9799 results about "Microphone" patented technology

An online social wager-based gaming system is disclosed, featuring dynamic cross-provider game filtering and persistent cross-provider voice-interactive group play. The system allows for automated multi-seat group game reservations and incorporates a distributed ledger for bet verification. Features include a Group Connect module for dynamic group formation and live audio across various game providers, enabling real-time play. A Professional Companion Connect module facilitates live webcam or microphone gambling sessions with professional companions, under contractual agreements. The User Games module enhances personalization by integrating user-uploaded images into the gaming environment. A cryptocurrency / blockchain-based bet tracking system ensures transparency and security in managing bet transactions through a controlled digital wallet system. This integrated platform aims to provide a cohesive, interactive, and personalized online casino experience, addressing limitations of traditional solitary online gaming by fostering social connections and enhancing user trust and engagement.

The invention discloses a smart park safety protection system and method based on smart video analysis and multi-mode integration, and relates to the technical field of smart park management. The system comprises a camera, an environment microphone and an access control terminal which are deployed in a park, an edge computing node is used for extracting structured video, audio and access control features, a central server realizes multi-modal space-time alignment through a self-calibration module, a multi-modal fusion module constructs a joint representation vector based on a low-rank tensor algorithm, and the joint representation vector is used for realizing multi-modal space-time alignment. And the security decision module identifies an abnormal event and triggers a response strategy in combination with a classification and anomaly detection model. According to the invention, multi-mode cooperative identification, high-robustness behavior analysis and intelligent response linkage are realized, and the real-time performance, accuracy and intelligent level of a park security system are improved.

A headphone includes a housing including a bottom wall portion and a side wall portion connected with the bottom wall portion which cooperate to form an accommodation space, a sealing ring, a microphone assembly including a sound guiding member configured to hold the sealing ring against a microphone and a support surface provided on a side of the side wall portion facing the accommodation space, and a positioning member inserted between the housing and the sound guiding member to enable the sound guiding member to remain the sealing ring in a press-hold condition. The sealing ring encircling the sound guiding hole provided on the support surface for connecting the accommodation space and an exterior of the housing is provided on a support surface. A sound guiding channel is provided on the sound guiding member for guiding a sound input from the sound guiding hole to the microphone.

The invention discloses a multi-modal data fusion method and system based on a large-model intelligent agent, belongs to the technical field of artificial intelligence, big data processing and intelligent agents, and aims to solve the technical problem of how to effectively integrate data of different modalities such as texts, images and voices by using the large-model intelligent agent. According to the technical scheme, the method comprises the steps that data collection and preprocessing are conducted, specifically, various modal data of texts, images and voice are collected through a web crawler, an API interface, a camera and microphone equipment, the collected data are preprocessed, the preprocessed multi-modal data are obtained, and the data quality is ensured; feature extraction and mapping: extracting corresponding modal features from the preprocessed multi-modal data through CNN and Transform models, mapping the different modal features to the same space, and combining the aligned features to form comprehensive feature representation; carrying out multi-modal fusion processing; and performing intelligent decision and feedback.

Automatic recognition of non-verbal messages in speech, and in particular to detection or analysis of prosodic multilayered analysis of intonation units such as prosodic unit prototypes and their multi-labeled variations, may form a hierarchical classification for the analysis of non¬ verbal information or cues in speech. A speech captured by a microphone is fed to a weakly- supervised deep learning acoustic model for speech recognition and transcription, that may be based on encoder-decoder Transformer architecture, such as Whisper by OpenAI. The model is trained to output multiple words form the text in the captured speech, to identify Intonation Units (IUs) that include one or more words, and associate non-verbal labels to each of the IUs. The labels may indicate a prototype, a discourse function (such as a conversation action), an emotion, an emphasis, or an attitude, as well as a genre of a part of, or whole of, the entire captured speech.

An intelligent (self-learning) sensor-aware and / or context-aware subsystem comprising (i) a System-on-a-Chip (SoC), (ii) a radio transceiver, (iii) a microphone, (iv) a voice processing module, (v) a (bio-inspired) neuromorphic event camera or a hyperspectral camera, (vi) a first set of computer implemental instructions in artificial neural networks (ANN) (which may include a transformer model / diffusion model or Poisson flow generative model++ (PFGM++)), (vii) a second set of computer implementable instructions to analyze and interpret contextual data and (viii) an autonomous artificial intelligence (AI) agent is disclosed.

