruptions (8). The measure of quality (2) is finally determined as a linear combination (16) of the various quality values (10, 15, 17, 18).

Abstract: A signal processor for reducing undesirable signal content reduces the undesirable signal content by exaggerating the undesirable signal content and then using this exaggerated undesirable signal and adaptive filter means to estimate the undesirable content in the signal and then substantially removing it from the signal. The signal processor includes a signal mapping means for exaggerating the undesirable signal content; and an adaptive filter means for reducing the undesirable signal content using the exaggerated undesirable signal content.

Abstract: A method and apparatus for generating a noise-reduced feature vector representing human speech are provided. Speech data representing an input speech waveform are first input and filtered. Spectral energies of the filtered speech data are determined, and a noise reduction process is then performed. In the noise reduction process, a spectral magnitude is computed for a frequency index of multiple frequency indexes. A noise magnitude estimate is then determined for the frequency index by updating a histogram of spectral magnitude, and then determining the noise magnitude estimate as a predetermined percentile of the histogram. A signal-to-noise ratio is then determined for the frequency index. A scale factor is computed for the frequency index, as a function of the signal-to-noise ratio and the noise magnitude estimate. The noise magnitude estimate is then scaled by the scale factor.