Abstract: Implementations include systems, methods and/or devices operable to enhance the intelligibility of a target speech signal by targeted voice model based processing of a noisy audible signal. In some implementations, an amplitude-independent voice proximity function voice model is used to attenuate signal components of a noisy audible signal that are unlikely to be associated with the target speech signal and/or accentuate the target speech signal. In some implementations, the target speech signal is identified as a near-field signal, which is detected by identifying a prominent train of glottal pulses in the noisy audible signal.

Abstract: A dual omnidirectional microphone array noise suppression is described. Compared to conventional arrays and algorithms, which seek to reduce noise by nulling out noise sources, the array of an embodiment is used to form two distinct virtual directional microphones which are configured to have very similar noise responses and very dissimilar speech responses. The only null formed is one used to remove the speech of the user from V2. The two virtual microphones may be paired with an adaptive filter algorithm and VAD algorithm to significantly reduce the noise without distorting the speech, significantly improving the SNR of the desired speech over conventional noise suppression systems.

Abstract: A dual omnidirectional microphone array noise suppression is described. Compared to conventional arrays and algorithms, which seek to reduce noise by nulling out noise sources, the array of an embodiment is used to form two distinct virtual directional microphones which are configured to have very similar noise responses and very dissimilar speech responses. The only null formed is one used to remove the speech of the user from V2. The two virtual microphones may be paired with an adaptive filter algorithm and VAD algorithm to significantly reduce the noise without distorting the speech, significantly improving the SNR of the desired speech over conventional noise suppression systems.

Abstract: A dual omnidirectional microphone array noise suppression is described. Compared to conventional arrays and algorithms, which seek to reduce noise by nulling out noise sources, the array of an embodiment is used to form two distinct virtual directional microphones which are configured to have very similar noise responses and very dissimilar speech responses. The only null formed is one used to remove the speech of the user from V2. The two virtual microphones may be paired with an adaptive filter algorithm and VAD algorithm to significantly reduce the noise without distorting the speech, significantly improving the SNR of the desired speech over conventional noise suppression systems.

Abstract: A method (400, 500) and apparatus (220) seeks to improve the intelligibility of speech emitted into a noisy environment. Formants are identified (426) and perceptual frequency scale band is selected (502) that includes at least one of the identified formants. The SNR in each band is compared (504) to a threshold and, if the SNR for that band is less than the threshold, the method increases a formant enhancement gain for that band. A set of high pass filter gains (338) is combined (516) with the formant enhancement gains yielding combined gains that are then clipped (518), scaled (520) according to a total SNR, normalized (526), smoothed across time (530) and frequency (532), and used to reconstruct (532, 534) an audio signal.

Abstract: A method, system and machine readable medium for noise reduction is provided. The method includes: (1) receiving a noise corrupted signal; (2) transforming the noise corrupted signal to a time-frequency domain representation; (3) determining probabilistic bases for operation, the probabilistic bases being priors in a multitude of frequency bands calculated online; (4) adapting longer term internal states of the method; (5) calculating present distributions that fit data; (6) generating non-linear filters that minimize entropy of speech and maximize entropy of noise, thereby reducing the impact of noise while enhancing speech; (7) applying the filters to create a primary output in a frequency domain; and (8) transforming the primary output to the time domain and outputting a noise suppressed signal.

Abstract: A noise reduction system and a noise reduction method are provided. The noise reduction system comprises a uni-directional microphone, an omni-directional microphone and a signal processing module. The signal processing module comprises an adaptive noise control (ANC) unit, a main noise reduction unit and an optimizing unit. The uni-directional microphone senses a first audio source to output a first audio signal, and the omni-directional microphone senses a second audio source to output a second audio signal. The ANC unit executes an adaptive noise control to output an estimated signal according to the first audio signal and the second audio signal. The main noise reduction unit executes a main noise reduction process to output a de-noise speech signal according to the estimated signal and the second audio signal. The optimizing unit executes an optimizing process to output an optimized speech signal according to the de-noise speech signal.

