1321 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.

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.

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.

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 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 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.

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.

The invention discloses a fully-implanted artificial cochlea system and a noise reduction method thereof.The fully-implanted artificial cochlea system comprises an implant and a fully-implanted microphone, the fully-implanted microphone comprises a shell, a PCBA board, a first sound sensor and a bone conduction sensor are arranged in the shell, the first sound sensor is connected with the PCBA board and used for receiving a first external sound signal and transmitting the first external sound signal to the PCBA board, and the bone conduction sensor is connected with the implant. The bone conduction sensor is also connected with the PCBA board and is used for collecting an in-vivo noise signal and transmitting the in-vivo noise signal to the PCBA board; the PCBA board is used for receiving the first external sound signal and the in-vivo noise signal, and at least performing noise reduction on the first external sound signal and then outputting the first external sound signal; the implant or the fully-implanted microphone is connected with a second sound sensor, the second sound sensor is connected with the PCBA, the second sound sensor receives a second external sound signal and transmits the second external sound signal to the PCBA board, and the PCBA board receives the second external sound signal, at least carries out noise reduction on the second external sound signal and then outputs the second external sound signal; according to the system, the wearing comfort of a user is effectively improved, the efficient noise reduction performance is met, and the hearing requirement of a user patient can be met.

A system for hearing assistance includes an array of microphones, which are configured be mounted in proximity to a head of a user of the system and to output electrical signals in response to first acoustic waves that are incident on the microphones. A speaker is configured for mounting in proximity to an ear of the user and configured to output second acoustic waves in response to a drive signal applied to the speaker. Processing circuitry is configured to generate the drive signal by amplifying and filtering the electrical signals using a beamforming filter that emphasizes first sounds that impinge on the array of microphones within a selected angular range while suppressing second sounds that are spoken by the user.

1. The name of the design product: behind-the-ear hearing aid set (F-AID4). 2. The use of the design product: the design product is used for assisting hearing. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: the combined state refers to Figure 1. 5. Other components that need to be explained: component 1 is a behind-the-ear hearing aid earphone box, and component 2 is a behind-the-ear hearing aid earphone.

A system for evaluating an ear seal between an earphone of a hearing device and an ear canal includes a first transducer configured to play a sound in response to an electrical signal including a reference frequency component and a test frequency component below the reference frequency. A second transducer receives the sound in the ear canal. A controller is configured to calculate at least one electrical signal level difference between the reference frequency component and the test frequency component of the electrical signal, measure the sound levels of the reference frequency component and the test frequency component of the sound in the ear canal, calculate an acoustic signal level difference between the measured sound levels of the reference frequency component and the test frequency component, calculate a normalized acoustic difference value by subtracting the electrical signal level difference from the acoustic signal level difference, and determine a measurement result of the ear seal based on the normalized acoustic difference value.

1. Name of the product in this design: Hearing Aid (H6103). 2. Purpose of this design: For use in assisting hearing. 3. The key design features of this product are its shape and texture. 4. The image or photograph that best illustrates the design's key points: a 3D model.

1. Name of the product of this design: Hearing aid component (990). 2. Purpose of the product of this design: used for hearing assistance; component 1 is a hearing aid, and component 2 is a hearing aid box. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: open state reference picture. 5. Design 1 is a left-ear hearing aid, and the views are omitted: the left-ear hearing aid is mirror-symmetrical to the right-ear hearing aid, and the corresponding six-sided views of the right-ear hearing aid are omitted.

A captioning method for presenting captions to an assisted user (AU) during communication with a hearing user (HU) where the assisted user uses a captioned device and the hearing user uses a hearing user's device to facilitate the communication, the captioned device including a display screen and a speaker for presenting captions and broadcasting the hearing user's voice signals, respectively, the method comprising the steps of during an ongoing call between the AU and the HU, using an automated speech recognition (ASR) engine to generate initial ASR captions associated with the HU's voice signal, assessing at least one caption quality factor associated with prior initial ASR captions generated during the ongoing call, delaying broadcast of HU voice signal to the AU and based on the at least one caption quality factor, adjusting a duration of the HU voice signal broadcast delay.

An exemplary hearing device may be configured to be inserted at least partially within an ear canal of a user of the hearing device. The hearing device may include a first temperature sensor configured to detect ear canal temperature within the ear canal, a second temperature sensor configured to detect ambient temperature outside of the ear canal, and a processor. The processor may be configured to determine a work status of the user indicative of an activity level of the user and determine a core body temperature of the user based on the ear canal temperature detected by the first temperature sensor, the ambient temperature detected by the second temperature sensor, and the work status of the user.

1. The name of the product of this design: earphones. 2. Purpose of this design product: It has noise reduction and intelligent voice transmission functions and can be used as a hearing protector. For example, it can be used as an intelligent labor protection headset in a noisy production environment. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Design 1 Stereoscopic Figure 1. 5. Designate Design 1 as the base design.

The invention relates to a method for testing a participant's ability to accurately detect speech under background noise, comprising: (a) audibly presenting a series of 2-bit numbers, 3-bit numbers, 4-bit numbers and / or 5-bit numbers in a random or fixed order to a participant's first ear at a fixed or varying signal-to-noise ratio (SNR) in a quiet or noisy environment, (b) audibly presenting a series of 2-bit numbers, 3-bit numbers, 4-bit numbers and / or 5-bit numbers in a random or fixed order to the second ear of the participant at a fixed or random signal-to-noise ratio (SNR) in a quiet or noisy environment, where the numbers are presented in the native language of the participant or the fluent language of the participant, (c) recording the numbers or sequence of numbers correctly recognized by the participant, and (c) storing the recorded numbers or sequence of numbers at the second ear of the participant. And (d) calculating a score as a function of the percentage of the number or sequence of numbers correctly replicated by the subject, or as a function of the sound intensity difference between the speech and noise required to achieve the correct recognition of 50% sequence of numbers. The invention also relates to a device and a method for measuring the digital recognition capability related to hearing loss, and to a computer-implemented method for evaluating the speech recognition capability of a participant.

The invention discloses a hearing aid health analysis method based on a physiological signal monitoring function. The method comprises the following steps: collecting physiological signal data of a user in real time through a multi-mode biosensor array integrated on a hearing aid body; the hearing aid body comprises a digital signal processor and a wireless communication module; the physiological signal data at least comprises a brain wave signal, a skin electric response signal and a temporal artery pulse signal; performing motion artifact elimination processing on the physiological signal data through an adaptive filtering algorithm; performing feature extraction on the preprocessed physiological signal by using an embedded health analysis engine to generate a composite health feature vector containing a sympathetic nerve activity index, cognitive load measurement and a cardiovascular function index; and dynamically generating a health risk assessment report based on an association relationship between the composite health feature vector and a preset hearing scene, the bone conduction vibration unit and the audio synthesis module of the hearing aid body output graded health alarm signals.