Abstract: A speech enhancement system improves speech conversion within an encoder and decoder. The system includes a first device that converts sound waves into operational signals. A second device selects a template that represents an expected signal model. The selected template models speech characteristics of the operational signals through a speech codebook that is further accessed in a communication channel.

Abstract: A method determines from an input noisy signal sequences of hidden variables including at least one sequence of hidden variables representing an excitation component of the clean speech signal, at least one sequence of hidden variables representing a filter component of the clean speech signal, and at least one sequence of hidden variables representing the noise signal. The sequences of hidden variables include hidden variables determined as a non-negative linear combination of non-negative basis functions. The determination uses the model of the clean speech signal that includes a non-negative source-filter dynamical system (NSFDS) constraining the hidden variables representing the excitation and the filter components to be statistically dependent over time. The method generates an output signal using a product of corresponding hidden variables representing the excitation and the filter components.

Abstract: A method includes generating a high-band residual signal based on a high-band portion of an audio signal. The method also includes generating a harmonically extended signal at least partially based on a low-band portion of the audio signal. The method further includes determining a mixing factor based on the high-band residual signal, the harmonically extended signal, and modulated noise. The modulated noise is at least partially based on the harmonically extended signal and white noise.

Abstract: Provided are methods and systems for noise suppression within multiple time-frequency points of spectral representations. A multi-feature cluster tracker is used to track signal and noise sources and to predict signal versus noise dominance at each time-frequency point. Multiple features, such as binaural and monaural features, may be used for these purposes. A Gaussian mixture model (GMM) is developed and, in some embodiments, dynamically updated for distinguishing signal from noise and performing mask-based noise reduction. Each frequency band may use a different GMM or share a GMM with other frequency bands. A GMM may be combined from two models, with one trained to model time-frequency points in which the target dominates and another trained to model time-frequency points in which the noise dominates. Dynamic updates of a GMM may be performed using an expectation-maximization algorithm in an unsupervised fashion.

Abstract: Technologies are described herein for noise adaptive training to achieve robust automatic speech recognition. Through the use of these technologies, a noise adaptive training (NAT) approach may use both clean and corrupted speech for training. The NAT approach may normalize the environmental distortion as part of the model training. A set of underlying “pseudo-clean” model parameters may be estimated directly. This may be done without point estimation of clean speech features as an intermediate step. The pseudo-clean model parameters learned from the NAT technique may be used with a Vector Taylor Series (VTS) adaptation. Such adaptation may support decoding noisy utterances during the operating phase of a automatic voice recognition system.

Abstract: A method for processing multichannel acoustic signals which processes input signals of a plurality of channels including the voices of a plurality of speaking persons. The method is characterized by detecting the voice section of each speaking person or each channel, detecting overlapped sections wherein the detected voice sections are common between channels, determining a channel to be subjected to crosstalk removal and the section thereof by use of at least voice sections not including the detected overlapped sections, and removing crosstalk in the sections of the channel to be subjected to the crosstalk removal.

Abstract: A Voice Activity Detection/Silence Suppression (VAD/SS) system is connected to a channel of a transmission pipe. The channel provides a pathway for the transmission of energy. A method for operating a VAD/SS system includes detecting the energy on the channel, and activating or suppressing activation of the VAD/SS system depending upon the nature of the energy detected on the channel.

Abstract: A calibration system built in an electronic device with noise suppression is provided. The calibration system includes a first audio receiving module, a second audio receiving module and a correction module. The correction module corrects an adjustment value of the first audio receiving module and the second audio receiving module. The adjustment value is for adjusting gains of audio received results of the first audio receiving and second audio receiving.

Abstract: A Voice Activity Detection (VAD) algorithm provides a simple binary signal indicating the presence or absence of speech in a microphone signal. The VAD algorithm includes a first step of noise suppression which both estimates and removes (i.e., filters) ambient noise from the microphone signal to create a filtered signal. The magnitude of the filtered signal is then compared to a threshold in order to produce a VAD output signal. The threshold is dynamic and may be derived either from the filtered signal itself, or from a noise spectrum estimate calculated by the noise suppression step.