Abstract: An apparatus processes an acoustic input signal to provide an output signal with reduced noise. The apparatus weights the input signal based on a frequency-dependent weighting function. A frequency-dependent threshold function bounds the weighting function from below.

Abstract: Described herein are multi-channel noise suppression systems and methods that are configured to detect and suppress wind and background noise using at least two spatially separated microphones: at least one primary speech microphone and at least one noise reference microphone. The multi-channel noise suppression systems and methods are configured, in at least one example, to first detect and suppress wind noise in the input speech signal picked up by the primary speech microphone and, potentially, the input speech signal picked up by the noise reference microphone. Following wind noise detection and suppression, the multi-channel noise suppression systems and methods are configured to perform further noise suppression in two stages: a first linear processing stage that includes a blocking matrix and an adaptive noise canceler, followed by a second non-linear processing stage.

Abstract: A device for improving the intelligibility of a signal arising from a source subjected to a noisy environment, said source marking the signal with a specific signature, the device comprising a processing circuit receiving the signal; and means for analyzing the signal and parameterizing the processing circuit according to characteristics of the signature present in the signal. A first channel with low distortion conveys the signal from the source to the means for analyzing, and a second channel, susceptible to introduce a distortion, conveys the signal from the source to the processing circuit.

Abstract: Provided are a method and an apparatus for acquiring a multi-channel sound by using a microphone array. The method estimates positions of sound sources corresponding to sound source signals, which are mixed together, from the sound source signals input via a microphone array; and generates a multi-channel sound source signal by compensating for the sound source signals, based on differences between the estimated positions of the sound sources and a position of a virtual microphone array substituting for the microphone array. By doing so, the multi-channel sound having a stereoscopic effect can be acquired from a plurality of distant sound source signals which are input via the microphone array from a portable sound acquisition device.

Abstract: A triangular microphone assembly (101) for use in a vehicle accessory includes a mirror housing (106) adapted for attachment to the interior of the vehicle. A mirror is disposed in an opening of the mirror housing (106) and a plurality of virtual digital microphones (108a, 108b, 108c) are arranged in a substantially triangular configuration in the mirror housing (106). A digital signal processor (DSP) (537) is used for receiving signals from the plurality of digital microphones (108a, 108b, 108c) such that the digital microphones exhibit directional characteristics for reducing undesirable noise in at least one direction by normalizing the phase of the received signals as a function of signal frequency.

Abstract: A VOX interface is provided that interfaces with at least two communication paths to two separate devices. One communication path may be to a first electronic device, such as a central monitoring station remote from the VOX interface, and another communication path may be to one or more remote devices, such as to one or more patient devices remote from the VOX interface. The VOX interface may determine which of the communication paths is sending a signal (such as an audio signal), and configure the VOX interface (via one or more switches) to pass the signal through. Specifically, the VOX interface may sense signals indicating the presence of audio from a central station audio bus and the patient station bus, may do some background noise filtering on the signals, and may pass these filtered values through a differentiator circuit to determine which bus presented the audio.

Abstract: A noise reduction system and a noise reduction method are provided. The noise reduction system comprises a uni-directional microphone, an omni-directional microphone and a signal processing module. The signal processing module comprises an adaptive noise control (ANC) unit, a main noise reduction unit and an optimizing unit. The uni-directional microphone senses a first audio source to output a first audio signal, and the omni-directional microphone senses a second audio source to output a second audio signal. The ANC unit executes an adaptive noise control to output an estimated signal according to the first audio signal and the second audio signal. The main noise reduction unit executes a main noise reduction process to output a de-noise speech signal according to the estimated signal and the second audio signal. The optimizing unit executes an optimizing process to output an optimized speech signal according to the de-noise speech signal.

