Abstract: An augmented reality environment allows interaction between virtual and real objects and enhances an unstructured real-world environment. An object datastore comprising attributes of an object within the environment may be built and/or maintained from sources including manufacturers, retailers, shippers, and users. This object datastore may be local, cloud based, or a combination thereof. Applications may interrogate the object datastore to provide user functionality.

Abstract: Voice activity detection (VAD) is an enabling technology for a variety of speech based applications. Herein disclosed is a robust VAD algorithm that is also language independent. Rather than classifying short segments of the audio as either “speech” or “silence”, the VAD as disclosed herein employees a soft-decision mechanism. The VAD outputs a speech-presence probability, which is based on a variety of characteristics.

Abstract: A speech recognition system comprises: an input, for receiving an input signal from at least one microphone; a first buffer, for storing the input signal; a noise reduction block, for receiving the input signal and generating a noise reduced input signal; a speech recognition engine, for receiving either the input signal output from the first buffer or the noise reduced input signal from the noise reduction block; and a selection circuit for directing either the input signal output from the first buffer or the noise reduced input signal from the noise reduction block to the speech recognition engine.

Abstract: A controller for a voice-controlled device is provided. The controller includes a setting module and a recognition module. The setting module generates a threshold according to an environmental parameter. The recognition module compares a confident score of speech recognition with the threshold to accordingly execute voice control.

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: 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 voice conversion method of a display apparatus includes: in response to the receipt of a first video frame, detecting one or more entities from the first video frame; in response to the selection of one of the detected entities, storing the selected entity; in response to the selection of one of a plurality of previously-stored voice samples, storing the selected voice sample in connection with the selected entity; and in response to the receipt of a second video frame including the selected entity, changing a voice of the selected entity based on the selected voice sample and outputting the changed voice.

Abstract: A method, an apparatus, and a computer-readable medium configured with instructions that when executed carry out the method for determining a measure of harmonicity. In one embodiment the method includes selecting candidate fundamental frequencies within a range, and for candidate determining a mask or retrieving a pre-calculated mask that has positive value for each frequency that contributed to harmonicity, and negative value for each frequency that contributes to inharmonicity. A candidate harmonicity measure is calculated for each candidate fundamental by summing the product of the mask and the magnitude measure spectrum. The harmonicity measure is selected as the maximum of the candidate harmonicity measures.

Abstract: An audio signal with a temporal sequence of blocks or frames is received or accessed. Features are determined as characterizing aggregately the sequential audio blocks/frames that have been processed recently, relative to current time. The feature determination exceeds a specificity criterion and is delayed, relative to the recently processed audio blocks/frames. Voice activity indication is detected in the audio signal. VAD is based on a decision that exceeds a preset sensitivity threshold and is computed over a brief time period, relative to blocks/frames duration, and relates to current block/frame features. The VAD and the recent feature determination are combined with state related information, which is based on a history of previous feature determinations that are compiled from multiple features, determined over a time prior to the recent feature determination time period. Decisions to commence or terminate the audio signal, or related gains, are outputted based on the combination.

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 for real-time monitoring of audio signals reception quality includes receiving output signals from a plurality of microphone clusters, each microphone cluster having at least two microphone units to receive audio signals from at least two distinct directions and output corresponding electrical signals; identifying comparative features of output signals for each of the microphone clusters; and selecting at least one microphone cluster based on the identified features. A system for real-time monitoring of audio signals reception quality includes a plurality of microphone clusters, each microphone cluster having at least two microphone units to receive audio signals from at least two distinct directions and output corresponding electrical signals; and a main audio unit to identify comparative features of output signals for each of the microphone clusters and to select at least one microphone cluster based on the identified features.

