73 results about "Auditory perception" patented technology

The invention relates to the technical field of electroencephalogram signal processing, in particular to an ontology brain wave audio auditory perception synchronous feedback method, device and system and electronic equipment. The method comprises the following steps: receiving electroencephalogram signals of a collected user on line from electroencephalogram collection equipment through an upper computer, obtaining electroencephalogram signals of a specified frequency band from the electroencephalogram signals, and extracting corresponding electroencephalogram characteristics; according to the electroencephalogram features or preset rhythm parameters, the electroencephalogram signals of the specified frequency band are segmented into a plurality of electroencephalogram segments, a plurality of audio expressions corresponding to the electroencephalogram segments are generated, and feature parameters of the audio expressions are determined according to the electroencephalogram features of the corresponding electroencephalogram segments; generating brain wave audio representation data according to the audio representation corresponding to the electroencephalogram signals of the one or more designated frequency bands, and obtaining brain wave audio according to the brain wave audio representation data. Therefore, the physiological suitability of nerve regulation and control and the artistic expressivity of audio generation are met at the same time, and organic unification of nerve regulation and control and audio generation is achieved.

An auditory neural interface device for sound perception by an individual that may be used as a hearing aid. The auditory neural interface device includes a receiver configured to receive sound signals, a processor operably connected to the receiver and configured to encode a received sound signal as a multi-channel neurostimulation signal, and a neurostimulation device operably connected to the processor and configured to apply the multi-channel neurostimulation signal to a neurostimulation electrode of the individual. The neurostimulation signal is configured to directly stimulate afferent sensory neurons of the central nervous system of the individual and thereby to elicit, for each channel of the neurostimulation signal, one or more non-auditory, preferably somatosensory, perceptions in a cortex area of the individual. Each channel of the neurostimulation signal is associated with a different non-auditory perception.

The invention discloses a non-therapeutic-purpose hearing and perception training device for non-invasive free mouse training and auditory cortex plasticity stimulation. The device comprises a soundproof box, a training device body in the soundproof box and a processing control system located outside the soundproof box. The training device main body in the soundproof box comprises a training box body, a water and air supply device, an animal action sensing device, an animal position sensing device, a loudspeaker and an illuminating lamp; the training box body comprises an open box and a dark box, and the animal position sensing device is arranged at the relative position of the junction of the open box and the dark box and the relative position of the side wall of the dark box; the processing control system located outside the soundproof box comprises a water and gas control device, a power amplifier and a control computer. The invention further discloses a method and application of the training device in auditory cortex plasticity induction and auditory perception training, and the training device has wide application prospects.

The invention discloses an environmental sound classification and noise reduction method and system for an intelligent Bluetooth hearing-aid earphone. The method comprises the following steps: S1, collecting background noise original audio signals and real-time binaural sound field signals in a typical scene; s2, Mel spectrum features and auditory perception features are extracted from each typical scene, fusion features are calculated, dimension compression is carried out, and a scene feature vector library is obtained; s3, extracting a live sound field feature, and extracting a scene feature vector matched with the live sound field in the scene feature vector library; s4, calculating a sound source direction correction coefficient, and calculating a corrected sound source direction; s5, calculating cross-modal interaction characteristics, then calculating noise suppression intensity and sound source gain intensity, and generating an audio after noise reduction; and S6, generating a synchronous stereo audio signal. The method can solve the problem that the traditional method is difficult to distinguish different types of background noise, so that the voice of a dialogue is inhibited by mistake, and the voice enhancement effect is poor.