Abstract: An audio decoding device of the present invention includes: a decoding unit decoding a stream to a spectrum coefficient, and outputting stream information when a frame included in the stream cannot be decoded; an orthogonal transformation unit transforming the spectrum coefficient to a time signal; a correction unit generating a correction time signal based on an output waveform within a reference section that is in a section that overlaps between an error frame section to which the stream information is outputted and an adjacent frame section and that is a section in the middle of the adjacent frame section, when the decoding unit outputs the stream information: and an output unit generating the output waveform by synthesizing the correction time signal and the time signal.

Abstract: A noise reduction system and a method of noise reduction includes a microphone array comprising a first microphone, a second microphone, and a third microphone. Each microphone has a known position and a known directivity pattern. An instantaneous direction-of-arrival (IDOA) module determines a first phase difference quantity and a second phase difference quantity. The first phase difference quantity is based on phase differences between non-repetitive pairs of input signals received by the first microphone and the second microphone, while the second phase difference quantity is based on phase differences between non-repetitive pairs of input signals received by the first microphone and the third microphone. A spatial noise reduction module computes an estimate of a desired signal based on a priori spatial signal-to-noise ratio and an a posteriori spatial signal-to-noise ratio based on the first and second phase difference quantities.

Abstract: In an automatic speech recognition system, a feature extractor extracts features from a speech signal, and speech is recognized by the automatic speech recognition system based on the extracted features. Noise reduction as part of the feature extractor is provided by feature enhancement in which feature-domain noise reduction in the form of Mel-frequency cepstra is provided based on the minimum means square error criterion. Specifically, the devised method takes into account the random phase between the clean speech and the mixing noise. The feature-domain noise reduction is performed in a dimension-wise fashion to the individual dimensions of the feature vectors input to the automatic speech recognition system, in order to perform environment-robust speech recognition.

Abstract: A post-filtering apparatus and method for speech enhancement in a modified discrete cosine transform (MDCT) domain are disclosed. In the apparatus and method, previous and current MDCT coefficients are used for obtaining a speech spectrum coefficient similar to a real speech spectrum, and a convex function is used for transforming the speech spectrum coefficient and obtaining a post-filter coefficient so that difference can increase in the case where the speech spectrum coefficient is small but decrease in the case where the coefficient is large. Then, the post-filter coefficient is applied to the MDCT coefficient. With this configuration, both the current and previous MDCT values are used, so that it is possible to obtain a spectrum coefficient similar to the real speech spectrum and to obtain a more accurate filter coefficient. Further, the coefficient is adaptively transformed through the convex function, thereby enhancing speech quality.

Abstract: A method and system denoises a mixed signal. A constrained non-negative matrix factorization (NMF) is applied to the mixed signal. The NMF is constrained by a denoising model, in which the denoising model includes training basis matrices of a training acoustic signal and a training noise signal and statistics of weights of the training basis matrices. The applying produces weight of a basis matrix of the acoustic signal, of the mixed signal. A product of the weights of the basis matrix of the acoustic signal and the training basis matrices of the training acoustic signal and the training noise signal is taken to reconstruct the acoustic signal. The mixed signal can be speech and noise.

Abstract: A sound processing apparatus is provided for estimating the power of background noise using a directional sound receiving technology using a plurality of sound receiving units, computing a gain control value on the basis of the estimated power of background noise and a predetermined power target value, and outputting the gain control value, so that a delay time of starting gain control can be reduced, and a slow response of a speech recognition application program or degradation of the speech quality of a voice communication program can be prevented.

Abstract: A sound source signal from a target sound source is allowed to be separated from a mixed sound which consists of sound source signals emitted from a plurality of sound sources without being affected by uneven sensitivity of microphone elements. A beamformer section 3 of a source separation device 1 performs beamforming processing for attenuating sound source signals arriving from directions symmetrical with respect to a perpendicular line to a straight line connecting two microphones 10 and 11 respectively by multiplying output signals from the microphones 10 and 11 after spectrum analysis by weighted coefficients which are complex conjugate to each other. Power computation sections 40 and 41 compute power spectrum information, and target sound spectrum extraction sections 50 and 51 extract spectrum information of a target sound source based on a difference between the power spectrum information.