The invention discloses a speech recognition and authentication method and system based on multi-modal features and dynamic evaluation in the technical field of speech recognition and authentication, and the method comprises the steps: collecting an original speech signal of a user through a microphone, and carrying out the preprocessing of the original speech signal, and obtaining the preprocessing speech data; and extracting feature data of the preprocessed voice data by adopting a multi-dimensional feature hierarchical extraction technology, and injecting a multi-source noise sample into an acoustic feature space of a voiceprint feature model based on an initial training stage established by the voiceprint feature model to construct an anti-noise mixed voiceprint map. Through integrating voiceprint, semantics, behavior characteristics and an environment adaptation mechanism, an authentication threshold is adjusted in real time according to dynamic risk assessment, meanwhile, a risk scoring model is utilized to calculate a comprehensive risk value, authentication modes of different levels are started according to risk scenes of different degrees, and two-factor authentication is forcibly implemented for high-risk scenes. And the authentication security and reliability can be obviously enhanced.

A user electronic device comprising: one or more microphones configured to capture raw audio data; and one or more processors and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving the raw audio data captured by the one or more microphones; processing the raw audio data using a speech transcriber to generate a live transcription of the raw audio data that comprises a plurality of text tokens; processing the raw audio data to generate a speaker identification output that identifies, for each of the text tokens, a respective speaker for each of the text tokens in the live transcription; and processing a first input comprising (i) a first input prompt and (ii) an input text generated from the live transcription using a language model neural network to generate a modified transcription.

The invention discloses a multi-modal self-adaptive child voice interaction method for an educational service robot, relates to the technical field of voice signal processing, and provides a multi-modal self-adaptive child voice interaction method for an educational service robot through multi-array microphone dynamic acquisition and beam forming, self-adaptive noise suppression, multi-speaker separation and speaker identification, and child exclusive model training and online fine tuning. Technical means such as context semantic correction and multi-modal fusion are adopted, so that the target voice focusing and recognition accuracy is greatly improved; multi-person voice tracks are distinguished through an end-to-end network, and rapid distinguishing of a multi-source voice scene is realized in combination with model optimization of child range features; meanwhile, correct vocabularies and pronunciation information are traced back to a speaker library and a child sound model by using real-time semantic correction and interactive feedback, and multi-mode cooperation of a camera and a positioning sensor is used for assisting, so that beams are quickly adjusted and interference is suppressed when a child moves at will and environmental noise suddenly increases, and the sound quality of the child is improved. And natural and smooth voice interaction experience is provided in class and family scenes.

The invention discloses an SF6 gas leakage detection method and system based on a photoacoustic spectrum analyzer, and the method comprises the steps: arranging a sampling end to collect an SF6 gas sample, and obtaining stable gas input through constant-current sampling and steady-state pretreatment; steady-state gas is guided into the photoacoustic spectrum analyzer, and resonance frequency stabilization and signal amplification output are achieved through the self-tuning unit; executing double-microphone differential detection and digital filtering processing, and outputting a stable SF6 detection signal with a high signal-to-noise ratio; performing time calibration, abnormity elimination and consistency processing on the detection signal to generate standardized detection data; inputting the standardized data to a Transform model, and performing inversion to generate an SF6 leakage source position and a diffusion path; and displaying an inversion result on a monitoring interface, triggering a sound-light alarm when the inversion result exceeds a limit, and uploading the inversion result to a cloud monitoring platform. According to the invention, the intelligent photoacoustic spectrum system combining photoacoustic-fluid steady-state control and self-tuning detection is constructed, so that high-sensitivity detection and accurate positioning of SF6 gas leakage are realized.

The invention relates to an audio feature extraction method and device based on a neural network. The method comprises the following steps: performing framing processing and fast Fourier transform on an original audio signal acquired by a vehicle-mounted microphone to obtain a frequency domain feature sequence; extracting short-time energy, a zero-crossing rate, a frequency spectrum centroid and a Mel-frequency cepstrum coefficient from the frequency domain feature sequence, and combining first-order difference and second-order difference features of each feature to obtain a multi-dimensional acoustic feature point sequence; performing time sequence arrangement on the multi-dimensional acoustic feature point sequence, constructing an original feature matrix, and performing principal component analysis on the original feature matrix to obtain a feature description matrix; inputting the feature description matrix into a dynamic time feature extraction network for deep time-frequency feature analysis to obtain vehicle-mounted voice deep time-frequency features; and performing voice detection classification based on the vehicle-mounted voice deep time-frequency features, and outputting a vehicle-mounted voice detection result. According to the invention, various noise interferences in a vehicle-mounted environment are effectively suppressed, and the anti-noise capability of the system is enhanced.

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

A logarithmic amplifier includes programmable gain amplifiers each having a different gain, wherein an input of each of the programmable gain amplifiers is coupled to an input of the logarithmic amplifier; and a summing circuit having inputs coupled to a corresponding output of each of the programmable gain amplifiers and an output coupled to an output of the logarithmic amplifier, wherein the summing circuit generates a logarithmic transfer function having piecewise linear segments.