The invention discloses an intelligent exoskeleton bone auxiliary conduction hearing aid system capable of being remotely controlled and having an electroencephalogram control function, and relates to the technical field of intelligent rehabilitation robots and hearing aid devices. The wearable mechanical part comprises a flexible actuator, an elastic fabric base material, an inertial measurement unit IMU, a plantar pressure sensor array, a surface myoelectricity EMG sensor and an electroencephalogram EEG sensor. And the information processing communication part comprises a central controller, a bone conduction hearing aid module, a multi-mode sensor, an embedded SoC, a DSP / AI accelerator, a 4G / 5G / Wi-Fi module and a power management unit. The flexible exoskeleton walking aid system and the bone conduction hearing aid module are integrated, the electroencephalogram EEG sensor is additionally arranged to achieve the electroencephalogram control function, and cooperation of the three functions of movement assistance, auditory perception and neural intention recognition is achieved. A user can directly control the exoskeleton action mode through electroencephalogram signals, meanwhile, intelligent assistance of lower limb joints is obtained in the walking process, and environment sounds and voice prompts are clearly received in a bone conduction mode. According to the system, the perception ability, the control flexibility and the social participation degree of old people or rehabilitation patients who are inconvenient to move and accompanied with hearing impairment in a complex environment are remarkably improved, and more natural and convenient man-machine interaction experience is provided for users.

The invention, which relates to the technical field of the simulation machine pet system, discloses an AI-driven full-perception simulation machine pet system comprising an AI training module, an olfactory perception module, an auditory perception module, a visual perception module, a navigation positioning module, a touch simulation module and a motion control module. The AI training module is used for generating a personalized behavior model through a machine learning algorithm based on the user behavior data and the environment data, and driving a mechanical pet to simulate the learning and growth process of a biological pet; the olfaction sensing module is used for collecting environment gas data through a gas sensor array, and identifying and feeding back a security threat signal to the main control system in combination with the behavior model output by the AI training module; the auditory perception module is used for receiving a sound wave signal through a microphone array and triggering an instruction response action generated by the AI training module after the sound wave signal is analyzed by a voice recognition algorithm; the visual perception module is used for capturing environment image data through a spherical camera.

The technical scheme of the present application provides a dynamic range control circuit, an audio processing chip and an audio processing method thereof, wherein the dynamic range control circuit has a plurality of parallel gain generation modules and an output module, and each gain generation module has a separate gain generator and a gain smoothing processing module. In the same gain generation module, the gain generator is used for gain processing of an input signal, and the gain smoothing processing module is used for setting the compression time and release time of the gain generation module based on the output gain of the gain generator. It can be seen that in each gain generation module, the compression time and release time of each gain generation module can be set by the respective smoothing processing module, so that the compression time and release time of different gain generation modules are separated, which can greatly improve the tuning of the audio power amplifier and the user's auditory perception.

This utility model discloses a popular science interactive display device. Key technical features include a display box with display windows on its periphery for observing the items inside. A vibration switch is installed on the inner side of the top cover of the display box. It also includes a sound module pre-stored with audio data, and the vibration switch controls the sound module to play the audio. This utility model allows the vibration switch to play pre-stored sounds of items by tapping the cover, combining auditory perception with physical interaction to enhance audience participation and exploration interest, and strengthen the immersive learning experience of scientific knowledge.

This invention discloses a music bandwidth expansion method based on auditory perception attention generative adversarial networks (GANs). The method comprises two parts: training and prediction. The prediction part uses the trained network model to complete the bandwidth expansion task. The training part includes the following steps: Step 1, data preprocessing: preprocessing the original music dataset to obtain high-frequency music signals and corresponding low-frequency music signals as training sample pairs; Step 2, model architecture design: training the training sample pairs from Step 1 to obtain a GAN model. The GAN model includes a generator for generating sample data and a multi-discriminator for determining the source of the input sample data. This invention incorporates a multi-discriminator into the network model, which to some extent avoids the problem of overly smooth high-frequency components in the expanded spectrogram.

The invention discloses a multi-modal aliasing sound signal separation method based on a lightweight convolutional neural network, relates to the technical field of signal processing, and aims to remove noise and perform normalization processing by preprocessing collected multi-modal aliasing sound signals. And then extracting features by using a Mel spectrogram, and converting the sound signal into a frequency spectrum representation conforming to auditory perception of human ears. Then, the extracted features are trained and learned through a constructed lightweight convolutional neural network model OfficientNet-B0, and a trained model weight is obtained; and finally, separating and identifying the new multi-modal aliasing sound signals by using the model, thereby realizing accurate classification of different types of damage signals, and effectively solving the problem that the multi-modal aliasing sound signals are difficult to accurately separate in a complex environment.

