1734 results about "Electrophonic hearing" patented technology

A neural end-to-end system is provided for the face and voice preserving translation of videos. The system is a pipeline of multiple models that produces a video of the original speaker speaking in the target language with modified lip movement to match the target speech, while preserving emphases and prosody of the original speech, and voice characteristics of the original speaker. The pipeline starts with automatic speech recognition including emphasis detection, followed by the translation model. The translated text is then synthesized by a Text-to-Speech model that recreates the original emphases in the target sentence. The resulting synthetic speech is then converted back to the original speakers' voice using a voice conversion model. Finally, to synchronize the lips of the speaker with the translated audio, a generative model generates frames of adapted lip movements which are combined with the audio to produce the final output. The disclosure further describes several use-cases and configurations that apply these techniques to video conferencing, dubbing, low-bandwidth transmission, speech enhancement and assistive technology for the hearing impaired.

A system may include a storage device, configured to store computer-executable instructions. A system may include an ear-bud configured to be positioned within an ear canal of a user, the ear-bud comprising: a speaker, a microphone; and one or more processors in communication with the storage device, wherein the computer-executable instructions, when executed by the one or more processors, cause the one or more processors to: obtain a user hearing profile, obtain an equal-loudness hearing profile, receive audio data from the microphone, and generate a second audio data based on a first sound-pressure level, a second sound-pressure level, a first frequency; and cause the speaker to emit the second audio data within the ear canal of the user, such that the user perceives the audio data as if the user has normal hearing.

A receiver-in-canal (RIC) hearing device comprises a housing configured for deployment behind an ear of a user of the hearing device. A power source, audio components, a communication device, and a controller are respectively disposed in the housing. A cable assembly comprises a cable, a receiver disposed at a distal end of the cable, and a connector disposed at a proximal end of the cable and configured to attach to the housing. An optical sensor is disposed in the connector and configured to generate a proximity signal based on proximity of the optical sensor to skin at or near the user's ear. The controller is configured to operate the hearing device in a nominal power mode in response to the proximity signal exceeding a threshold and to operate the hearing device in a low power mode in response to the proximity signal falling below the threshold.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The invention belongs to the technical field of hearing testing, and relates to a self-adaptive hearing screening optimization method based on acoustic feature analysis, which comprises the following steps: generating audio data with different signal-to-noise ratios through a constructed audio library, measuring an acoustic transfer function of a user ear canal by using a probe microphone, and generating a personalized acoustic transfer function in combination with a head-related transfer function. Time domain and time frequency features are extracted by means of EEG data, and the auditory reaction ability and the spatial auditory ability of the user are quantified in combination with the spatial positioning features of the binaural simulation microphones; the method comprises the following steps: constructing a multi-modal auditory feature vector, weighting features in combination with a multi-head attention mechanism, predicting the hearing age of a user through a time sequence Transform encoder in combination with the age of the user and a standard threshold value, and evaluating hearing loss according to a prediction result; the individual difference of each user can be accurately adapted, the defect that individual difference and complex environmental noise are neglected in a traditional hearing screening method is overcome, and therefore the accuracy of a screening result is improved.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus for processing audio through a neural network contained in a hearing device. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

The disclosure generally relates to a method, system and apparatus for processing audio through a neural network contained in a hearing device. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

A loudspeaker system and method can measure a specific user's hearing and implement compensatory or corrective processing to address the user's hearing deficiencies. The user's hearing acuity may be determined by (i) headphone techniques in which frequency-based hearing thresholds are determined; (ii) a loudspeaker system set up as intended for use in an acoustic space to emit tonal stimuli; or (iii) inducing, acquiring, and interpreting otoacoustic emissions. Once the hearing profile is determined, appropriate signal processing parameters can be used to generate a corrected audio output signal adjustment. The administered hearing test results can include a plurality of hearing loudness threshold levels at respective test frequencies. The hearing correction system's corrected audio output can be generated from corrected loudness values at selected correction frequency sub-bands.

A fitting apparatus for a hearing device includes a memory, the memory having stored thereon a plurality of embedding vectors and related solutions for possible hearing issues with a hearing or computing device. The fitting apparatus is configured to:receive, via a user interface, a first signal indicative of a natural language input indicative of an issue experienced by a user;determine an embedding based on the natural language input;generate, based on the embedding, a first embedding vector;determine a closest match between the first embedding vector and an embedding vector of the plurality of embedding vectors; andsend, to the user interface, a second signal indicative of a reply output, the reply output comprising information related to a solution of the related solutions for the issue experienced by the user.

The invention provides a sound coordination method and system based on a tinnitus condition, and relates to the technical field of tinnitus treatment.The method comprises the steps that a tinnitus feature vector of a patient is established through broadband hearing testing and three-dimensional sound field modeling, and a dual-mode treatment audio is generated based on the tinnitus feature vector; the dual-mode treatment audio comprises offset sound waves with opposite phases and masking sound waves with matched frequency bands; establishing a dynamic mapping relationship between a game interaction event and the audio parameters of the dual-mode treatment audio; and dynamically adjusting treatment parameters according to the dynamic mapping relation and the real-time physiological feedback data. The tinnitus characteristic vector of the patient is accurately established through comprehensive application of broadband hearing testing, three-dimensional sound field modeling and binaural sound field matching, and the treatment audio is dynamically adjusted according to personalized characteristics of tinnitus. According to the personalized sound coordination method, the tinnitus symptom can be effectively relieved according to the tinnitus symptom of each patient, and the treatment compliance of the patient is improved.

