34 results about "Acoustic space" patented technology

The invention provides a control method and a control system for building an independent acoustic space of an automobile cabin, which are applied to the technical field of sound field control of the automobile cabin, and are used for inputting a multi-channel vibration signal acquired in real time into a deep learning noise prediction model to obtain an in-automobile background noise prediction value at a future moment; the prediction noise is filtered by the secondary path estimation model and then is used as a feedforward reference signal for active noise reduction, and the prediction noise and a residual signal collected by a bright area error microphone are jointly used for weight updating of an adaptive filter; the updated filter generates a reverse-phase noise elimination signal and the reverse-phase noise elimination signal is played by a secondary loudspeaker in real time so as to counteract background noise of the bright area; and closed-loop adjustment of the noise reduction effect is formed based on the sound pressure level contrast ratio of the bright and dark areas, so that the independent acoustic space is kept stable in the time-varying environment of vehicle driving. According to the method, the low noise of the bright area and the isolated sound field of the dark area in the vehicle are realized by fusing deep learning noise prediction and active noise control, and the personalized auditory experience in the vehicle can be remarkably improved.

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 present application belongs to the technical field of audio processing, and particularly relates to an audio reproduction method and system for live sound field data collection and digital signal processing. The method comprises collecting sound field data of a real acoustic space and generating a dedicated sound field parameter model; receiving an original digital audio signal and a user instruction, obtaining a dedicated sound field parameter model corresponding to the user instruction as a target dedicated sound field parameter model; performing convolution processing on the original digital audio signal and the target dedicated sound field parameter model to obtain a processed audio signal with enhanced spatial sense; and outputting the processed audio signal after multi-channel digital amplification, thereby realizing audio reproduction of the acoustic response characteristics of the dedicated sound field. The present application generates a dedicated sound field parameter model based on impulse response data collected in a real acoustic space, and the reproduced reverberation characteristics, spatial sense and sound image positioning are highly consistent with the target space, and the sound field restoration accuracy is significantly improved.

To realize localization of a sound image even with respect to an acoustic component in a low frequency band handled by a subwoofer.SOLUTION: A signal processing device includes a sound source assigning unit 61 that assigns each of a plurality of sound sources corresponding to different positions to one or more subwoofers according to a positional relationship with the sound source among a plurality of subwoofers installed in an acoustic space, and a signal processing unit 62 that generates a plurality of first sound signals respectively corresponding to the plurality of subwoofers from a plurality of sound source signals respectively corresponding to the plurality of sound sources according to a result of the assignment by the sound source assigning unit 61.SELECTED DRAWING: Figure 5

According to one embodiment of the present disclosure, an electronic device can be provided. The electronic device may include: a housing including a first speaker hole; and a speaker assembly disposed in the housing and emitting sound to the outside of the electronic device through the first speaker hole. The speaker assembly includes: a speaker including a diaphragm; a first speaker cover facing the diaphragm and spaced apart from the diaphragm; an acoustic space formed between the diaphragm and the speaker cover; a first support structure including a first portion surrounding a portion of the acoustic space; and a step structure disposed adjacent to a portion of the first portion of the first support structure and an area where the first speaker cover contacts each other and spaced apart from the speaker module.

An audio system includes a plurality of subwoofers installed in an acoustic space and a signal processing device. The signal processing device includes one or more memories storing instructions and one or more processors. The one or more processors are configured to assign each of a plurality of sound sources that correspond to different positions, to one or more subwoofers installed in an acoustic space. Each of the plurality of sound sources is assigned based on a positional relation with each of the plurality of sound sources and a plurality of subwoofers installed in the acoustic space and including the one or more subwoofers. The one or more processors are also configured to generate, from a plurality of sound source signals corresponding to respective ones of the plurality of sound sources, a plurality of first sound signals corresponding to respective ones of the plurality of subwoofers.

The invention provides a DAS water content identification method based on shaft axial acoustic attenuation characteristics. The method comprises the following steps: acquiring DAS acoustic time-domain signals of a plurality of axial positions of a shaft by using a distributed optical fiber; performing preprocessing and frequency domain transformation on the time domain signal to obtain an acoustic frequency spectrum distributed along the axial direction of the shaft; according to the law that the acoustic spectrum amplitude changes along with the position, calculating an acoustic space attenuation feature alpha (f) by adopting least square fitting based on the distance; constructing an attenuation spectrum based on the spatial attenuation characteristics, and extracting attenuation characteristic parameters related to the moisture content from the attenuation spectrum; constructing a training set and establishing a support vector machine (SVM) moisture content identification model based on a radial basis function (RBF); and inputting the actual attenuation characteristic parameters into the trained SVM model to obtain the predicted moisture content. The invention further discloses a water content identification system for executing the method and a storage medium, and the system and the storage medium are suitable for identifying the water content of the oil well shaft fluid.