Provided are an audio peak limiting system and method, which, by setting a moving maximum window to drive gain calculation, and in combination with matching a moving maximum window length to a delay duration of an audio input signal, suppress a risk of overshoot while enabling a user to flexibly adjust a suitable attack time, and result in a smoother gain curve and reduce distortion in dynamic range processing, thereby achieving a more natural auditory perception.

The application provides a volume adjusting method and a vehicle, and relates to the technical field of intelligent cockpits. The method comprises the following steps: in response to a volume adjusting instruction, obtaining a current volume value and a target volume value indicated by the volume adjusting instruction; in the case that a variation range between the current volume value and the target volume value exceeds a preset variation range, obtaining an upper limit value of an auditory perception step, the upper limit value of the auditory perception step being used for indicating a single maximum variation range in which an ear of a human being cannot perceive a volume mutation; generating an intermediate volume sequence based on the current volume value, the target volume value and the upper limit value of the auditory perception step; and adjusting the current volume value in sequence according to the intermediate volume sequence until the target volume value is reached. The technical problem of insufficient noise suppression effect of a vehicle-mounted full-scene volume mutation in the related art is solved.

The embodiment of the invention provides an audio signal processing method, electronic equipment, a storage medium and a program product, and the method comprises the steps: carrying out the time-frequency conversion of a to-be-processed audio segment, and extracting a key frequency band feature, a time-frequency fusion feature and an audio semantic feature; comprehensive representation of the audio signal in three dimensions of local frequency domain details, time-frequency dynamic change and high-level semantic content is realized; the first fusion feature with complementary information and higher representation capability is generated by fusing the three features, and quality analysis is performed based on the first fusion feature, so that the accuracy and reliability of audio quality evaluation are remarkably improved, and the audio quality evaluation is closer to human subjective auditory perception.

This application discloses a speech synthesis method, apparatus, device, and storage medium. The method involves analyzing the original text to be synthesized to obtain a phoneme sequence; inputting the phoneme sequence into a configured speech synthesis model to obtain synthesized speech output by the model. The speech synthesis model is a final speech synthesis model after parameter adjustment of the basic speech synthesis model, using the scoring results of multiple candidate speech samples corresponding to the input test text synthesized by the basic speech synthesis model as reward signals. The scoring results of each candidate speech sample conform to the user's auditory perception goals. This application adds user auditory feedback signals (i.e., the scoring results as reward signals) to the training process of the speech synthesis model, guiding the speech synthesis model to optimize model parameters in a direction that better conforms to the user's auditory perception, making the synthesized speech more in line with the user's auditory perception goals and improving the speech synthesis effect.

The invention relates to the technical field of intelligent auditory enhancement and digital signal processing, in particular to an intelligent hearing aid mode switching system and method, and the system comprises a panoramic sound field sensing unit which is used for calculating a sound field uncertainty index; the body motion intention capturing unit is used for resolving gaze point transfer intensity and a real-time motion vector; the heterogeneous feature decoupling and fusion unit is used for being connected with the capturing unit; when the sound field uncertainty index is greater than a preset sound field uncertainty threshold value and the fixation point transfer intensity is greater than a preset fixation point transfer intensity threshold value, generating a parameter freezing signal; the parameter freezing signal is used for calculating a beam lead compensation angle; the wave beam pointing is driven to perform same-direction advanced deflection; the auditory perception feedback optimization unit is used for generating a correction feedback signal when the definition index is reduced; according to the method, the problem of frequent mistaken switching in a high-dynamic complex environment is solved, and the continuity and the stability of auditory perception of a user in a sound source searching process are ensured.