Abstract: In order to enhance the quality of a communication signal derived from speech and noise, a filter divides the communication signal into a plurality of frequency band signals. A calculator generates a plurality of power band signals each having a power band value and corresponding to one of the frequency band signals. The power band values are based on estimating, over a time period, the power of one of the frequency band signals. The time period is different for different ones of the frequency band signals. The power band values are used to calculate weighting factors which are used to alter the frequency band signals that are combined to generate an improved communication signal.

Abstract: Provision to reduce production of musical noise. A noise reduction device includes: means for calculating a rank for each element included in a first region having predetermined sizes in the time axis direction and in the frequency axis direction, depending on a value of the element, in a noise section of an observed signal indicating variation of a frequency spectrum with time; means for calculating a rank for each element included in a second region, depending on a value of the element, the second region having predetermined sizes in the time axis direction and in the frequency axis direction in the observed signal; and means for subtracting, from the values of the respective elements in the second region, values based on the values of the respective elements in the first region whose ranks correspond to ranks of respective elements in the second region.

Abstract: A method of estimating the reverberations in an acoustic signal (y) comprises the steps of determining the frequency spectrum (Y) of the signal (y), providing a first parameter (?) indicative of the decay of the reverberations part (r) of the signal over time, and providing a second parameter (?) indicative of the amplitude of the direct part (d) of the signal relative to the reverberations part (r). An estimated frequency spectrum ({hacek over (R)}) of the reverberations signal (r) is produced using the frequency spectrum (Y) of a previous frame, the first parameter (?), and the second parameter (?). The second parameter (?). The second parameter (?) is preferably inversely proportional to the early-to-late ratio of the signal (y).

Abstract: A band division noise suppressor suppressing noise sufficiently with a small amount of processing and a little voice distortion. In the band division noise suppressor, a band dividing section (101) divides an input voice signal into a low band voice signal and a high band voice signal. The low band voice signal is subjected to decimate at a decimation section (102), subjected to noise suppression at a low band noise suppressing section (103), and then interpolated at an interpolation section (104). On the other hand, the high band voice signal is subjected to noise suppression at a high band noise suppressing section (105). A band combination section (106) composes the bands of low-band and high-band voice signals subjected to noise suppression and outputs a voice signal subjected to noise suppression over the entire band.

Abstract: Digital audio data with error detection bits added thereto is inputted to an error detecting and correcting device (4). The correcting device (4) corrects an error when the error is detected in the digital audio data. The digital audio data outputted from the error detecting and correcting device (4) is inputted to an impulse noise suppressing circuit (6). The suppressing circuit (6) operates for a predetermined time period when the correcting device (4) detects an error.

Abstract: An apparatus for adaptively suppressing noise in an input signal frequency spectrum derived from overlapping input frames is provided. The system includes a psychoacoustic power computation module configured to compute a noisy signal power in psychoacoustic bands, a voice activity scoring module configured to compute a probabilistic score for a presence of a speech, and a noise estimation module configured to estimate a noise power in the psychoacoustic bands based on information of past frames, the probabilistic score, and the computed noisy signal power. The system also includes a gain computation module configured to compute a gain for each frequency, based on a probabilistic heuristic, the probabilistic score and the information on the past frames, and a gain post-processing module configured to perform a gain time smoothing, a gain frequency smoothing, and a gain regulation for the computed gain.

Abstract: A method for improving the intelligibility of an incoming telephone signal, including boosting loudness of at least one band of poorly heard frequencies of the signal within at least one band of intensities of the signal, the band lying below a predetermined intensity level at which telephone standard conformance testing is performed, thereby to generate a differentially boosted telephone signal.

Abstract: The present invention relates to an apparatus and method of improving intelligibility of a voice signal. A method of improving intelligibility of a voice signal according to an embodiment of the present invention includes analyzing a background noise signal on a call receiving side, classifying a received voice signal into a silence signal, an unvoiced sound signal, and a voiced sound signal, and intensifying the classified unvoiced sound signal and voiced sound signal on the basis of the analyzed background noise signal on the call receiving side.