Various embodiments of an ear-wearable electronic device are disclosed. The device includes a housing having a top shell and a bottom shell, a microphone disposed within the housing, and an acoustic path disposed at least partially within the housing and extending between an acoustic port disposed at an outer surface of the housing and an outlet disposed within the housing that acoustically couples the acoustic path to an inlet of the microphone. The device further includes an acoustic filter disposed at least partially within an inner surface of the top shell and includes a neck and a resonance cavity acoustically coupled to the neck. The acoustic filter is acoustically coupled to the acoustic path via the neck. Further, the acoustic filter is configured to reduce an intensity of acoustic waves sensed by the microphone in a first frequency range.

An artificial intelligence (AI) entry management (EM) security system includes a camera, a microphone, a motion detector, a speaker, and a software platform. Geofences are utilized to create boundaries around physical areas, such as locations for package delivery or property boundaries. The EM device and other devices connected to the software platform are configured to monitor the geofences and detect a presence of an activity, an event, an object, or a device. At least one license plate reader is utilized to read license plate characters. Voice recognition and voice identification are used to grant or deny permissions for individuals on a property.

Provided is a sound reproduction device which reduces air noise. The sound reproduction device includes a casing in which an opening section communicating with an inside and an outside is formed, and a microphone that is disposed in an internal space communicating with the opening section, in which a value obtained by dividing a volume of the internal space from the opening section to the microphone by an area of the opening section is 2.9 or more.

Disclosed are systems and methods for adaptive noise cancellation (ANC) at a virtual microphone located at the eardrum of a wearer of an earphone. The techniques estimate the level of leakiness of ambient noise in the earphone from the magnitude of the gain of the transfer function of the feed forward loop filter of the ANC. Based on the estimated leakiness, the techniques estimate the transfer function of the feed forward loop filter to compensate for the difference in the effect of noise cancellation at the virtual microphone and error microphone. A bias term that represents the difference in the frequency response of the attenuated noise at the virtual and error microphone may be added to the adaptive feed forward algorithm. The ANC operation may apply the bias term to the adaptive feed forward loop filter to reduce the ambient noise at the eardrum rather than at the error microphone.

A communications system for a restaurant includes multiple field communications units, a portable communications device, and processing circuitry. The field communications units include a speaker and a microphone. The portable communications device is transportable by an order taker of the restaurant. The processing circuitry obtains a user input to transition the portable communications device between multiple different channels. The multiple different channels correspond to one of the multiple field communications units. The processing circuitry transitions the portable communications device to one of the multiple different channels according to the user input. The processing circuitry facilitates end-to-end bi-directional audio communication between the order taker and a customer by operating the portable communications device and the one of the multiple field communications units to exchange audio data over the one of the multiple different channels.

A method of operating a microelectromechanical system (MEMS) includes, in a first operational mode, converting an analog output of the MEMS into a first internal data stream and a first external data stream having a first sampling rate; transitioning from the first operational mode to a second operation mode without restarting the MEMS; and in the second operational mode, converting the analog output of the MEMS into a second internal data stream having a second sampling rate different from the first sampling rate, and performing a sampling rate conversion of the second internal data stream to generate a second external data stream.

The invention relates to the technical field of safety and environmental protection, in particular to a negative-pressure circulating explosion-control dust removal method suitable for combustible dust places, which comprises the following steps: firstly, sealing a bin body and injecting carbon dioxide-nitrogen inert gas to generate a low-oxygen environment; then, a flow guide angle-adjustable cyclone separator, a dielectric barrier discharge plasma reactor and a waste heat thermo-acoustic transducer are driven to cooperatively capture dust, and sound node amplitude synthesis capture data are obtained through compressed sensing of a microphone; inputting the environment data and the capture data into a reinforcement learning process containing a micro-thermochemistry model, and outputting instructions for adjusting negative pressure pulse, inert flow, sound field intensity and cyclone geometry; in combination with distributed radio frequency imaging data, an adversarial digital twinborn model is generated to predict explosion free energy, and automatic rollback or shutdown is carried out when the explosion free energy exceeds a threshold, so that a safe, efficient and low-energy-consumption closed loop is formed.

The invention discloses an intelligent diagnosis and maintenance system for power equipment, and relates to the technical field of power equipment detection, and the system comprises the following components: an array microphone module which is composed of a plurality of microphones, is used for accurately calculating the spacing, is arranged in a three-dimensional or plane matrix manner, and is used for collecting sound signals generated in the operation process of the power equipment; according to the invention, the array microphone module is combined with a beam forming technology, the sound signals are collected efficiently, a voiceprint topological map is constructed, sound source distribution and energy conduction paths of all parts of the equipment are represented in a visual form, and the sound source distribution and energy conduction paths of all the parts of the equipment are displayed in a visual manner. Meanwhile, voiceprint features and vibration modal features are extracted through a feature extraction module, and a joint inversion module is used for performing joint analysis on the two features based on a mapping relation model and a machine learning algorithm and in combination with a modal database, so that the damage degree of the mechanical part of the power equipment is accurately inverted.