The invention discloses an intelligent coal gangue identification method based on transfer learning and machine auditory spectrum features, which comprises the following steps: acquiring test bed and underground sound signals, extracting CASP advanced auditory perception features, and constructing a cross-domain transfer convolutional neural network model optimized by maximum mean difference, domain adversarial and covariance joint loss, rich laboratory data is effectively utilized to solve the problem of scarcity of underground samples, and cross-working-condition high-precision coal gangue identification is realized.

This invention relates to an intelligent method for identifying abnormal motor noises based on time-frequency features and auditory adaptation, belonging to the field of motor fault detection technology. The method includes: real-time acquisition of motor operating sound signals through a multi-directional acoustic signal acquisition array, followed by signal preprocessing and dynamic framing; generation of a time-frequency spectrum using short-time sliding window time-frequency conversion, establishing an auditory baseline for normal operation sound using auditory perception adaptation dynamic weighting technology, and performing hierarchical weighting processing on the time-frequency spectrum to generate fused time-frequency weighted features; construction of a time-frequency weighted feature-enhanced residual network model, achieving abnormal feature extraction and identification through cross-dimensional fusion mechanisms, fault feature transfer learning mechanisms, and fault feature attention mechanisms; and completion of status identification and alarm response using a dynamic adaptation inference mechanism and a hierarchical linkage alarm system. This invention effectively improves the accuracy and real-time performance of motor abnormal noise identification and is suitable for motor status monitoring in complex industrial environments.

This application provides a virtual playback simulation method, apparatus, device, and medium, relating to the fields of audio signal processing and audio playback device simulation technology. The method includes: acquiring an input audio signal and complex frequency response data of a target audio playback device, the response data including amplitude frequency response data and phase frequency response data; adaptively selecting a target algorithm from multiple preset virtual playback simulation algorithms according to preset application constraints; the multiple preset algorithms have different delay characteristics, accuracy levels, and computational complexity, and at least one algorithm adopts a frequency resolution processing method matching the characteristics of human auditory perception; using the target algorithm, processing the input audio signal based on the complex frequency response data to generate an output audio signal simulating the playback effect of the target audio playback device. This application improves the flexibility, accuracy, real-time performance, and perception optimization effect of virtual simulation through the organic combination of adaptive algorithm selection and auditory perception optimization.

The application relates to the field of hearing aids, in particular to a hearing aid sound compensation method, which comprises a system architecture module, the system architecture module is internally provided with an implementation module, an innovation module and a processing module, and the implementation module, the innovation module and the processing module are mutually electrically connected; the implementation module is internally provided with a data acquisition module, a sound compensation model module, a digital signal processing module and a sound output module, hearing data of a user is acquired, a targeted sound compensation model is constructed, and a digital signal processing technology is adopted to realize accurate compensation on a sound signal output by the hearing aid. Experimental results show that the method has obvious advantages in improving the auditory perception quality of the user, provides a more intelligent and personalized hearing solution for the hearing impaired, and can effectively increase the hand-on performance and self-updating performance of the user through individual training and a self-updating module, so that the user can conveniently use the hearing aid.

This invention relates to the field of early warning and control technology for airport bird flocks, specifically disclosing a radar-based system and method for timely early warning and control of airport bird flocks. The system includes the following steps: obtaining the minimum spatial distance value among individual bird flocks and comparing it with the radius of the warning airspace to obtain an early warning signal; obtaining the spatial location of individual bird flocks at each detection time node; calculating the predicted limit value of the bird flock's flight path at detection time node m and comparing it with the radius of the warning airspace to obtain an early warning signal or a predicted signal; reducing the impact of laser and sound waves on the visual and auditory perception of the bird flock, avoiding unpredictable effects caused by stressful flight patterns after the flock is stimulated, reducing the use of laser and sound waves, avoiding interference with other organisms in the airport's surrounding environment or other aircraft during flight, and reducing safety hazards.