Methods and apparatuses are described for modulating multiple integrated neural networks to alter composite sensory processes, such as audition or hearing. These methods and apparatuses may be used for therapeutic and non-therapeutic uses, including enhancing entertainment and communication, by providing a cranio-cervical tuning apparatus worn in or around the outer ear or auricle. These methods and apparatuses may include functional neurosensory bias for neurosensory scrambling neuromodulation to influence composite or multi-modal sensory processes.

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

An earplug having a bamboo attenuator and a tapered body portion that includes a central shaft with bamboo attenuator disposed within and extending throughout an entirety of a hollow sheath, and contact structures which are flexible and have a successively smaller size moving from a lateral end of the tapered body portion to a medial end of the tapered body portion, and a stopper portion attached to the lateral end of the tapered body portion. The earplug provides passive, nonlinear attenuation of incoming sound to provide hearing protection to a user while allowing for comfortable use.

The invention relates to the field of aviation voice signal processing, and discloses a voice recognition compensation pilot earphone hearing protection method and system, and the method comprises the following steps: collecting multi-modal data, and separating a sound source through tensor decomposition; inferring a pilot state by using a dynamic network; performing context recognition and semantic evaluation on the attention target voice; and finally, dynamically modulating the sound field based on deep reinforcement learning, enhancing the voice in a personalized manner, and outputting after noise suppression. The system comprises a multi-mode perception data acquisition module, a sound source decoupling module, a pilot state inference module, a voice processing and semantic evaluation module and a sound field modulation and output module. According to the invention, high-fidelity speech extraction is realized through multi-modal perception and tensor decomposition; evaluating priority key information in combination with attention and semantics; and deep reinforcement learning and model prediction control are adopted to dynamically optimize the sound field, so that the voice recognition accuracy and the pilot information acquisition efficiency are improved.

The invention provides a hearing screening system suitable for rural old people, and belongs to the technical field of data processing, and the system comprises a data collection module which collects voice and determines a comprehensive data set; the equipment calibration module is used for determining an audio output parameter of the hardware equipment based on the hardware equipment characteristics in combination with the hardware equipment characteristics, and calibrating the hardware equipment; the parameter determination module is used for determining voice interaction parameters; the hearing test module is used for generating an audiogram; the preliminary judgment module is used for analyzing the audiogram and determining a preliminary judgment result; and the result determination module is used for selecting vocabularies from a preset vocabulary database and a dialect voice database, playing high-frequency audios corresponding to the vocabularies on the calibrated hardware equipment, obtaining user feedback and determining an optimization judgment result in combination with the vocabularies and the dialect voice database. The method has the advantages of individuation, accuracy and high efficiency, is low in cost, is especially suitable for hearing screening requirements of rural old people, and improves the universality and accuracy of screening.

The invention discloses a Bluetooth hearing-aid earphone optimization method and system for adaptive hearing compensation. The method comprises the following steps: S1, acquiring a personalized hearing curve of a user and background audio data of left and right ears in each typical scene, and respectively preprocessing the background audio data; s2, extracting time-frequency fusion features of each typical scene, generating scene feature vectors, and constructing a scene feature vector library; s3, calculating a scene perception conversion vector, an abrupt change risk vector and a smooth gain vector; s4, calculating a binaural gain change vector, a binaural synchronous entropy vector, a phase alignment factor vector and a left and right ear cooperative gain vector; and S5, according to the left and right ear cooperative gain vectors, processing the background audio data after left and right ear preprocessing in the current scene, and outputting the processed background audio data to the Bluetooth hearing-aid earphone. According to the invention, the problem of gain abrupt change generated during scene switching of the existing Bluetooth hearing-aid earphone and the problem of spatial perception distortion caused by binaural coordination imbalance can be solved.

The invention relates to a hearing-aid debugging method and system, and the method comprises the steps: obtaining a reference parameter of a hearing-aid, applying the reference parameter to the hearing-aid, enabling the hearing-aid to have an initial reference value before the parameter adjustment, guaranteeing that the result is not deviated in the subsequent debugging process, and improving the debugging efficiency. The change conditions of the emotion balance index and the psychological pressure index when the debugger wears the hearing aid to carry out the hearing test are taken as the basis for adjusting the parameters of the hearing aid, so that feedback can be quickly obtained without language communication with the debugger, and the emotion level and the psychological pressure level when the debugger wears the hearing aid can be known in real time; and parameters of the hearing aid can be adjusted in time according to the information, so that the hearing feeling of a debugger is improved. In the hearing aid parameter adjustment process, the hearing aid parameters are subjected to coarse adjustment and fine adjustment in sequence through two different stride adjustment modes, the most comfortable hearing area of a debugged person can be approached at the fastest speed, and the accuracy of the finally obtained hearing aid parameters is improved.