Abstract: Various techniques are disclosed for reducing artifacts generated by time compression. by adapting the time compression based on the state of the received audio. The amount of time compression may be bounded based on audio characteristics. Another feature provides a way of determining the most correlated portions of segments of audio. Voiced speech may be distinguished from unvoiced speech. Another feature provides a way of distinguishing between silence, voiced speech, and unvoiced speech. Time compression may be adapted during periods of lengthy silence. Another feature allows for reducing time compression during sensitive portions of the received audio. One or more of these features may be present in different embodiments.

Abstract: Systems and methods for inhibiting access to the lips of speaking person including a sound receiving device for receiving speech of a person speaking, the person having lips that move when the person speaks, a blocker connected to the device for blocking the lips of the person speaking while the person is speaking; and, in some aspects, such a blocker with a material addition apparatus to provide added material for the breath of a person speaking, e.g., for preventing the spread of disease or to freshen a speaker's breath. This abstract is provided to comply with the rules requiring an abstract which will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure and is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims, 37 C.F.R. 1.72(b).

Abstract: A howling canceller which suppresses occurrence of howling even when an open loop gain exceeds “1” in the whole reproduction band. In the howling canceller, an adaptive filter (107) operates a digital received voice signal with a tap coefficient to generate a pseudo echo; a subtractor (108) subtracts the pseudo echo from a digital transmitted voice signal to generate a residual signal; and an amplitude limiting circuit (110) limits the absolute value of the amplitude of the digital received voice signal to be equal to or smaller than a predetermined threshold which ensures that all of a D/A converter (101), a power amplifier (102), a speaker (103), a microphone (104), a microphone amplifier (105), and an A/D converter (106) operate in a linear operation area, and outputs the amplitude-limited digital received voice signal to the D/A converter (101) and the adaptive filter (107).

Abstract: A speech processing apparatus includes a sound collecting unit configured to collect sound signals, a sound source direction estimating unit configured to estimate a direction of a sound source of each sound signal collected by the sound collecting unit, a reverberation reducing filter calculating unit configured to calculate a reverberation reducing filter to be applied to the sound signals collected by the sound collecting unit, and a reduction processing unit configured to apply the reverberation reducing filter calculated by the reverberation reducing filter calculating unit to the sound signals, and the reverberation reducing filter calculating unit calculates the reverberation reducing filter to be applied based on the directions of the sound sources estimated by the sound source direction estimating unit.

Abstract: A device and method for estimating a tonal stability of a sound signal include: calculating a current residual spectrum of the sound signal; detecting peaks in the current residual spectrum; calculating a correlation map between the current residual spectrum and a previous residual spectrum for each detected peak; and calculating a long-term correlation map based on the calculated correlation map, the long-term correlation map being indicative of a tonal stability in the sound signal.

Abstract: Systems, methods, and devices for providing noise reduction to an audio signal, such as a speech signal, to improve the accuracy of a speech recognition system. The various embodiments may be particularly useful for training and simulation systems.

Abstract: Methods and systems for transmission of noise parameters for improving automatic speech recognition are disclosed. A system includes one or more microphones, wherein each microphone is configured to produce an audio signal. The system also includes a noise reduction module configured to generate a noise-reduced audio signal and a noise parameter. Furthermore, the system includes a transmitter configured to transmit, to a computing device, the noise-reduced audio signal and a noise parameter. The computing device may use the noise parameter in obtaining a model to use for performing automatic speech recognition.

Abstract: Wind and other noise is suppressed in a signal by adaptively changing characteristics of a filter. The filter characteristics are changed in response to the noise content of the signal over time using a history of noise content. Filter characteristics are changed according to a plurality of reference filters, the characteristics of which are chosen to optimally attenuate or amplify signals in a range of frequencies.

