21 results about "Normal voice" patented technology

The invention discloses a method and system for monitoring the abnormal state of a belt conveyor based on deep learning, and the method comprises the steps: laying sensing optical fibers along the line of a rack of the belt conveyor, and collecting the operation sound signals of a plurality of spatial point locations along the line through the sensing optical fibers by a distributed acoustic sensing DAS device; the method comprises the following steps: in a normal operation state of a belt conveyor, collecting normal sound signals of each point location, preprocessing the signals, and constructing a normal sample data set; for a normal sample of each spatial point location, training a corresponding unsupervised learning model; in real-time monitoring, sound signals collected at each point location are input into a corresponding unsupervised learning model, a reconstruction error is calculated, and the reconstruction error is compared with a dynamic threshold value based on normal sample statistical characteristics to obtain an abnormal result; and performing comprehensive judgment on an abnormal result based on statistical logic of the time window, and triggering an alarm if an abnormal proportion in the window exceeds a set value. High-accuracy abnormity early warning is realized, and system deployment is convenient.

A machine learning model is constructed by machine learning based on image data that is obtained by imaging each portion provided in a substrate processing device and sound data of sounds emitted when the portions operate. As the sound data, both the data of a normal sound that is emitted when each portion operates normally and the data of an abnormal sound that is emitted when each portion is abnormally operated are collected. When abnormality detection is performed, an eye tracking function identifies a position that is being viewed by a worker wearing smart glasses in which a machine learning model is installed. An image of a region including the identified viewed position is captured, and a sound is collected in a state in which the worker is viewing the viewed position. The collected image data and sound data are input into the machine learning model.

The invention relates to the technical field of abnormal sound detection, in particular to a scraper abnormal sound recognition method and device and electronic equipment. The scrapper abnormal sound recognition method comprises the following steps: based on historical sound data of all working surfaces of a plurality of coal mines and an HTS-AT model, acquiring a universal audio recognition model divided according to a mining dimension; obtaining a target normal sound sample, a target fault sound sample and a target environment interference sound sample which are matched with the target working surface; based on the sampling height of the target working face, the target normal sound sample, the target fault sound sample and the target environment interference sound sample, performing fine tuning on the universal audio recognition model to obtain a target audio recognition model matched with the target working face; and based on the target audio recognition model, recognizing the to-be-detected sound of the target working surface, and obtaining an abnormal sound recognition result of the scraper. The abnormal sound of the scraper conveyor can be accurately recognized, real-time and accurate support is provided for equipment troubleshooting, and the coal mine production efficiency is improved.

This invention provides a voice interaction control method for smart home appliances, a smart home appliance, and a computer-readable storage medium. The voice interaction control method includes: turning on the smart home appliance; identifying the real-time status of a target user in the environment of the smart home appliance at preset intervals; when the real-time status of the target user is identified as active for a preset number of consecutive times, controlling the smart home appliance to execute a normal voice interaction strategy; when the real-time status of the target user is identified as sleep or rest, controlling the smart home appliance to execute a downgraded voice interaction strategy. This allows for dynamic and accurate perception of the user's real-time status to dynamically adapt to different strategies of the smart home appliance's voice interaction function, precisely preventing the smart home appliance's voice interaction function from interfering with the user's sleep or rest, and accurately realizing intelligent interaction of the voice interaction function during non-sleep or rest periods. This improves the accuracy and stability of the smart home appliance's voice interaction control, thereby enhancing the user experience.

Regardless of the type of elevator, it can be easily retrofitted, detect operational abnormalities, and enable direct communication between the elevator occupants and the outside. [Solution] The elevator management device 200 is retrofitted to the outside of the elevator car and includes a microphone 204 for collecting ambient sounds, a speaker 205 for outputting sound, and a communication unit 302 for communicating with an external device 300. When the microphone 204 collects a predetermined sound or a sound similar thereto, or when the microphone 204 collects a sound different from the sounds that normally occur, the communication unit 302 transmits information about the collected sound and information about an abnormality determined based on the collected sound to the external device 300, and the speaker 205 outputs sound related to the predetermined information either towards the outside of the car or towards the inside of the car.

