750 results about "Reverberation" patented technology

A system configured to improve audio processing by performing dereverberation and noise reduction during a communication session. In some examples, the system may include a deep neural network (DNN) configured to perform speech enhancement, which is located after an Acoustic Echo Cancellation (AEC) component. For example, the DNN may process isolated audio data output by the AEC component to jointly mitigate additive noise and reverberation. In other examples, the system may include a DNN configured to perform acoustic interference cancellation, which may jointly mitigate additive noise, reverberation, and residual echo, removing the need to perform residual echo suppression processing. The DNN is configured to process complex-valued spectrograms corresponding to the isolated audio data and / or estimated echo data generated by the AEC component.

The invention provides a manifold constraint-based sonar imaging reverberation elimination method and system, and is applied to the field of imaging data processing. According to the method, the time domain waveform of the echo signal is collected in real time, whether the irregular reflection peak value is detected or not is judged, potential interference and reflection in the underwater environment can be rapidly recognized, and particularly, in the complex underwater environment, non-target objects (such as seabed obstacles or sundries) possibly cause irregular reflection signals, so that the interference and reflection in the underwater environment can be rapidly recognized. Meanwhile, the underwater propagation characteristics of sound waves can be accurately modeled by collecting the reflection path of the echo signal and predicting the propagation parameters of the reverberation signal. And accurate background data can be provided for the propagation modeling of the reverberation signal through the pre-recorded information of submarine topography, geological characteristics, sound wave propagation characteristics and the like.

The invention relates to the technical field of audio signal processing, and discloses a room sound correction method, device and equipment for audio equipment and a storage medium, which are used for improving the accuracy and correction effect of correction parameters and effectively improving the acoustic effect of the audio equipment in a room. The room sound correction method of the audio equipment comprises the following steps: acquiring response data of a room to a multi-band preset test signal, and extracting room acoustic data by adopting a time-frequency conjoint analysis method, the room acoustic data comprising frequency attenuation, reflection paths, phase shifts and reverberation time information of different bands; based on the room acoustic data, performing compensation processing by using preset microphone calibration data to obtain a calibrated frequency response curve; performing fitting calculation on a preset ideal frequency curve and the calibrated frequency response curve according to an optimization algorithm to obtain specific correction parameters of the room; and correspondingly adjusting the output of the audio equipment according to the correction parameter.

An audio apparatus comprising a receiver (501) receiving audio data and metadata including data for reverberation parameters for the environment. A modifier (503) generates a modified first parameter value for a first reverberation parameter which is a reverberation delay parameter or a reverberation decay rate parameter. A compensator (505) generates a modified second parameter value for a second reverberation parameter in response to the modification of the first reverberation parameter / The second reverberation parameter is indicative of an energy of reverberation in the acoustic environment. A renderer (400) generates audio output signals by rendering the audio data using the metadata and specifically a reverberation renderer (407) generates at least one reverberation signal component for at least one audio output signal from at least one of the audio signals and in response to the first modified parameter value and the second modified parameter value. The compensation may provide improved perceived reverberation while allowing flexible adaptation.

A method that includes determining a set of one or more reverberation parameters of an extended reality (XR) environment in which a user is to participate, determining whether an audio source device is wirelessly communicatively coupled to send audio to an audio output device, in response to determining that the audio source device is not wirelessly communicatively coupled to the audio output device obtaining a microphone signal produced by a microphone of the audio source device, producing a reverberant audio signal from the microphone signal according to the set of one or more reverberation parameters, and sending the reverberant audio signal to drive a speaker driver of the audio source device.

The embodiment of the invention provides an audio processing method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a target pulse response of a first audio signal, wherein the target pulse response is a stereo pulse response used for simulating sound reflection and attenuation effects of the first audio signal in an acoustic space; performing convolution processing on the first audio signal and the target pulse response to obtain a second audio signal; and performing audio mixing on the first audio signal and the second audio signal to output a third audio signal. According to the scheme provided by the invention, the stereo pulse response data capable of simulating the reflection and attenuation effects of the sound in the space can be synchronously determined when reverberation is carried out on the audio signal, and reverberation is carried out on the audio signal by using the stereo pulse response data, so that the sound is heard to be generated in different space environments; the reverberation effect of the audio signal is more vivid, the sense of space and the sense of layering of the sound are increased, and the sound is fuller and stereoscopic.