Abstract: Provided are systems and methods for generating clean speech from a speech signal representing a mixture of a noise and speech. The clean speech may be generated from synthetic speech parameters. The synthetic speech parameters are derived based on the speech signal components and a model of speech using auditory and speech production principles. The modeling may utilize a source-filter structure of the speech signal. One or more spectral analyses on the speech signal are performed to generate spectral representations. The feature data is derived based on a spectral representation. The features corresponding to the target speech according to a model of speech are grouped and separated from the feature data. The synthetic speech parameters, including spectral envelope, pitch data and voice classification data are generated based on features corresponding to the target speech.

Abstract: A method processes an acoustic signal that is a mixture of a target signal and interfering signals by first enhancing the acoustic signal by a set of enhancement procedures to produce a set of initial enhanced signals. Then, an ensemble learning procedure is applied to the acoustic signal and the set of initial enhancement signals to produce features of the acoustic signal.

Abstract: A frame extracting means 71 extracts frames from sample data as voice data in which whether each frame is an active voice frame or a non-active voice frame is already known. A feature quantity calculating means 72 calculates multiple feature quantities of each of the frames. A feature quantity integrating means 73 calculates an integrated feature quantity of the multiple feature quantities. A judgment means 74 judges whether each of the frames is an active voice frame or a non-active voice frame. An erroneous feature quantity calculation value calculating means 75 obtains a first erroneous feature quantity calculation value and a second erroneous feature quantity calculation value by executing prescribed calculations. A weight updating means 76 updates weights used for weighting so that the rate between the first erroneous feature quantity calculation value and the second erroneous feature quantity calculation value approaches a prescribed value.

Abstract: An electric equipment including a communication unit to communicate with at least one electric equipment in a predetermined space through a network, a sound collection unit to collect sound in the predetermined space, a voice recognition unit to recognize a voice from the collected sound, and a controller to transmit a noise reduction control signal to the at least one electric equipment when the recognized voice is an operation command. Voice recognition is performed in a state in which surrounding noise is reduced, thereby improving performance of the voice recognition and thus improving operational accuracy of an electric equipment. In addition, a voice recognition rate is increased, thereby improving user satisfaction.

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 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: Mitigating disruption to a voice recognition system in a vehicle caused by a passing source of noise is provided. Sensors sense an approaching truck or the like that is likely to disrupt operation of the in-vehicle voice recognition system. Countermeasures are initiated to mitigate the disruption.

Abstract: Systems and methods are disclosed herein for improving audio conferencing services. One aspect relates to processing audio content of a conference. A first audio signal is received from a first conference participant, and a start and an end of a first utterance by the first conference participant are detected from the first audio signal. A second audio signal is received from a second conference participant, and a start and an end of a second utterance by the second conference participant is detected from the second audio signal. The second conference participant is provided with at least a portion of the first utterance, wherein at least one of start time, start point, and duration is determined based at least in part on the start, end, or both, of the second utterance.

Abstract: A speech processing device includes a reverberation characteristic selection unit configured to correlate correction data indicating a contribution of a reverberation component based on a corresponding reverberation characteristic with an adaptive acoustic model which is trained using reverbed speech to which a reverberation based on the corresponding reverberation characteristic is added for each of reverberation characteristics, to calculate likelihoods based on the adaptive acoustic models for a recorded speech, and to select correction data corresponding to the adaptive acoustic model having the calculated highest likelihood, and a dereverberation unit configured to remove the reverberation component from the speech based on the correction data.

Abstract: A speech processing device includes a distance acquisition unit configured to acquire a distance between a sound collection unit configured to record speech from a sound source and the sound source, a reverberation characteristic estimation unit configured to estimate a reverberation characteristic based on the distance acquired by the distance acquisition unit, a correction data generation unit configured to generate correction data indicating a contribution of a reverberation component from the reverberation characteristic estimated by the reverberation characteristic estimation unit; and a dereverberation unit configured to remove the reverberation component from the speech by correcting the amplitude of the speech based on the correction data.