Provided is, for example, an acoustic reproduction device having a structure capable of effectively vibrating particles possessed by the acoustic reproduction device. The acoustic reproduction device includes: a housing having an internal space; a driver unit accommodated in the inner space of the housing; and a powder accommodating portion in which powder is accommodated, the driver unit having a rear surface located on an opposite side of a radiation direction of sound reproduced from the driver unit, and at least a portion of the rear surface being acoustically spatially connected to the powder accommodating portion.

This sound signal processing method includes: accepting acoustic space information, first position information indicating a listening position in an acoustic space, and second position information indicating the positions of a plurality of ambient sounds in the acoustic space; accepting a first sound signal of a content sound and second sound signals related to the plurality of ambient sounds; classifying each of the plurality of ambient sounds into one of a plurality of groups on the basis of the first position information and the second position information; subjecting each of the second sound signals classified into the plurality of groups to sound processing for each classified group; and outputting the first sound signal and the second sound signal after the sound processing.

The invention discloses a coffee machine voice interaction method and system, and relates to the technical field of voice interaction. The method comprises the following steps: when the coffee machine does not perform voice interaction, detecting a kitchen space and monitoring environment background sound, and constructing and dynamically updating a kitchen environment acoustic space model at least representing a noise source physical position, acoustic characteristics and a sound reflection path; when a user voice instruction is detected, accurately positioning the mouth position of the user based on a sound reflection path in the model; performing spatial enhancement, active noise cancellation and active echo cancellation on the mixed audio signal containing the user voice instruction in parallel so as to separate out a pure user voice signal; and identifying the pure user voice signal and executing a corresponding coffee making instruction. According to the method, the acoustic space model is constructed and processed in parallel, so that the noise and echo interference problem in a complex acoustic environment of a kitchen is effectively solved, and the voice recognition accuracy and interaction fluency are remarkably improved.

This provides a sound processing method that makes your own performance sound as if it were coming from a predetermined location within the space. [Solution] In the sound signal processing method, the sound signal processing device, which is a general-purpose information processing device, receives acoustic space information, first position information of a first performer in the acoustic space, and second position information of a second performer in the acoustic space, receives a first sound signal related to the performance of the first performer from an audio interface, receives a second sound signal related to the performance of the second performer via a network, applies first binaural processing to the first sound signal based on the first position information, applies second binaural processing to the second sound signal based on the second position information, and outputs the first binaural signal after the first binaural processing and the second binaural signal after the second binaural processing from the audio interface.

The system effectively detects the flow of sound radiated within an acoustic space. [Solution] The computing device (1) includes a sound detection means (110) that detects sound from a sound source (300) at at least two locations (210, 220), and a computing means (120) that performs calculations related to the propagation direction of sound from the sound source based on the times (T0, T1) at which sound is detected at each of the at least two locations. With such a computing device, it becomes possible to intuitively and simply know the flow of sound radiated into the acoustic space.

A music synthesizer generates an audio signal using an assembly comprising hundreds or thousands of resonators. These resonators may be based on the analysis of any acoustic space, such as acoustic musical instruments, rooms, recording studios, or music halls. A machine learning network is trained to learn features of the music sound. The feature may be whether the sound is melodious. The network produces an audio effect applied to a selected frequency in the spectrum. An input signal or an excitation signal is provided to the network that processes the input by a trained model of the target audio source and configures the resonator components to generate an output audio signal based on the input signal. The network may be expanded to create novel impulse responses to create tones and timbres unique to existing audio sources, which input signals may include musical tones or include human voice inputs.

Vehicle (1), comprising a vehicle cabin (2) defining an acoustic space having specific aurally perceivable properties in a reference state, comprising an apparatus (3) for outputting an audio signal (4) in the vehicle cabin (2), characterized in that the apparatus (3) for outputting an audio signal (4) in the vehicle cabin (2) comprises:an audio outputting device (6) configured to output an audio signal (4) in the vehicle cabin (2);an acoustic impression modifying device (8) configured to generate an acoustic space modification signal (9) allowing for modifying the aurally perceivable properties of the acoustic space defined by the vehicle cabin (2) with regard to a reference state.

The application discloses a dynamic equalization and howling suppression intelligent tuning method of a digital audio processor and belongs to the technical field of computers. The method is characterized in that a distributed high-fidelity microphone array is laid out, a wideband sweep excitation signal is output, and sound pressure data are synchronously collected; potential howling modal regions are extracted through spatial Fourier transform and cross-spectral density analysis, real resonance modes are confirmed through modal matching combined with finite element simulation; the critical state of howling is determined by monitoring the growth of modal energy and the spatial deviation, and finally, local equalization filtering is activated according to the howling position. The application realizes accurate positioning and local suppression of howling, maximally retains the original sound quality, and improves the stability and adaptive ability of an audio system in a complex acoustic space.