The invention discloses a sound transmission method based on floor obstruction in a virtual scene and a related device. The method comprises the following steps: acquiring floor space states of a target sounding object and a target listening object in a floor space environment; the floor space state shows that the target sound production object or the target sound listening object is located in the floor space, and the target sound production object and the target sound listening object are located on different floors; the normal sound resource and the floor sound resource in the floor space are mixed as a first blocking sound with relatively high blocking strength and are transmitted from the target sound production object to the target sound listening object, and the normal sound resource is strongly blocked by the floor; the floor space state indicates that the target sound production object and the target sound listening object are both located outside the floor space, and the target sound production object and the target sound listening object are located at different floors, filtering a second barrier sound with a normal sound resource being relatively low barrier strength through the floor barrier parameter, and spreading the second barrier sound from the target sound production object to the target sound listening object. Normal sound resources are weakly blocked by floors.

The invention discloses a wake-up processing method and device based on far-field voice, and terminal equipment, and relates to the technical field of voice recognition wake-up, and the method comprises the steps: carrying out the analysis processing of a detected wake-up audio, and calculating a wake-up confidence score; when the calculated wake-up confidence score of the wake-up audio is greater than or equal to a preset threshold value, determining that the wake-up is effective and controlling to enter a normal voice interaction process; when the calculated wake-up confidence score of the wake-up audio is lower than a preset threshold value, sending the wake-up audio to a background for voice recognition; performing second-level judgment: judging whether the character information of the voice recognition is consistent with a preset wake-up word or not; if so, entering a normal voice interaction process; and if not, false wake-up is confirmed, and the voice interaction process is controlled to be ended. According to the invention, the false awakening condition caused by environmental noise, similar pronunciation and the like can be solved, and convenience is provided for the use of a user.

The invention relates to the technical field of voice information security, and discloses a recording interference prevention method and device, and the method comprises an environment perception step, an equipment recognition and positioning step, an interference strategy decision-making step, a dynamic sequence generation step, a signal fusion construction step, a parametric array modulation step, a directional emission step, and an evaluation adjustment step. The device corresponds to the method. According to the application, different recording devices are accurately distinguished through an acoustic fingerprint identification technology, and a targeted interference strategy can be generated according to specific acoustic features of the devices; by combining an acoustic parametric array and a beam forming technology, accurate directional transmission of interference sound waves is realized, interference energy is enabled to act on target equipment in a concentrated manner, and the interference efficiency is improved; through fusion of multiple dynamic sequences and construction of composite baseband signals, the unpredictability and anti-filtering capability of interference signals are enhanced. Therefore, the high-efficiency interference performance is maintained, the influence on normal voice communication is reduced, and accurate and self-adaptive anti-recording protection is realized.

This invention relates to the field of hearing aids, specifically to a method and system for testing the operational performance of hearing aids. The system includes a processing module, a receiver module, a timed switching module, and a comparison module. The processing module comprises a processor module, a button module, a power supply module, a playback module, and a transmission module. By setting a timed self-test, the system collects sound from the inside of the device normally used for auxiliary receiver switching during the self-test. Then, the auxiliary receiver module collects the sound played by the playback module and compares it briefly with normal sounds in a normal sound database. If the playback is confirmed to be problem-free, it proves that neither the playback module nor the receiver module has a performance degradation issue. If the short comparison confirms a playback problem, a long-term comparison is performed, comparing the sound data played by the playback module with the sound data collected by the receiver module to determine whether either the playback module or the receiver module has a problem, or which module is malfunctioning.

This application provides a method, device, vehicle, and medium for alerting abnormal vehicle noises. The method, applied in the field of vehicles, includes: acquiring sound information generated by the vehicle, vehicle operation information, and vehicle driving information; determining the vehicle's operating scenario based on the vehicle operation information and driving information; comparing the sound information with normal sound information stored in a first database based on the operating scenario to generate a detection result; and outputting corresponding alert information according to the detection result and a corresponding alert mode. This method can alert users to vehicle noises based on their needs, enabling users to promptly detect vehicle malfunctions and ensuring vehicle driving safety.

The objective of the invention is to provide the sound spectrum mode recognizer which is high in abnormal sound signal recognition accuracy and high in detection efficiency. The system comprises an audio acquisition module, a spectrogram module, a neural network module and a result output module. The audio acquisition module is used for converting sound into an audio signal; the spectrogram module is used for converting an audio signal acquired by the audio acquisition module into a spectrogram; the neural network module performs feature extraction on the spectrogram so as to extract features of normal sound and abnormal sound; the specific extraction process comprises the steps of sequentially performing classification labeling on the spectrogram, setting parameters to generate a training set, selecting a neural network model, setting hyper-parameters, inputting the training set into the neural network model to start training and storing the network model. And the result output module calls the network model stored in the neural network module to compare and judge the spectrogram to be detected converted by the spectrogram module, and outputs a judgment result. The method is applied to the technical field of acoustic testing.