The invention relates to the technical field of multi-modal sensors, in particular to a multi-modal sensor embedded self-calibration system and a real-time compensation method, and the method comprises the following steps: S1, data acquisition: a multi-modal data acquisition mode is adopted, a multi-modal data acquisition module is responsible for acquiring original data of a camera, an inertial measurement unit and a microphone, and the original data of the camera, the inertial measurement unit and the microphone are acquired; the camera collects image data at the frequency of 30 Hz. The method has the advantages of comprehensive data acquisition, accurate data processing, comprehensive and deep feature extraction, scientific and flexible calibration parameters and efficient and continuous real-time compensation, and a multi-modal data fusion technology is adopted in the actual use process; a composite sensing system covering space positioning, dynamic sensing and acoustic analysis is constructed, and the multi-source heterogeneous data fusion scheme can comprehensively capture multi-dimensional features in a complex scene.

Techniques for utilizing invisible and / or inaudible watermarking techniques in media streams (e.g., video and / or audio streams) as a form of in-band steganography to authenticate the source capture camera and / or microphone to prevent deepfakes in network-based communication systems. User device(s) may establish cloud-based connections to a network-based communication system hosting media stream(s). An encoder of a watermarking component of a user device may receive video / audio data directly from a camera / microphone thereof and encode the video / audio data with watermark(s) representing a signed signature. A decoder of a watermarking component of a recipient user device and / or another device associated with the communication system may extract the watermarks and authenticate the signed signature using public certificate(s) associated with the sending user device to validate authenticity of the capture source(s) of the sending user device and that the video / audio data has not been modified since the time of capture.

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

The invention relates to a human body posture capture-based disabled assisting robot planning method and system, and the method comprises the following steps: S1, a patient is fixed to a system main body through a flexible fixing device, so that the posture capture precision is ensured, and accidental sliding is prevented; s2, a high-definition RGB camera and a depth sensor are used, real-time posture joint point data of the patient are obtained based on a human body posture estimation algorithm, and the real-time posture joint point data comprise the head position, the limb position and the trunk position; s3, resolving the captured data in real time, and referring to a posture database to generate a most suitable initial rehabilitation posture; s4, collecting visual, voice and physiological signals by using a camera, a microphone and other sensors, and performing feature extraction and fusion by using a convolutional neural network to improve the recognition accuracy; s5, judging the satisfaction degree of the patient to the current posture through an emotion recognition technology in combination with voice emotion analysis, and adjusting the system according to the satisfaction degree of the patient; the motion parameters of rehabilitation training of the patient are obtained quickly, the effectiveness and rehabilitation efficiency of rehabilitation training are improved, and the participation degree and enthusiasm of the patient are increased.

The present invention provides a vehicle comprising a sound control device. A sound control device, according to one embodiment of the present invention, comprises: a sound object extraction module that extracts at least one audio object from an audio signal received from at least one of an outdoor microphone provided outside a vehicle and an indoor microphone provided inside the vehicle; and a sound object renderer that performs rendering with an audio function by using the audio object signal extracted by the sound object extraction module.

The invention relates to the technical field of game development and artificial intelligence, and discloses a Qt interactive game role action response control method fused with AI emotion recognition, which comprises the following steps: S1, acquiring multi-modal data such as facial expression, voice intonation and limb action of a player by using sensors such as a camera and a microphone on game equipment; s2, the collected multi-modal data are transmitted to an AI emotion recognition module, a deep learning algorithm is adopted to analyze and process the data, and the current emotion state of the player is recognized; and S3, obtaining current game scene information and other operation instructions input by the player through the Qt framework. According to the Qt interactive game role action response control method and system fused with AI emotion recognition, through the AI emotion recognition technology, a game role can sense the emotion state of a player and make the emotion interaction action matched with the game role, the emotion resonance between the game role and the player is enhanced, and the interaction experience and immersion of a game are greatly improved.

A system for presenting audio content to a user. The system comprises one or more microphones coupled to a frame of a headset. The one or more microphones capture sound from a local area. The system further comprises an audio controller integrated into the headset and communicatively coupled to an in-ear device worn by a user. The audio controller identifies one or more sound sources in the local area based on the captured sound. The audio controller further determines a target sound source of the one or more sound sources and determines one or more filters to apply to a sound signal associated with the target sound source in the captured sound. The audio controller further generates an augmented sound signal by applying the one or more filters to the sound signal and provides the augmented sound signal to the in-ear device for presentation to a user.