Abstract: A noise filler for providing a noise-filled spectral representation of an audio signal on the basis of an input spectral representation of the audio signal has a spectral region identifier configured to identify spectral regions of the input spectral representation spaced from non-zero spectral regions of the input spectral representation by at least one intermediate spectral region, to obtain identified spectral regions, and a noise inserter configured to selectively introduce noise into the identified spectral regions to obtain the noise-filled spectral representation of the audio signal. A noise filling parameter calculator for providing a noise filling parameter on the basis of a quantized spectral representation of an audio signal has a spectral region identifier, as mentioned above, and a noise value calculator configured to selectively consider quantization errors of the identified spectral regions for a calculation of the noise filling parameter.

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: Embodiments of methods and devices for classifying background noise contained in an audio signal are disclosed. In one embodiment, the device includes a module for extracting from the audio signal a background noise signal, termed the noise signal. Also included is a second that calculates a first parameter, termed the temporal indicator. The temporal indicator relates to the temporal evolution of the noise signal. The second module also calculates a second parameter, termed the frequency indicator. The frequency indicator relates to the frequency spectrum of the noise signal. Finally, the device includes a third module that classifies the background noise by selecting, as a function of the calculated values of the temporal indicator and of the frequency indicator, a class of background noise from among a predefined set of classes of background noise.

Abstract: A speech processing method and arrangement are described. A dynamic noise adaptation (DNA) model characterizes a speech input reflecting effects of background noise. A null noise DNA model characterizes the speech input based on reflecting a null noise mismatch condition. A DNA interaction model performs Bayesian model selection and re-weighting of the DNA model and the null noise DNA model to realize a modified DNA model characterizing the speech input for automatic speech recognition and compensating for noise to a varying degree depending on relative probabilities of the DNA model and the null noise DNA model.

Abstract: The invention relates to audio signal processing. More specifically, the invention relates to enhancing multichannel audio, such as television audio, by applying a gain to the audio that has been smoothed between portions of the audio. The invention relates to methods, apparatus for performing such methods, and to software stored on a computer-readable medium for causing a computer to perform such methods.

Abstract: An electronic device for generating a masking signal is described. The electronic device includes a plurality of microphones and a speaker. The electronic device also includes a processor and executable instructions stored in memory that is in electronic communication with the processor. The electronic device obtains a plurality of audio signals from the plurality of microphones. The electronic device also obtains an ambience signal based on the plurality of audio signals. The electronic device further determines an ambience feature based on the ambience signal. Additionally, the electronic device obtains a voice signal based on the plurality of audio signals. The electronic device also determines a voice feature based on the voice signal. The electronic device additionally generates a masking signal based on the voice feature and the ambience feature. The electronic device further outputs the masking signal using the speaker.

Abstract: Various embodiments provide an ability to analyze an audio input signal and generate a counter audio signal based, at least in part, on the audio input signal. In some cases, combining the audio input signal with the counter audio signal renders the audio input signal incoherent and/or unintelligible to accidental listeners and/or listeners to whom the audio input signal is not directed towards. Alternately or additionally, the counter signal can mask the audio input signal to the accidental listeners.

Abstract: Multi-channel noise suppression systems and methods are described that omit the traditional delay-and-sum fixed beamformer in devices that include a primary speech microphone and at least one noise reference microphone with the desired speech being in the near-field of the device. The multi-channel noise suppression systems and methods use a blocking matrix (BM) to remove desired speech in the input speech signal received by the noise reference microphone to get a “cleaner” background noise component. Then, an adaptive noise canceler (ANC) is used to remove the background noise in the input speech signal received by the primary speech microphone based on the “cleaner” background noise component to achieve noise suppression. The filters implemented by the BM and ANC are derived using closed-form solutions that require calculation of time-varying statistics of complex frequency domain signals in the noise suppression system.