Abstract: The subject disclosure is directed towards a noise adaptive beamformer that dynamically selects between microphone array channels, based upon noise energy floor levels that are measured when no actual signal (e.g., no speech) is present. When speech (or a similar desired signal) is detected, the beamformer selects which microphone signal to use in signal processing, e.g., corresponding to the lowest noise channel. Multiple channels may be selected, with their signals combined. The beamformer transitions back to the noise measurement phase when the actual signal is no longer detected, so that the beamformer dynamically adapts as noise levels change, including on a per-microphone basis, to account for microphone hardware differences, changing noise sources, and individual microphone deterioration.

Abstract: Variable sound decomposition masking techniques are described. In one or more implementations, a mask is generated that incorporates a user input as part of the mask, the user input is usable at least in part to define a threshold that is variable based on the user input and configured for use in performing a sound decomposition process. The sound decomposition process is performed using the mask to assign portions of sound data to respective ones of a plurality of sources of the sound data.

Abstract: Noise cancelling headsets and a method of improving audio sensitivity for a headset are disclosed.

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: In a multiband compressor 100, a level calculation unit 121 calculates a signal level inputted for each of bands, a gain calculation unit 122 calculates a gain value from the calculated signal level, and a gain limitation unit 130 limits a gain value by comparison with a gain value of the other band in a compressor for each band. With this configuration, provided is a multiband compressor capable of achieving a balance between the quality of sound and the effect of enhancing the sound level at a high level.

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: Communication systems are described, including both portable handset and headset devices, which use a number of microphone configurations to receive acoustic signals of an environment. The microphone configurations include, for example, a two microphone array including two unidirectional microphones, and a two-microphone array including one unidirectional microphone and one omnidirectional microphone. The communication systems also include Voice Activity Detection (VAD) devices to provide information of human voicing activity. Components of the communications systems receive the acoustic signals and voice activity signals and, in response, automatically generate control signals from data of the voice activity signals. Components of the communication systems use the control signals to automatically select a denoising method appropriate to data of frequency subbands of the acoustic signals.

Abstract: Disclosed herein is a sound source recording apparatus and method adaptable to an operating environment, which can record a target sound source at a predetermined level without being affected by characteristics of the sound source or ambient noise. A target sound source is separated from a sound source signal received through an array of microphones and a recording sound pressure level and a gain are estimated using a reference sound pressure level and a reference distance for the target sound source, thereby controlling or adjusting the gain of the microphones.

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: By monitoring the wind noise in a location in which a cellular telephone is operating and by applying noise reduction and/or cancellation protocols at the appropriate time via analog and/or digital signal processing, it is possible to significantly reduce wind noise entering into a communication system.

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 method determines a bias reduced noise and interference estimation in a binaural microphone configuration with a right and a left microphone signal at a time-frame with a target speaker active. The method includes a determination of the auto power spectral density estimate of the common noise formed of noise and interference components of the right and left microphone signals and a modification of the auto power spectral density estimate of the common noise by using an estimate of the magnitude squared coherence of the noise and interference components contained in the right and left microphone signals determined at a time frame without a target speaker active. An acoustic signal processing system and a hearing aid implement the method for determining the bias reduced noise and interference estimation. The noise reduction performance of speech enhancement algorithms is improved by the invention. Further, distortions of the target speech signal and residual noise and interference components are reduced.

Abstract: Embodiments of the present invention provide an adaptive noise canceling system. The adaptive noise canceling system may be used in a handset to cancel background noise by generating an anti-noise signal. The adaptive noise canceling system may include first input to receive a first signal from a feedforward microphone; a second input to receive a second signal from an error microphone; a controller coupled to the inputs, the controller configured to adaptively generate an anti-noise signal according to the received signals, wherein the controller derives a profile of the anti-noise signal from the first signal and derives a magnitude of the anti-noise signal from both first and second signal; and an output to transmit the anti-noise signal to a speaker.