The invention belongs to the technical field of sound source positioning, and particularly relates to a sound source orientation identification method based on a three-array-element miniature microphone array. According to the method, sound source localization is converted into a deep learning classification task by extracting a microphone array sound intensity feature map. The method comprises the following steps: firstly, on the basis of a three-array-element differential microphone array, extracting orthogonal sound intensity features and converting the orthogonal sound intensity features into an RGB sound intensity spectrogram; secondly, designing a new lightweight neural network to meet the requirements of sound source localization and deployment; and finally, the horizontal plane sound source orientation is divided into different angle categories, a sound intensity spectrogram data set is made and sent to a neural network for training and testing, and a sound source orientation recognition result is obtained. Compared with the prior art, the feature map and the network model provided by the invention have better robustness in a high reverberation environment, the azimuth recognition angle precision is high, the calculation complexity is low, and the method is not influenced by voice characteristics.

An audio system is provided that includes a loudspeaker, at least one microphone, and at least one controller. The loudspeaker transmits an audio signal into a listening environment defined by at least one wall in a room. The at least one microphone is positioned on the loudspeaker and is configured to capture a reverberated audio signal including a plurality of reverberations and a plurality of peaks. The reverberated audio signal is indicative of the audio signal being reflected from the at least one wall. The at least one controller is programmed to apply a confidence score to the plurality of peaks to obtain a maximum score which is indicative of a maximum peak of the audio signal that is reflected from the at least one wall and determine a distance between the loudspeaker and the wall based at least on the maximum score.

An apparatus for processing an audio input signal having one or more audio channels to obtain an audio output signal according to an embodiment is provided. The apparatus has a reverberation gain determiner configured to determine reverberation gain information depending on the audio input signal. Moreover, the apparatus has a signal processor configured to obtain the audio output signal depending on the reverberation gain information by adding artificial reverberation to the audio input signal or to a preprocessed audio signal, which depends on the audio input signal.

A spatial audio processing system operable to enable audio signals to be spatially extracted from, or transmitted to, discrete locations within an acoustic space. Embodiments of the present disclosure enable an array of transducers being installed in an acoustic space to combine their signals via inverting physical and environmental models that are measured, learned, tracked, calculated, or estimated. The models may be combined with a whitening filter to establish a cooperative or non-cooperative information-bearing channel between the array and one or more discrete, targeted physical locations in the acoustic space by applying the inverted models with whitening filter to the received or transmitted acoustical signals. The spatial audio processing system may utilize a model of the combination of direct and indirect reflections in the acoustic space to receive or transmit acoustic information, regardless of ambient noise levels, reverberation, and positioning of physical interferers.

The invention provides an audio processing method, communication equipment, a communication system and a readable storage medium, and the method comprises the steps: obtaining a to-be-processed audio signal; inputting the audio signal and a preset target attenuation coefficient into a first filter to obtain a first output audio signal with an echoing sound effect; inputting the first output audio signal and the target attenuation coefficient into a second filter to obtain a second output audio signal with a sound trailing phenomenon; respectively inputting the second output audio signal into a plurality of third filters to obtain a third output audio signal corresponding to each third filter; and superposing the plurality of third output audio signals to obtain a target output audio signal with a reverberation sound effect. According to the method, the reverberation time of each frequency band can be accurately controlled, the reverberation reality sense of the output audio is effectively improved, the reverberation effect is closer to the convolution reverberation effect, meanwhile, the requirement for the computing power is greatly reduced, the calculation amount of the algorithm is effectively reduced, and the application channel of the algorithm is effectively widened.

The invention discloses a speaker recognition method in a real sound field environment based on a self-supervised learning model, and the method comprises the steps: obtaining large-scale label-free pure audio data, and adding noise and reverberation to the large-scale label-free pure audio data; clustering and labeling the pure audio data; taking the clustering pseudo labels as learning targets, and inputting a large-scale no-label noise reverberation-containing audio database into a self-supervised learning model for training; a speaker recognition network model is constructed, the speaker recognition network model comprises a front end and a rear end, the trained self-supervised learning model is migrated to the front end, and the rear end sequentially comprises a plurality of one-dimensional convolutional networks, a time delay neural network, an aggregation and pooling network and a full-connection output network; training the speaker recognition network model; and brand new voice signals are tested. According to the method, the problem of low speaker recognition precision in strong noise and reverberation environments is solved, and the method is suitable for various application scenes and has important promotion significance in voiceprint recognition under various severe conditions.