A method for vehicle occupant input includes acquiring a vehicle occupant data from a plurality of occupants of a vehicle, where the vehicle occupant data includes an acoustic spatial data and biometric data including at least voice characteristic data. The method further includes associating one or more positions of a plurality of positions in the vehicle with an occupant information. The occupant information associated with a position includes the biometric data for an occupant at the position based on the vehicle occupant data acquired and processing a first audio input from a first occupant of the vehicle using the voice characteristic data associated with a first position of the first occupant in the vehicle.

This sound signal processing method involves: at a first terminal, receiving acoustic space information, first position information of a first performer in the acoustic space, and second position information of a second performer in the acoustic space, and receiving, from an audio interface, a first sound signal pertaining to the performance of the first performer; outputting, from the first terminal and via a network, the first sound signal to a second terminal of the second performer; receiving, at the first terminal and via the network, a second sound signal pertaining to the performance of the second performer; on the first terminal, subjecting the first sound signal to first binaural processing on the basis of the first position information and subjecting the second sound signal to second binaural processing on the basis of the second position information in the first terminal; and outputting, from the audio interface on the first terminal, the first binaural signal after the first binaural processing and the second binaural signal after the second binaural processing.

This invention provides an audio processing system and method based on active sound field control, belonging to the technical field of audio processing technology. The method includes: generating a mixed acoustic signal and transmitting the mixed acoustic signal through a transmitting unit; synchronously acquiring a composite frequency band mixed acoustic signal formed after the mixed acoustic signal propagates in an acoustic space through a receiving unit; separating the composite frequency band mixed acoustic signal into an ultrasonic echo stream and an audible ambient stream; constructing a three-dimensional acoustic map based on the ultrasonic echo stream, and generating a room impulse response from the transmitting unit to a preset listener position based on the three-dimensional acoustic map; determining the ambient noise field based on the audible ambient stream; and generating an output audio signal based on the room impulse response and the ambient noise field, and playing it through the transmitting unit. This invention solves the problem of low environmental perception accuracy, thereby improving the accuracy of environmental perception.

A signal processing method assigning each of a plurality of sound sources that correspond to different positions, to one or more subwoofers installed in an acoustic space, in which each of the plurality of sound sources is assigned based on a positional relation between each of the plurality of sound sources and a plurality of subwoofers installed in the acoustic space and including the one or more subwoofers; and based on results of assignment of each of the plurality of sound sources, generates, from a plurality of sound source signals corresponding to respective ones of the plurality of sound sources, a plurality of first sound signals corresponding to respective ones of the plurality of subwoofers.

A method of managing an arrangement of acoustic devices in an acoustic space receives information about the acoustic space, a position of at least one sound source in the acoustic space, and a position of at least one noise source in the acoustic space, calculates, for the acoustic space, the arrangement of the acoustic devices corresponding to the received position of the at least one sound source and the received position of the at least one noise source, wherein the acoustic devices include microphones, and outputs the calculated arrangement of the acoustic devices.

The embodiments described herein provide an adaptation and adjustment (A2) mechanism for multilingual speech recognition models that combines both adaptation and adjustment methods as an integrated end-to-end training to improve the model’s generalization and mitigate the long-tail problem. Specifically, the multilingual language model mBERT is utilized and converted into a self-attention decoder. Furthermore, to explore the acoustic space beyond the text space, a cross-attention module is added on top of the self-attention layers of mBERT in the encoder. The joint training of the encoder and mBERT decoder can bridge the semantic gap between speech and text.

This invention provides an audio signal processing method that can achieve natural ambient sound in a virtual space while keeping processing load down. [Solution] The sound signal processing method receives acoustic space information, first position information indicating the listening position in the acoustic space, and second position information indicating the positions of multiple ambient sounds in the acoustic space, receives a first sound signal of content sound and second sound signals relating to the multiple ambient sounds, classifies each of the multiple ambient sounds into one of a plurality of groups based on the first position information and the second position information, applies sound processing to each of the second sound signals classified into the plurality of groups, outputs the first sound signal and the second sound signal after sound processing.

A musical synthesizer produces an audio signal using a set including hundreds or thousands of resonators. The resonators can be based on analysis of any acoustic space such as an acoustic instrument, room, studio, or concert hall A machine learning network is trained to learn the characteristics of a musical sound. The characteristic may be whether the sound is pleasing to the human ear. The network produces audio effects applied to selected frequencies in the spectrum. An input or excitation signal is provided to the network, which processes the input through a trained model of a target audio source and configures the set of resonators to produce an output audio signal based on the input signal. The network may be expanded to create novel impulse responses creating tones and timbre unique to existing audio sources, the input signal may include musical tones or include vocal inputs.