Abstract: A voice activity detector (100) includes a frame divider (201) for dividing frames of an input signal into consecutive sub-frames, an energy level estimator (202) for estimating an energy level of the input signal in each of the consecutive sub-frames, a noise eliminator (203) for analyzing the estimated energy levels of sets of the sub-frames to detect and eliminate from enhancement noise sub-frames and to indicate remaining sub-frames as speech sub-frames, and an energy level enhancer (205) for enhancing the estimated energy level for each of the indicated speech sub-frames by an amount which relates to a detected change of the estimated energy level for a current speech sub-frame relative to that for neighboring speech sub-frames.

Abstract: A method of performing a voice command function in an electronic device includes detecting voice of a user, acquiring one or more pieces of attribute information from the voice, and authenticating the user by comparing the attribute information with pre-stored authentic attribe information, using a recognition model. An electronic device includes a voice input module configured to detect a voice of a user, a first processor configured to acquire one or more pieces of attribute information from the voice and authenticate the user by comparing the attribute information with a recognition model, and a second processor configured to when the attribute information matches the recognition mode, activate the voice command function, receive a voice command of the user, and execute an application corresponding to the voice command. Other embodiments are also disclosed.

Abstract: Sound decomposition models are described. In one or more implementations, a plurality of individual models is generated for respective ones of a plurality of sound sources. The plurality of models is collected to form a universal audio model that is configured to support sound decomposition of sound data through use of one or more of the models. The plurality of models is not generated using a sound source that originated at least a portion of the sound data.

Abstract: A method of operation beamforms a plurality of microphone outputs to obtain a plurality of virtual microphone audio channels with at least one audio output channel and at least one audio control channel. The method performs voice recognition on the audio control channel to detect voice commands for controlling audio output channel attributes, and adjusts an audio channel attribute in response to detecting a voice command. Adjusting an attribute of the audio channel may be accomplished by, for example, controlling one or more parameters of an adjustable beamformer. The detected voice commands for controlling audio channel attributes may include voice commands for controlling audio sensitivity zooming, panning in a specified direction, focusing on a specified direction, blocking a specified direction, mixing a narrator's voice, blocking a narrator's voice, or reducing background noise. An apparatus that performs the method of operation is also disclosed.

Abstract: Provided is a noise signal suppressing device including: an input unit configured to receive a sound signal; a time/frequency converting unit; an independent peak spectrum extracting unit configured to extract a peak spectrum having independence; a persistence determining unit configured to determine that the peak spectrum having independence persists for a predetermined period or longer; a noise-signal suppressing unit configured to suppress the peak spectrum having independence as the noise signal. The independent peak spectrum extracting unit includes: a first peak extracting unit configured to extract a peak spectrum having higher energy than that of an adjacent frequency signal, and a second peak extracting unit configured to extract a peak spectrum maintaining a frequency interval of equal to or larger than a predetermined value with respect to a peak spectrum adjacent thereto as the peak spectrum having independence.

Abstract: The present invention relates to blind source separation. More specifically certain embodiments relate to the blind source separation using frequency domain processes. Aspects of the invention relate to methods and systems for receiving a set of frequency-domain first signals, and then separating the set of frequency-domain first signals into a set of frequency-domain second signals. The frequency-domain second signals may have a set of separated frequency-domain second signal elements corresponding to individual frequencies wherein each frequency-domain second signal element is assigned an identifier. The identifier may indicate which of the set of frequency-domain second signals includes the frequency-domain second signal element. Some aspects also include reordering the identifiers corresponding to at least one frequency to improve coherence of the frequency-domain second signals and to produce a set of frequency-domain third signals.

Abstract: Systems, methods, apparatus, and machine-readable media for voice activity detection in a single-channel or multichannel audio signal are disclosed.

Abstract: An apparatus and method for performing asynchronous speech recognition using multiple microphones are disclosed. The apparatus includes a microphone selection unit, a signal-to-noise ratio measurement unit, a speech recognition and verification unit, and a final recognition result output unit. The microphone selection unit selects two or more microphones responsive to a user's voice from among a plurality of microphones distributed around the user. The signal-to-noise ratio measurement unit measures the signal to noise ratios of inputs of the selected two or more microphones. The speech recognition and verification unit performs speech recognition using the input of the microphone having a highest signal to noise ratio, and verifies the speech recognition using the inputs of the remaining microphones. The final recognition result output unit outputs the final recognition results of the user's voice based on the results of the speech recognition and verification unit.