Abstract: A voice recognition system (10) for improving the toughness of voice recognition for a voice input for which a deteriorated feature amount cannot be completely identified. The system comprises at least two sound detecting means (16a, 16b) for detecting a sound signal, a sound source localizing unit (21) for determining the direction of a sound source based on the sound signal, a sound source separating unit (23) for separating a sound by the sound source from the sound signal based on the sound source direction, a mask producing unit (25) for producing a mask value according to the reliability of the separation results, a feature extracting unit (27) for extracting the feature amount of the sound signal, and a voice recognizing unit (29) for applying the mask to the feature amount to recognize a voice from the sound signal.

Abstract: A method for multifunctional processing of signals in frequency subbands performs subband decomposition and signal processing in two stages. A fullband signal is first splitted, with downsampling, into wide frequency subband (WFS) signals. Processing algorithms not requiring a high frequency resolution but benefiting from downsampling (such as subband acoustic echo cancellation), are applied to the WFS signals by wide subband processing blocks. Processed WFS signals are splitted, preferably without downsampling, into groups of narrow frequency subband (NFS) signals. The NFS signals are processed using processing algorithms (noise suppression, etc.) requiring a higher resolution. Processed NFS signals are synthesized into processed WFS signals, which are recombined into an output signal. Two-stage processing makes it possible to optimize signal processing, while keeping computational costs at low level and avoiding undesirable time delays.

Abstract: A speech processing system for improving a user's experience with a speech-enabled system using artificially generated white noise. The system can include an audible environment that includes at least one microphone and at least one speaker, a white noise generator, a white noise removal engine, and a speech processing system. The white noise generator can be configured to generate white noise to be audibly presented in the audible environment. This white noise can be captured in speech input and the white noise removal engine can digitally preprocess the input to remove the white noise components. The preprocessed input can be processed by the speech processing system and the speech processing system can create speech output based on the received input.

Abstract: Methods and apparatus for reducing the effect of surrounding noise in a push-to-talk (PTT) system are disclosed. In one embodiment, a method includes obtaining a first media stream using a microphone when a PTT functionality of a PTT communications system is in a first state, and identifying a first set of characteristics associated with noise in the first media stream. The method also includes obtaining a second media stream using the microphone that includes the noise and a first sound when the PTT functionality is in a second state. A second set of characteristics associated with the first sound in the second media stream is identified, and parameters associated with a filtering arrangement are determined using the first and second sets of characteristics. Finally, the method includes applying the filtering arrangement to the second media stream to filter out the noise such that a communications stream is created.

Abstract: A sound signal processor includes first and second framing sections, first and second frequency analyzing sections, and a cross-spectrum calculating sections, for detecting the phase of a cross-spectrum between the sound signals input to first and second microphones, a phase extracting sections, a phase unwrap processing sections, a frequency band dividing section, and first through N-th inclination calculating sections, for detecting the inclinations of the phase of the cross-spectrum detected by the cross-spectrum calculating section with respect to the frequency, and a histogram calculating section and a voiced/voiceless determining section, for detecting a speech section in the sound received by the first and second microphones based on the inclination with respect to the frequency detected by the first through N-th inclination calculating sections.

Abstract: A noise-canceling device of a voice communication terminal that removes noise elements included in received voice signals. The device comprises: a digital filter array that exhibits filter qualities in response to a coefficient setting signal showing each supplied arrays of filter coefficients, and includes a first-stage filter that receives the received voice signals as well as multiple later-stage filters connected thereto in a straight line; a filter qualities designator that generates input designation that designates each qualities of the multiple digital filters forming the digital filters array; and a filter coefficient setter that retains multiple arrays of filter coefficients, extracts a filter coefficient array corresponding to the designation input from among the multiple filter coefficient arrays, and supplies to each multiple digital filters.