Abstract: In the field of audio encoding/decoding technologies, a signal de-noising method is provided. The method includes: selecting, according to a degree of inter-frame correlation of a frame where a spectral coefficient to be adjusted resides, at least two spectral coefficients having high correlation with the spectral coefficient to be adjusted; performing weighting on the at least two selected spectral coefficients and the spectral coefficient to be adjusted to acquire a predicted value of the spectral coefficient to be adjusted; and adjusting a spectrum of a decoded signal by using the acquired predicted value, and outputting the adjusted decoded signal. A signal de-noising apparatus corresponding to the signal de-noising method and an audio decoding system using the signal de-noising apparatus are also provided.

Abstract: Systems and methods to automatically equalize coloration in speech recordings is provided. In example embodiments, a reference spectral shape based on a reference signal is determined. An estimated spectral shape for an input signal is derived. Using the estimated spectral shape and the reference spectral shape a comparison is performed to determine gain settings. The gain settings comprise a gain value for each filter of a filter system. Using gain values associated with the gain setting, automatic equalization is performed on the input signal.

Abstract: In a pulse encoding and decoding method and a pulse codec, more than two tracks are jointly encoded, so that free codebook space in the situation of single track encoding can be combined during joint encoding to become code bits that may be saved. Furthermore, a pulse that is on each track and required to be encoded is combined according to positions, and the number of positions having pulses, distribution of the positions that have pulses on the track, and the number of pulses on each position that has a pulse are encoded separately, so as to avoid separate encoding performed on multiple pulses of a same position, thereby further saving code bits.

Abstract: A personal audio device, such as a wireless telephone, includes noise canceling circuit that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone may also be provided proximate the speaker to estimate an electro-acoustical path from the noise canceling circuit through the transducer. A processing circuit uses the reference and/or error microphone, optionally along with a microphone provided for capturing near-end speech, to determine whether one of the reference or error microphones is obstructed by comparing their received signal content and takes action to avoid generation of erroneous anti-noise.

Abstract: The present invention relates to a system for suppressing transient interference from a signal. The system includes a modeling system, wherein the modeling system constructs a model of transient interference from a first signal, and a filtering system, wherein the filtering system suppresses transient interference from a second signal by applying the model to the second signal.

Abstract: A method for processing multichannel acoustic signals, whereby input signals of a plurality of channels including the voices of a plurality of speaking persons are processed. The method is characterized by comprising: calculating the first feature quantity of the input signals of the multichannels for each channel; calculating similarity of the first feature quantity of each channel between the channels; selecting channels having high similarity; separating signals using the input signals of the selected channels; inputting the input signals of the channels having low similarity and the signals after the signal separation; and detecting a voice section of each speaking person or each channel.

Abstract: An in-vehicle communication device includes: a noise removal filter and a noise suppressor which are configured to remove running noise superimposed on a voice signal collected by a microphone; a band energy ratio corrector for correcting a band energy ratio reduced by the noise removal filter and the noise suppressor; and a variable bitrate encoder for transmitting a speech voice to the other party via a telephone network, the variable bitrate encoder compressing the speech voice corrected by the band energy ratio corrector. This can reduce the possibility that a voice classifier of the variable bitrate encoder erroneously determines voiced sound as voiceless sound and the voiced sound is erroneously compressed by voiceless sound-use low bitrate encoding. Consequently, even in low average bitrate communications, the speech voice in the in-vehicle environment can be provided to the other party at high quality.

Abstract: Systems and methods for controlling adaptivity of noise cancellation are presented. One or more audio signals are received by one or more corresponding microphones. The one or more signals may be decomposed into frequency sub-bands. Noise cancellation consistent with identified adaptation constraints is performed on the one or more audio signals. The one or more audio signals may then be reconstructed from the frequency sub-bands and outputted via an output device.

Abstract: An objective quality assessment method for obtaining an improved estimate of a perceptual quality degradation of a processed signal, and an arrangement for executing such a method, is provided, which is executed on a processed signal and an associate reference signal. Both signals are split up into associated frame-pairs after which either all or selected frame-pairs are processed further, by creating a reference residual signal and a processed residual signal for each frame-pair, calculating separate ratios of p-norms on both residual signals, and by calculating and storing a per-frame quality estimate on the basis of the ratios of p-norms for each selected frame-pair. An objective per-signal quality estimate that is proportional to the perceptual quality degradation is then provided by aggregating the calculated per-frame-pair quality estimates.