The invention discloses a conduction device fitting management system and a conduction device, and belongs to the technical field of data analysis, and the method specifically comprises the steps: collecting multi-source fitting data, carrying out the real-time fusion, and constructing a scene-physiology-loss three-dimensional self-adaptive model through the combination of a regional fitting strategy defined based on a geographic position or an environment type; according to the real-time fusion data and model data, dynamically allocating three types of data priorities and generating initial compensation parameters, inputting the initial compensation parameters into a third-order LSTM acoustic compensation engine containing an attention mechanism, and outputting acoustic compensation signals in combination with hearing audio signals collected by a real-time hearing test strategy; converting the acoustic compensation signal into a hearing aid DSP executable instruction, driving the hearing aid to compensate and output a gain curve, and collecting user feedback at the same time; the system can adaptively adjust the compensation parameters according to the real-time state of the user and the environment change, and improves the compensation effect of the hearing aid.

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 an earphone sound effect personalized balanced automatic tuning method and system, and particularly relates to the technical field of earphone tuning, and the method comprises the steps: collecting the hearing feature data of a user in an initialization stage, constructing an individual compensation baseline, and carrying out the self-tuning of the earphone sound effect; solidifying a safety boundary containing the maximum allowable gain, the maximum output, the compression parameter upper limit and the parameter change rate upper limit as a hard constraint; in daily use, multi-source data is collected by taking a wearing session as granularity, the comprehensive quantity of comfort evidence is calculated, and a comfort label sequence is generated; based on the scene feature sequence, the comfort level label and the current parameter, constructing an individualized discomfort risk model, performing multi-objective decision making by combining the definition income, the comfort level risk cost and the security boundary hard constraint, and outputting an updated parameter set; smooth taking-into-effect and safe output of parameters are achieved through gradual issuing and protection state control, and evolution updating and version backspacing are carried out based on long-term logs.

The present disclosure relates to a hearing device comprising a first radar sensor configured for obtaining first radar data indicative of a shape of a first pinna of the first ear of a user. A processing unit of the hearing device is configured to receive the first radar data from the first radar sensor, and determine, based on the first radar data, a shape of the first pinna.

The invention relates to a hearing threshold prediction method based on frequency sweep OAEs and a deep learning model, and the method comprises the steps: employing a frequency sweep stimulation signal normal form with a unified mode to extract an SFOAEs signal and a DPOAEs signal, the stimulation sound normal form of the SFOAEs signal is a four-segment frequency sweep signal, and the stimulation sound normal form of the DPOAEs signal is a single-segment frequency sweep signal. And carrying out interference signal filtering on a residual signal of the single DPOAEs signal or the SFOAEs signal through a tracking filter with a dynamically changed zero pole so as to extract frequency sweep OAEs spectrum information. And constructing a data set of a deep learning model based on the sweep frequency OAEs spectrum information, and training and evaluating the deep learning model to obtain a hearing threshold prediction model. And calling the hearing threshold prediction model to perform hearing threshold prediction on the SFOAEs signals and the DPOAEs signals under different test intensities, and outputting hearing thresholds corresponding to the frequencies, thereby ensuring the accuracy of diagnosing the hearing loss degree.

A hearing system having a hearing device, including a receiver antenna assembly with a receiver core having a relatively high magnetic permeability and a receiver coil wound around the receiver core, operably connected to a rechargeable power source, and a hearing device charger, including a transmitter antenna assembly, with a transmitter core having a relatively high magnetic permeability and a transmitter coil wound around the transmitter core, operably connected to a power supply. The respective configurations of the hearing device and the hearing device charger may be such that when the hearing device is in a charging position on the hearing device charger, the receiver core and the transmitter core together provides a closed loop path for magnetic flux.

1. Name of the Design Product: External Receiver Behind-the-Ear Hearing Aid. 2. Use of the Design Product: After professional fitting, it is used to compensate for the hearing of patients with conductive hearing loss. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photo that Best Illustrates the Design Key Points: Stereogram.

The invention relates to the technical field of medical data processing, in particular to a data analysis and processing system based on clinical hearing detection, and aims to solve the problems that dynamic characteristics of auditory nerve response cannot be systematically described, high-dimensional multi-modal feature vectors cannot be constructed, and the data analysis and processing efficiency is low in the prior art. A stable and reliable input basis cannot be provided for intelligent classification, anomaly detection and individualized analysis, and the sensitivity and specificity of hearing state recognition are reduced; the multi-dimensional hearing feature extraction module fuses time domain, frequency domain and non-linear complexity analysis methods, systematically depicts dynamic features of auditory nerve response, constructs a high-dimensional multi-modal feature vector by integrating three-dimensional features, remarkably improves sensitivity and specificity of hearing state recognition, and improves the accuracy of hearing state recognition. The feature representation method provides a stable and reliable input basis for subsequent intelligent classification, anomaly detection and individualized analysis.