A vehicle (1) comprising a vehicle cabin (2) defining, in a reference state, an acoustic space having certain acoustically perceptible properties; a device (3) for outputting an audio signal (4) in the vehicle cabin (2), characterized in that the device (3) for outputting an audio signal (4) in the vehicle cabin (2) comprises: - audio output means (6) configured to output an audio signal (4) in the vehicle cabin (2); - acoustic impression modifying means (8) configured to generate an acoustic space modifying signal (9) allowing to modify the acoustically perceptible properties of the acoustic space defined by the vehicle cabin (2) with respect to the reference state.

A method for delivering auditory feedback to a driver in a cabin of a road vehicle, the vehicle comprising a plurality of wheels and an electric motor coupled to at least one of the plurality of wheels and configured to drive the at least one of the plurality of wheels, the cabin containing a sound space, the sound space includes a sound location mesh, the method comprising: determining a torque transmitted to at least two of the plurality of wheels; determining a wheel torque profile of the vehicle based on the determined torque; determining a main sound position in the sound space according to the wheel torque distribution; and inputting the primary sound location to a spatial audio system configured to communicate auditory feedback to the vehicle cabin such that the auditory feedback is perceived by the driver as originating from a virtual audio source located at the primary sound location.

[Problem] To provide a multi-channel audio device with which it is possible to achieve an environment where it seems as if acquaintances such as family and friends who live geographically apart therefrom are living nearby.　[Solution] On the basis of a sound field analysis result in a virtual acoustic space in which a virtual sound source is set at a position specified by a relative positional relationship with a listening point P, a multi-channel audio device 1a, 1b generates multi-channel audio data for making sound audible when collected sound data of an acquaintance's daily-life sounds, which is received from another multi-channel audio device 1 via a network 5, is emitted from the virtual sound source in the virtual acoustic space. The multi-channel audio device then reproduces the generated multi-channel audio data as audio signals for a plurality of channels and outputs the same from speakers 2a-1 to 2a-5, 2b-1 to 2b-5 connected thereto.

The invention relates to the technical field of electric digital data processing, and discloses a sound effect optimization method and device, equipment and a storage medium, which are used for improving the adaptive capacity of a sound field. The sound effect optimization method comprises the following steps: acquiring relative position relation data between each loudspeaker box and a user; based on the relative position relation, acoustic space modeling is carried out in combination with analysis of room impulse response, and a real-time space model containing geometric attributes and acoustic propagation characteristics is obtained; calculating and distributing sound channel mapping weights based on the real-time space model, and generating a sound channel distribution scheme dynamically changing along with the position of the user; and according to the sound channel allocation scheme, carrying out real-time adjustment of an equalizer curve, delay compensation and phase parameters on each sound box.

An arrangement design support method for microphone includes receiving an input condition including an acoustic space and positions of a plurality of objects in the acoustic space, calculating an arrangement distribution of the microphone corresponding to the received input condition in the received acoustic space, outputting the calculated arrangement distribution, and correcting a position of another object in conjunction with correction of a position of at least one object among the plurality of objects based on information on an installation condition included in each of the plurality of objects, in a state where a request for correction of the input condition is received.

A system and method for accurately estimating engine noise at a virtual microphone location, such as an ear location of an occupant, in an acoustic space in order to enhance the performance of an engine order cancellation (EOC) system is provided. A set of weights and transfer functions dependent on various vehicle parameters, such as frequency, load, and speed, can be employed to estimate the noise at a location where no physical microphone exists. Accurate estimation of engine noise at a virtual location, such as an ear location of an occupant, can be achieved using a frequency dependent weighted sum of filtered and unfiltered error signals measured at microphones mounted at different locations, such as a vehicle cabin, within the acoustic space that can not be located near the virtual location.

This invention provides a control method and control system for constructing an independent acoustic space in an automotive cabin, applied in the field of automotive cabin sound field control technology. It inputs real-time acquired multi-channel vibration signals into a deep learning noise prediction model to obtain predicted in-vehicle background noise values ​​for future times. The predicted noise is filtered by a secondary path estimation model and used as a feedforward reference signal for active noise reduction. This signal, along with the residual signal acquired by the bright-area error microphone, is used to update the weights of an adaptive filter. The updated filter generates an inverse-phase noise cancellation signal, which is played in real-time by a secondary speaker to cancel out bright-area background noise. A closed-loop adjustment of the noise reduction effect is constructed based on the contrast between bright and dark sound pressure levels, ensuring the stability of the independent acoustic space in the time-varying environment of vehicle operation. This invention achieves low noise in bright areas and isolated sound fields in dark areas by integrating deep learning noise prediction and active noise control, significantly enhancing the personalized in-vehicle listening experience.