Abstract: The present invention is directed to a wireless telephone having a first microphone and a second microphone and a method for processing audio signal in a wireless telephone having a first microphone and a second microphone. The wireless telephone includes a first microphone, a second microphone, and a signal processor. The first microphone outputs a first audio signal, the first audio signal comprising a voice component and a background noise component. The second microphone outputs a second audio signal. The signal processor increases a ratio of the voice component to the noise component of the first audio signal based on the content of at least one of the first audio signal and the second audio signal to produce a third audio signal.

Abstract: The inventive method provides for an encoder in a voice codec to be designed such that after a particular idle time (“Idle Period”) it recalculates the averaged energy and the autocorrelation function. Administrative points in the network inform the encoder about the idle time which has been set in the transmission network.

Abstract: The present invention provides a noise reduction control method using a microphone array and a noise reduction control device using a microphone array wherein the method comprises the steps of: S1: collecting, by the microphone array, acoustic signals; S2: estimating incidence angles of all acoustic signals of the microphone array; S3: conducting a statistics on signal components according to incidence angles; S4: determining a parameter ? from a ratio of noise components according to the statistical result and using the parameter ? as a control parameter for controlling an adaptive filter. With the present invention, space position information of the sound is obtained directly with the microphone array to control update of the adaptive filter more accurately, so as to eliminate noise, enhance SNR and protect speech quality well at the same time.

Abstract: A method of dominant speech extraction is provided that includes acquiring a primary audio signal from a microphone and at least one additional audio signal from at least one additional microphone, wherein the acquired audio signals include speech and noise, decomposing each acquired audio signal into a low frequency sub-band signal and a high frequency sub-band signal, applying speech suppression beamforming to the low frequency sub-band signals to generate a reference channel having an estimate of noise in the low frequency sub-band signals, applying noise cancellation to the low frequency sub-band signal of the primary audio signal using the reference channel to generate a first signal having a low frequency estimate of the speech, applying noise suppression beamforming to the high frequency sub-band signals to generate a second signal having a high frequency estimate of the speech, and combining the first and second signals to generate a full-band audio signal.

Abstract: A non-spatial speech detection system includes a plurality of microphones whose output is supplied to a fixed beamformer. An adaptive beamformer is used for receiving the output of the plurality of microphones and one or more processors are used for processing an output from the fixed beamformer and identifying speech from noise though the use of an algorithm utilizing a covariance matrix.

Abstract: Disclosed is the system and method to remove noises in voice signals in a voice communication. The at least one embodiment of the present disclosure performs a spectral subtraction (SS) for voice signals based on a gain function by a spectral subtraction apparatus, performs clustering of voice signals consecutive on a frequency axis of a spectrogram for the voice signals in which the spectral subtraction has been already performed to designate one or more clusters, and extracts musical noises by determining continuity of each of the designated clusters on the frequency axis and a time axis of the spectrogram to extract musical noises.

Abstract: A speech enhancement system enhances transitions between speech and non-speech segments. The system includes a background noise estimator that approximates the magnitude of a background noise of an input signal that includes a speech and a non-speech segment. A slave processor is programmed to perform the specialized task of modifying a spectral tilt of the input signal to match a plurality of expected spectral shapes selected by a Codec.

Abstract: A voice correction device includes a detector that detects a response from a user, a calculator that calculates an acoustic characteristic amount of an input voice signal, an analyzer that outputs an acoustic characteristic amount of a predetermined amount when having acquired a response signal due to the response from the detector, a storage unit that stores the acoustic characteristic amount output by the analyzer, a controller that calculates an correction amount of the voice signal on the basis of a result of a comparison between the acoustic characteristic amount calculated by the calculator and the acoustic characteristic amount stored in the storage unit, and a correction unit that corrects the voice signal on the basis of the correction amount calculated by the controller.