Examples of the disclosure describe systems and methods for estimating acoustic properties of an environment. In an example method, a first audio signal is received via a microphone of a wearable head device. An envelope of the first audio signal is determined, and a first reverberation time is estimated based on the envelope of the first audio signal. A difference between the first reverberation time and a second reverberation time is determined. A change in the environment is determined based on the difference between the first reverberation time and the second reverberation time. A second audio signal is presented via a speaker of a wearable head device, wherein the second audio signal is based on the second reverberation time.

A system for detecting speech from reverberant signals is disclosed. The system is programmed to receive spectral temporal amplitude data in the modulation frequency domain. The system is programmed to then enhance the spectral temporal amplitude data by reducing reverberation and other noise as well as smoothing based on certain properties of the spectral temporal spectrogram associated with the spectral temporal amplitude data. Next, the system is programmed to compute various features related to the presence of speech based on the enhanced spectral temporal amplitude data and other data in the modulation frequency domain or in the (acoustic) frequency domain. The system is programmed to then determine an extent of speech present in the audio data corresponding to the received spectral temporal amplitude data based on the various features. The system can be programmed to transmit the extent of speech present to an output device.

The invention provides an audio data processing method, electronic equipment, a storage medium and a computer program product, and the method comprises the steps: extracting audio feature information from target audio data according to a feature extraction strategy corresponding to a specified classification algorithm; classifying the audio feature information according to the specified classification algorithm to obtain a music type of the target audio data; calling a sound effect enhancement strategy matched with the music type, and performing sound effect enhancement processing on the target audio data; wherein the sound effect enhancement strategy refers to an adjustment mode of an equalizer, a reverberation mode and a bass enhancement function. According to the scheme, classification and sound effect enhancement of the audio data are realized under the condition of relatively low hardware requirements and resource consumption.

The invention relates to the technical field of voice signals, in particular to a two-step mixed sound source separation and de-reverberation method, which comprises the following steps of: firstly, carrying out separation network training by taking different types of signals as training targets in various separation networks for separating attention and the like; the invention provides an improved de-reverberation method based on a time convolution network-weight prediction error, multiple improvement strategies such as taking a scale invariance signal-to-noise interference ratio as a network loss function, adopting a transposition mechanism for an input signal and a mechanism for additionally adding a residual value to a network unit are used, and finally, the de-reverberation method based on the time convolution network-weight prediction error is obtained. And cascading the separation attention network with the best separation noise reduction effect with the time convolution-transpose-residual error-WPE network. According to the invention, the problem that the separation effect of the mixed audio signal with reverberation and noise signals is not good under the actual sound field condition is solved, compared with a single one-step or two-step existing separation, de-mixing and noise reduction network, the method is significantly improved, and the quality of the separated voice can be improved for later recognition and discrimination.

The invention relates to the technical field of underwater acoustic engineering and ocean exploration, in particular to a multi-channel underwater acoustic signal transmitting and measuring system and a signal processing method, which are used for solving the problems that the existing multi-channel underwater acoustic signal processing generally depends on fixed threshold detection or simple time sequence alignment, and the signal processing efficiency is low. The problem that residual vibration, local noise abrupt change or multipath reverberation is easily misjudged as an effective first arrival signal in a complex underwater environment due to the fact that the influence of the physical response characteristic of a transducer on emission time calibration is not considered and effective verification on whether a candidate arrival structure accords with a sound wave propagation physical rule is lacked is solved. According to the invention, a multi-channel energy time sequence and hydrophone space geometrical relationship is fused through an underwater sound propagation initial physical judgment module, a judgment mechanism is constructed based on distance-time consistency of sound propagation, and self-consistent verification is realized by combining a cross-channel arrival sequence and sound velocity constraint. And the accuracy, the robustness and the physical interpretability of the judgment of the effective launching time of the underwater sound are obviously improved.

The invention discloses an intelligent noise reduction method and system based on a mine earphone, and the method comprises the following steps: S1, obtaining an original noise signal in a mine operation environment, and carrying out the preprocessing of the original noise signal; s2, designing an adaptive compensation mechanism according to the reflection characteristics of the closed space of the mine, calculating a sound wave propagation attenuation coefficient and reflection delay, constructing a roadway reverberation model, and generating advanced compensation sound waves; and S3, carrying out collaborative fusion on the advanced compensation sound wave and a main noise reduction signal to generate a composite noise reduction signal. The invention relates to the technical field of intelligent noise reduction. According to the intelligent noise reduction method and system based on the mine earphone, the noise level in a mine operation environment is effectively reduced, the communication efficiency and the working comfort of operators are improved, potential damage of noise to hearing of the operators is reduced, and therefore the overall safety and the production efficiency of mine operation are improved.