The embodiment of the invention provides a vehicle-mounted voice protection method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring an in-vehicle voice signal in real time; analyzing the voice signal to obtain power spectrum distribution characteristics; according to the power spectrum distribution characteristics, multiple paths of periodic short pulse sequences are constructed; generating a multi-channel ultrasonic masking signal according to the multi-path periodic short pulse sequence; and transmitting the multi-channel ultrasonic masking signal by using an ultrasonic phased array, and forming an ultrasonic sound field in a target area in the vehicle. In this way, the directional interference characteristic of the ultrasonic phased array can be utilized, accurate noise injection of illegal recording equipment is achieved, and therefore vehicle-mounted voice privacy is effectively protected under the condition that normal voice communication is not affected.

A noise reduction earphone based on a convolutional neural network belongs to the technical field of noise reduction earphones and comprises a noise power generation and energy storage device, a microphone array, a preprocessing module, a convolutional neural network module, a noise reduction module and a loudspeaker which are connected in sequence. The microphone array, the preprocessing module, the convolutional neural network module, the noise reduction module and the loudspeaker are all connected with a storage battery of the noise power generation and energy storage device. The earphone provided by the invention can generate power by collecting noise without external power supply, and can automatically identify the noise, filter the noise and automatically play normal sound, thereby facilitating communication in a noise place and judging abnormal sound. The method is wide in application prospect, can be applied to places with high noise, such as pump rooms, factory buildings and workshops, and achieves the purposes of recognizing and filtering noise, carrying out voice communication and listening to abnormal sound.

The utility model provides voice interaction equipment. The voice interaction equipment comprises an outer shell, a first sound device and a second sound device, a containing cavity is formed in the outer shell, and the outer shell is provided with a sound transmission part used for allowing sound waves to enter and exit from the containing cavity. The first sound device and the second sound device are both arranged in the accommodating cavity, a sound wave propagation area is formed between the first sound device and the sound transmission part, and the second sound device is located in the sound wave propagation area; one of the first sound device and the second sound device is a sound production device, and the other one is a sound reception device. According to the utility model, the number of the sound transmission structures on the outer shell is effectively reduced while the normal voice interaction function of the equipment is ensured, so that the probability that the sound transmission structures are blocked is reduced, the waterproof performance of the equipment is improved, and the equipment is good in use stability and good in use experience.

The application discloses an intelligent cabin vehicle self-service voice interaction method and device, equipment and storage medium, the method receives user voice instruction and carries out voiceprint identification, determines the user identity identifier, acquires the historical behavior data corresponding to the user identity identifier;When the historical behavior data meets the preset self-service trigger condition, the default execution instruction is generated and enters the preset waiting period, and whether there is a breaking instruction is monitored in the preset waiting period;According to the breaking monitoring result and time state in the preset waiting period, the default execution instruction is determined or the normal voice interaction process is turned in;The number of multi-round voice interactions in the driving scene can be significantly reduced to reduce the distraction risk, and the preset waiting period and the breaking instruction monitoring mechanism are combined to provide the opportunity for instant intervention for the user, so that the safety hidden danger caused by the misoperation is effectively avoided while the voice interaction efficiency and convenience are improved, and the balance between automatic execution and user control right is realized.

This invention provides a noise reduction and sound pickup device and method. The noise reduction and sound pickup device includes at least one noise pickup, a target sound pickup device, and a sound signal processing unit. The at least one noise pickup is positioned close to a corresponding noise source, suitable for acquiring ambient noise emitted by the noise source and generating an ambient noise frequency signal. The target sound pickup device is positioned close to a target sound source, suitable for acquiring the target sound from the target sound source and generating a target sound frequency signal. The sound signal processing unit inverts and amplifies at least a portion of the frequency signal in the ambient noise frequency signal, superimposes the inverted and amplified ambient noise signal with the target sound signal to obtain a useful sound, and outputs the useful sound. The noise reduction and sound pickup device and method can acquire and eliminate various complex noises emitted by large equipment, while simultaneously preserving and amplifying the required sound signal to ensure normal voice communication and improve communication quality.