Abstract: An electrical apparatus a voice signal receiving method thereof are disclosed. The electrical apparatus includes a plurality of voice receivers, a voice activity detector, a voice channel switch and a noise eliminator. The voice receivers are used to receive the voice signals. The voice activity detector receives and detects the voice signals, and obtains a main voice signal from the voice signals. The voice channel switch transports the main voice signal to a voice transporting channel and transports a plurality of other voice signals of the voice signals other than the main voice signal to a noise transporting channel according to a detecting result of the voice activity detector. The noise eliminator reduces the noise in the main voice according to the voice signals from the noise transporting channel.

Abstract: The invention automatically enables and disables noise reduction based on a noise threshold. This threshold can be pre-defined by a user for a particular machine or can be defined “on the fly” before/during a telephonic conversation. With this flexibility, the users can “by-pass” the noise reduction and preserve the voice quality which are usually altered/modified by noise reduction algorithms. The present invention provides a novel system and method for monitoring the audio signals, analyze selected audio signal components, compare the results of analysis with a threshold value, and enable or disable noise reduction capability of a communication device.

Abstract: Unlike sound based pressure waves that go everywhere, air turbulence caused by wind is usually a fairly local event. Therefore, in a system that utilizes two or more spatially separated microphones to pick up sound signals (e.g., speech), wind noise picked up by one of the microphones often will not be picked up (or at least not to the same extent) by the other microphone(s). Embodiments of methods and apparatuses that utilize this fact and others to effectively detect and suppress wind noise using multiple microphones that are spatially separated are described.

Abstract: A method and apparatus for transcoding audio data. The method includes determining if AAC joint stereo exists, running a reference AC-3 rematrixing when the AAC joint stereo does not exist, when AAC joint stereo does exist, enabling rematrixing when the number of corresponding AAC bands is greater than half the size of the band, otherwise, running reference AC-3 rematrixing.

Abstract: A method of selectively performing signal processing in a first mode and in a second mode. In the first mode, a noise cancel signal having a signal characteristic to cancel an external noise component is generated based on a voice signal supplied from a microphone, and an input digital audio signal and the noise cancel signal are combined into a voice signal to be output through a speaker. In the second mode, a sound process for vocal voice is performed on a voice signal supplied from a microphone, a vocal voice component is canceled from a digital audio signal of input music to generate a karaoke signal, and the karaoke signal and the vocal signal are combined into a voice signal to be output through a speaker. The first mode corresponds to an audio replay operation accompanied by noise cancel, and the second mode corresponds to a karaoke operation.

Abstract: An audio signal in which an audio signal is received as a stream of digital samples, each being a numerical value representing a sampled signal level. A first zero crossing point is identified and the received audio samples are stored until a second zero crossing point is identified, thereby storing a first half-wave of samples. The highest intensity sample is identified from the stored samples and this is compared against a predetermined threshold. All stored samples are scaled by an initial scaling factor so that the intensity of the highest intensity sample is not above this threshold. A second half-wave of samples is stored in which all samples of the second half-wave are below the threshold. All stored samples of the second half-wave are also scaled but by a modified scaling factor derived from a combination of the initial scaling factor and a decay factor.

Abstract: Method and apparatus that dynamically adjusts operational parameters of a text-to-speech engine in a speech-based system. A voice engine or other application of a device provides a mechanism to alter the adjustable operational parameters of the text-to-speech engine. In response to one or more environmental conditions, the adjustable operational parameters of the text-to-speech engine are modified to increase the intelligibility of synthesized speech.

Abstract: A method and an apparatus for processing an audio signal in a mobile terminal, in which an audio signal that is received from a counterpart mobile terminal is classified into a voice signal and a noise signal according to respective energy. A frequency of the classified voice signal and an energy of the classified noise signal is controlled according to a predetermined criteria, then the controlled voice signal and the controlled noise signal are coupled and output to a speaker.