The invention discloses a residual network sound source localization method and system based on a fusion attention mechanism, and the method comprises the steps: adding a 1 * 1 convolution kernel, adding an extra SEAM module to form an SC-SEAM module, adding the SC-SEAM module in the last two stages of a residual network structure, forming a residual network architecture of a fusion channel attention mechanism module, and carrying out the sound source localization of the residual network. An indoor sound source positioning model is trained and generated, and the method comprises the following steps: after a microphone array obtains a to-be-positioned sound signal, STFT is carried out on the to-be-positioned sound signal received by each microphone; extracting a phase component between the STFT coefficients of the sound signals to be positioned received by each microphone, and obtaining a difference to obtain a phase difference diagram between each microphone; and inputting the phase difference image into an indoor sound source positioning model, and outputting an estimated angle value of the sound signal to be positioned. The method is high in sound source positioning accuracy and strong in robustness in indoor reverberation, noise and other multi-scene complex environments.

An apparatus, method and computer program is described comprising: obtaining a virtual audio signal (comprising virtual audio samples) from one or more virtual sound signals of a virtual environment for presentation to a user; processing the virtual audio samples based on first reverberation parameters to generate a first reverberation signal (based on a geometry of a real-world space) for samples up to a first threshold time following the respective virtual audio sample being obtained; processing the virtual audio samples based on second reverberation parameters to generate a second reverberation signal (based on a geometry of the virtual environment) for samples beyond a second threshold time following the respective virtual audio sample being obtained; and generating an audio output for presentation to the user based on a sum of the first and second reverberation signals.

Bidirectional signalling for Immersive Voice Audio Services bitstreams (eg. in different languages or from different audio scenes captured in Metadata Assisted Spatial Audio, MASA) is incorporated int

The invention discloses a spatial audio processing method and device, computer equipment and a storage medium, and the method comprises the steps: responding to an operation of a user for audio equipment, and initializing a gyroscope sensor in the audio equipment; starting a gyroscope sensor, obtaining head motion original data of a user, and then performing data preprocessing to obtain current head angle information of the user; determining a corresponding head-related transfer function based on the head angle information; performing conversion processing on the original audio data based on the head-related transfer function to obtain target audio data; and performing spatial reverberation simulation on the target audio data to obtain a corresponding spatial reverberation audio. According to the scheme, high-precision and high-real-time audio output can be provided while low resource occupation is kept, and more real and immersive auditory experience is provided for a user.

The invention discloses a room geometry inference method based on positioning of a direct sound source and a first-order reflection sound source, which comprises the following steps of: 1) acquiring reverberation signals of a target room by using a microphone array, converting the reverberation signals into FOA signals, and calculating a time-frequency covariance matrix of the FOA signals, estimating the direction of arrival DOAs of the direct sound source s and the direction of arrival DOAs'of the n first-order reflection sound sources s' according to the time-frequency covariance matrix; 2) estimating the distance ds of the direct sound source s according to the DOAs, the DOAs'and the height dh of the microphone array, and determining the position Ps of the direct sound source s; 3) estimating the distance ds'of the first-order reflection sound source s' based on the FOA signal, the DOAs, the DOAs' and ds, and determining the position Ps' of the first-order reflection sound source s'; and 4) obtaining the geometric space structure of the target room according to the position Ps of the direct sound source s and the position Ps'of each first-order reflection sound source s'.

A method of presenting an audio signal to a user of a mixed reality environment is disclosed, the method comprising the steps of detecting a first audio signal in the mixed reality environment, where the first audio signal is a real audio signal; identifying a virtual object intersected by the first audio signal in the mixed reality environment; identifying a listener coordinate associated with the user; determining, using the virtual object and the listener coordinate, a transfer function; applying the transfer function to the first audio signal to produce a second audio signal; and presenting, to the user, the second audio signal.