Abstract: Methods and arrangements for improving quality of content in voice applications. A specification is provided for acceptable content for a voice application, and user generated audio content for the voice application is inputted. At least one test is applied to the user generated audio content, and it is thereupon determined as to whether the user generated audio content meets the provided specification.

Abstract: Signals are received, over a range of angles, at an input of a device. The signals include a primary signal with a principal direction of arrival and an interfering signal with a respective interfering direction of arrival at the input. Measurements are determined for the received signals over the range of angles. Each measurement relates to a particular angle and indicating the energy of the received signals which are received from the particular angle. For each angle over the range of angles, a value is removed from the measurement for that angle, the value being based on the minimum of: (i) the energy of the measurement for that angle, and (ii) the energy of a corresponding measurement for a corresponding angle mirrored around the principal direction of arrival, whereby the remaining values of the plurality of measurements are indicative of said at least one interfering direction of arrival.

Abstract: A difference signal calculating unit of a noise detecting device calculates a difference between the amplitudes of a residual signal at each sample timing and a residual signal at the preceding sample timing. A difference signal comparing unit determines whether or not an impulsive noise is present on the basis of the difference signal at the current sample timing, and the difference signal at each sample timing within a predetermined duration from the current sample timing.

Abstract: The method comprises the steps of: digitizing sound signals picked up simultaneously by two microphones (N, M); executing a short-term Fourier transform on the signals (xn(t), xm(t)) picked up on the two channels so as to produce a succession of frames in a series of frequency bands; applying an algorithm for calculating a speech-presence confidence index on each channel, in particular a probability a speech that is present; selecting one of the two microphones by applying a decision rule to the successive frames of each of the channels, which rule is a function both of a channel selection criterion and of a speech-presence confidence index; and implementing speech processing on the sound signal picked up by the one microphone that is selected.

Abstract: A method for enhancing speech includes extracting a center channel of an audio signal, flattening the spectrum of the center channel, and mixing the flattened speech channel with the audio signal, thereby enhancing any speech in the audio signal. Also disclosed are a method for extracting a center channel of sound from an audio signal with multiple channels, a method for flattening the spectrum of an audio signal, and a method for detecting speech in an audio signal. Also disclosed is a speech enhancer that includes a center-channel extract, a spectral flattener, a speech-confidence generator, and a mixer for mixing the flattened speech channel with original audio signal proportionate to the confidence of having detected speech, thereby enhancing any speech in the audio signal.

Abstract: Methods and arrangements for improving quality of content in voice applications. A specification is provided for acceptable content for a voice application, and user generated audio content for the voice application is inputted. At least one test is applied to the user generated audio content, and it is thereupon determined as to whether the user generated audio content meets the provided specification.

Abstract: In an aspect, in general, an automobile communication system includes a first signal input for receiving an input signal from a sensor, a second signal input for receiving a first signal representing a rotational frequency associated with a portion of an engine of the automobile, an engine noise estimation module, and a transmitter. The engine noise estimation module is configured to determine an estimate of an engine-related component of the input signal based on the input signal and the first signal and to form a modified input signal. The engine noise estimation module includes a signal combination module configured to form the modified input signal, including combining the estimate of the engine-related component with the input signal. The transmitter is configured to transmit the modified input signal as part of an outgoing communication.

Abstract: An apparatus and method for the robust recognition of speech during a call in a noisy environment is presented. Specific background noise models are created to model various background noises which may interfere in the error free recognition of speech. These background noise models are then used to determine which noise characteristics a particular call has. Once a determination has been made of the background noise in any given call, speech recognition is carried out using the appropriate background noise model.