The invention discloses an acoustic simulation method and system based on a low-frequency waveguide digital grid and geometric modeling, and relates to the technical field of acoustic simulation. A three-dimensional scene model composed of triangular patches is imported, and sound source parameters and the position of a receiver are initialized; based on the three-dimensional scene model, the sound source parameters and the receiver position, multiple sound field propagation paths are obtained through geometric acoustic pre-analysis, and initial perception importance parameters are calculated for each sound field propagation path. And distributing each sound field propagation path to a first calculation strategy or a second calculation strategy for processing according to the initial perception importance parameter. According to the method, through geometric acoustic pre-analysis and real-time dynamic evaluation, a high-precision calculation strategy is only allocated to a key sound field propagation path with high perceptual contribution degree, and an efficient geometric method is adopted for a large number of secondary paths. According to the resource scheduling strategy based on auditory perception, computing resources are highly focused, and meaningless consumption of secondary components is avoided.

The invention is suitable for the technical field of audio signal processing, and provides a sparse auditory pulse coding method and device fusing a masking effect and a dynamic threshold. According to the auditory rarefaction method provided by the embodiment of the invention, a human auditory perception mechanism can be combined, and the threshold group characteristics are utilized to realize time sequence pulse coding, so that the audio signal can directly adapt to the pulse neural network model, the coding efficiency and fidelity are improved, and meanwhile, the data redundancy is reduced. While the perception quality is ensured, the number of pulse events can be remarkably reduced, the energy efficiency and accuracy of a recognition task are improved, and the method is naturally adaptive to brain-like hardware and a pulse neural network. According to the embodiment of the invention, the masking effect of psychoacoustics is fused into the pulse coding process for the first time, and is highly consistent with the feeling and processing mode of organisms on sound signals. The biological reasonability is relatively high.

An in-ear audio transducer such as a single earphone or a pair of earphones produces audio which accounts for frequency detected hearing impairment and auditory masking conditions spanning frequencies expected to be encountered by the user, thereby improving auditory perception without having to increase overall volume as much as in the prior art. The audio transducer(s) communicates with an audio base unit configured to output modified multichannel digital audio data. The in-ear audio transducer element has a processing unit, a plurality of transducer amplifiers and a plurality of acoustic elements.

This invention discloses a multi-labeled sound recognition method for birds, including a training phase and an inference phase. The training phase includes the following steps: inputting audio data labeled with multiple tags, and extracting three complementary acoustic representations in parallel through a multi-view feature extraction module. This application uses parallel configuration of Mel spectrogram extraction submodules, CQT spectrogram extraction submodules, and CWT spectrogram extraction submodules to capture complementary features in the audio signal related to human auditory perception, such as energy distribution, pitch and harmonic structure, transients, and sharp calls. Furthermore, the three acoustic representations are aligned in the time dimension to form a comprehensive multi-view feature representation. Compared to existing technologies using fixed view combinations or single feature extraction methods, this design effectively avoids the problem of single-view failure due to noise or occlusion, providing a rich and reliable feature foundation for subsequent recognition tasks and significantly improving feature adaptation capabilities in complex soundscape environments.

The invention discloses a keyboard prompting method and system for footstep sound in a game, and the method comprises the steps: capturing an audio signal of an environment in the game in real time, carrying out the spectrum analysis and footstep sound frequency feature separation of the audio signal, and extracting the direction and distance parameters of the footstep sound; mapping the azimuth and distance parameters into a keyboard area control instruction; generating a dynamic visual prompt signal according to the keyboard area control instruction; and outputting the dynamic visual prompt signal to an RGB keyboard light control system, and driving light in a corresponding keyboard area to correspondingly display according to the dynamic visual prompt signal so as to realize visual prompt of the direction and the distance of footstep sound in a game. By means of the embodiment of the invention, auditory perception can be assisted in a visual mode, the intuition and identifiability of sound information are improved, the game operation threshold is reduced, and the immersion is enhanced.