A method is performed by an endpoint device that includes a loudspeaker, a microphone, and a controller. The method includes: by the loudspeaker, playing a loudspeaker signal into a space; by the microphone, detecting audio in the space, to produce a feedback audio signal; estimating acoustic parameters for the space including a reverberation time and an ambient noise power based on the feedback audio signal and the loudspeaker signal; receiving an incoming audio signal that is not detected by the microphone; using the acoustic parameters, generating an acoustic watermark signal that, when played into the space through the loudspeaker, would be inaudible to a listener; adding the acoustic watermark signal to the incoming audio signal to produce a watermarked audio signal; and playing the watermarked audio signal into the space through the loudspeaker.

Various embodiments of the present disclosure provide methods, apparatuses, systems, and / or devices that are configured to separate multi-source audio signal samples into discrete source separated channel audio samples using trained multi-modal audio source channelization models. Multi-source audio signal samples are difficult to separate because they can include multiple target audio sources (e.g., individual speakers) that are often inter-mixed and overlaid with other audio sources such as noise, music, reverberations, and other audio artifacts. The multi-modal audio source channelization models discussed herein are trained to generate source separated channel audio samples based on audio signal samples and on video signal samples.

The invention belongs to the technical field of reverberators, and relates to a reverberator cloning method and device. The reverberator cloning method comprises the following steps: acquiring a cloning signal, sending a test audio signal, and collecting a return audio signal of the test audio signal; performing deconvolution operation on the test audio signal and the return audio signal to obtain a pulse response signal; segmenting the pulse response signal to obtain a plurality of signal segments; performing fast Fourier transform processing on each signal segment to obtain a clone sample of each signal segment; a cloning sample is selected according to requirements so as to realize cloning of the reverberator; the return audio signal has a reverberation feature. According to the invention, a one-stop reverberation cloning scheme can be provided, the blank of a small convolution reverberator and reverberation cloning equipment in the market is filled, and a user can clone any kind of reverberation effect through very simple operation.

The invention discloses an indoor multi-sound-source positioning method based on DOA estimation and DOA association, and the method comprises the steps: judging single-source time-frequency points through the correlation of time delay inequality vectors of adjacent time-frequency points between microphones, and constructing a variable-size elastic single-source region; applying the FSSZ distribution condition of the sound source in a reference array to all arrays by using the high correlation characteristic of the FSSZ time-frequency distribution of the same sound source at different microphone arrays in a frame; performing middle DOA estimation on the FSSZs of all the arrays in the whole observation time period by using a circular integral cross spectrum method, and constructing a sound source position histogram in combination with FSSZ aggregation degree weighting; 2D positions of the plurality of sound sources are estimated from the sound source position histogram using 2D-CFAR. According to the invention, under the conditions of indoor reverberation and noise, position estimation can be carried out on a plurality of sound sources with an unknown number, the detection performance under the conditions of positioning precision and missed detection is obviously superior to that of an existing method, and the defects of the prior art are overcome.

The invention relates to an acoustic covering system for covering at least parts of a boundary (B) of a room, the acoustic covering system being configured to provide variable sound absorption, where the acoustic covering system comprises: a solid structure (2) configured to be attached to the boundary (B), such that the solid structure (2) and the boundary (B) form a space (S); and one or more boards (6) attached to the solid structure (2) and configured to selectively move relative to the solid structure (2), such that, in an open state of the acoustic covering system, one or more respective openings (45) are created between the one or more boards (6) and the solid structure (2) on at least part of a circumference of the respective one or more boards (6) to enable sound energy to pass through and reach sound absorbing means (12) within the space (S) between the one or more boards (6) and the boundary (B), wherein the sound energy is absorbed in the open state of the acoustic covering system to lower the reverberation time, RT, in the room when the acoustic covering system is installed.

The invention provides a method and device for carrying out noise detection on a train, which can be applied to the field of railway and urban rail transit, and the method comprises the following steps: determining the initial noise reverberation duration and the sound source position of noise; iteratively executing the following operations to obtain the dynamic reverberation duration: determining the nth reverberation duration according to the sum of the (n-1) th noise reverberation duration and the preset duration; processing the nth noise reverberation duration and the reference reverberation duration according to tunnel shape parameters for the pipe tunnel to obtain an nth room coefficient; processing the nth room coefficient by using a target noise detection model corresponding to the sound source position to obtain an nth sound pressure level increment value of the noise; under the condition that a difference value between the Nth sound pressure level increment value and a preset standard sound pressure level increment value meets a preset convergence condition, determining the Nth noise reverberation duration as a dynamic reverberation duration; and processing the reference reverberation duration and the dynamic reverberation duration according to a reverberation noise prediction algorithm to obtain a noise value of the noise.