This application relates to a method for automatically switching between mesh calls and 5G data network calls. Specifically a Bluetooth device constructs a mesh network to form a mesh group One of the nodes is used as the master node, and an online loop is created on the AP P. All Bluetooth devices communicate with the application in a two-way dynamic heartbeat data mode, and the cloud synchronizes information in the virtual network formed by mapping the nodes; The voice data between online nodes is communicated in mesh mode; when the nodes of Bluetooth devices are offline or reconnected, the node device automatically switches to the data network mode through the application and performs network communication using the data network mode via the cloud. This automatic switching method between mesh calls and 5G data network calls monitors the online status of the device in real time and automatically switches the voice data transmission to the cloud network when the device / node goes offline, thereby ensuring the normal voice data transmission and reception of non - communicating nodes and ensuring the real - time nature, continuity and completeness of voice data transmission. ​

An automatic inspection system includes a wireless slave device and a wireless master device. The wireless slave device includes a sound collection unit that collects sound generated from an inspection target object, an analysis unit that analyzes the collected sound to obtain a degree of difference between the collected sound and normal sound learned in advance and sound state information of the collected sound, as an analysis result, a wireless communication unit that wirelessly transmits data including the analysis results to a wireless master device, and a power supply unit that supplies power to the sound collection unit, the analysis unit, and the wireless communication unit. The wireless master device is configured to perform processing of receiving and managing the data from the wireless slave device, and transmitting the analysis result extracted from the data to a monitoring terminal that monitors a state of the inspection target object.

The invention relates to the field of hearing aids, in particular to an attenuation transient detection method of a hearing aid, comprising a body module, a control module, a mounting module and a detection module, the body module comprises a hearing aid main body and an external ear pendant, the hearing aid body comprises a shell, a key, a broadcaster, a sound receiver, a battery, a charging interface and a processor, the battery, the charging interface and the processor are installed in the hearing aid body, and the external ear hanging piece is hung on an external ear and used for installing and supporting the hearing aid body. Therefore, the whole hearing aid is reinforced and prevented from being collided and falling off in a noisy environment, meanwhile, the storage module is leaked, the telescopic module pushes the sound receiving module to enter the outer side of the broadcaster at the moment, the played sound is collected and compared with the normal sound standard, and the sound quality is improved. And the played sound is adjusted in real time according to a comparison result, so that normal use of a hearing aid user is facilitated.

The invention discloses a cross-domain abnormal sound detection method and system based on pre-training audio feature extraction, and the method comprises the steps: extracting corresponding acoustic feature vectors for normal sound samples based on a pre-training audio feature extraction model, and storing the acoustic feature vectors in a source domain feature memory library and a target domain feature memory library; for each target domain acoustic feature vector in the target domain feature memory bank, constructing a preset number of enhanced target domain acoustic feature vectors, and adding the enhanced target domain acoustic feature vectors into the target domain feature memory bank; calculating the distance between the acoustic feature vector of the sound signal to be detected and the feature memory library, performing normalization processing on the distance value between the acoustic feature vector of the sound signal to be detected and the feature memory library based on the statistical characteristics of the corresponding feature memory library, and taking the minimum value of the normalization result as the abnormal score of the sound signal to be detected. According to the method, the influence of domain offset caused by factors such as operation condition change and environmental noise difference on an anomaly detection result is effectively reduced.

The application relates to the field of hearing aids, in particular to a noise recognition method and system of a hearing aid, which comprises a processing module, a collecting module, a comparison module and an adjusting module, the processing module comprises a processor module, a button module, a power module and a transmission module, the processor module is used for collecting and processing data in the system and controlling the operation of the hearing aid, the button module is used for manual button pressing, a user can select whether to perform noise recognition processing according to the user's own needs, and the upper limit of high pitch and the upper limit of sound that can be played by the hearing aid are adjusted, so that the played sound is prevented from being too high, the received sound is distinguished, the sound higher than the upper limit of high pitch is played after being degraded and noise removed, the user is prevented from missing nearby sound information, and the sound lower than the upper limit of high pitch is compared and recognized with normal sound data in the environment, so that subsequent targeted processing and playing are facilitated.