The invention relates to the technical field of pipeline water leakage detection and fire fighting equipment, and discloses a fire hydrant device and method for intelligent detection of pipeline water leakage. In order to solve the problems of limited operation time, high experience dependency, environmental noise interference and the like in the traditional manual detection technology, the invention provides an integrated solution that an embedded control unit, a broadband underwater sound sensing module and a solar energy supply system are arranged on a fire hydrant base body, and pipeline sound wave signals are collected in real time. After the preprocessing of pre-emphasis, 43-dimensional feature vectors are extracted from three aspects of time domain, frequency domain and auditory perception, and leakage probability and confidence coefficient prediction is realized in combination with a pre-trained SVM classification model, so that the detection efficiency and the confidence coefficient are improved; and the cloud platform receives the data based on the MQTT protocol and judges whether an early warning mechanism is triggered or not. The device supports long-term unattended operation, significantly reduces the manual inspection cost through a confidence threshold and a trigger alarm mechanism, is suitable for intelligent monitoring and early leakage early warning of a municipal water supply network, and is suitable for popularization and application.

The application relates to the technical field of automobile detection, in particular to an abnormality detection method based on auditory perception. The method comprises the following steps: S1, performing Mel band analysis on an audio signal to obtain a Mel spectrogram; S2, setting a frequency range of interest, calculating the total energy of the Mel spectrum in the frequency range of interest, and performing smoothing processing on the total energy; S3, calculating the mean value and the standard deviation according to the smoothed energy, and setting a dynamic detection threshold based on the mean value and the standard deviation; S4, monitoring the time point at which the energy exceeds the dynamic detection threshold as a preliminary abnormal point, calculating the frequency band energy difference between the preliminary abnormal point and the previous and subsequent time points, and identifying an energy prominent frequency band according to the difference; S5, verifying whether the energy prominent frequency band is continuous and whether the length of the continuous frequency band reaches a preset minimum value, and if yes, determining that the preliminary abnormal point is an effective abnormal point; and S6, outputting the time, the center frequency, the frequency range and the bandwidth information of the effective abnormal point.

This application relates to a speech encoding method performed by a computer device the method, including: performing subband decomposition on a target speech signal to obtain a plurality of subband excitation signals; obtaining an auditory perception representational value that corresponds to each subband excitation signal; determining at least one first subband excitation signal and at least one second subband excitation signal from the at least two subband excitation signals; obtaining a gain of each of the at least one first subband excitation signal relative to a preset reference excitation signal as an encoding parameter that corresponds to the first subband excitation signal; obtaining a corresponding encoding parameter that is obtained by quantizing each of the at least one second subband excitation signal; and performing encoding on each subband excitation signal based on the encoding parameter corresponding to the subband excitation signal.

The application discloses a speech enhancement model training method and system based on a subband loss function, a terminal and a medium, and relates to the technical field of speech enhancement. The method comprises the following steps: obtaining noisy speech and clean speech, and determining the logarithmic power spectrum of the enhanced speech and the logarithmic power spectrum of the target speech respectively; based on the mel scale, the logarithmic power spectrum of the enhanced speech and the logarithmic power spectrum of the target speech are segmented respectively to obtain the subband of the enhanced speech and the subband of the target speech; the subband loss value between each enhanced speech subband and the corresponding target speech subband is determined; a perceptual weight is assigned to each subband loss value, and the overall loss value is determined to guide the speech enhancement model training. The application can guide the speech enhancement model to exhibit differentiated learning behavior for different frequencies, so as to make the speech enhancement model output speech that is more in line with the human auditory perception law, and significantly improve the listening comfort after speech enhancement.

The application provides a brain electrical response deep learning classification and identification method based on underwater acoustic signal stimulation, which is based on brain electrical signals and combines deep learning to classify and identify underwater acoustic target signals. The method fully utilizes the differences in the subjective sensitivity of people to underwater noise and underwater acoustic signals, the rapid auditory perception of the human brain to different types of underwater acoustic signals and the differences in the conscious information extraction, takes the brain electrical signals as the main input signals, and classifies and identifies the underwater acoustic signals after corresponding processing of the brain electrical signals. The application plays the "filtering characteristics" of the human brain which is more advanced and more targeted than computers, and the characteristics of more accurate classification and identification, and can improve the poor target recognition effect in a low signal-to-noise ratio environment in the traditional underwater acoustic target classification method.