1402 results about "Speech control" patented technology

Disclosed in the present invention are a multi-modal shared teleoperation system and method for a three-arm space robot. The system at least comprises a master-side teleoperation system, a communication module and a slave-side robot system, wherein the master-side teleoperation system at least comprises two force feedback hand controllers, a microphone array and upper computer software, and the slave-side robot system comprises two operating arms each equipped with a gripper at the end, an observation arm having a binocular camera mounted at the end, a vision unit, a force sensor and lower computer software. The method comprises: an operator controlling two operating arms of an extravehicular robot to execute a task, and controlling an observation arm to acquire a better local field of view. In the method, a multi-modal teleoperation method comprising pose control, voice control and force control is fused with autonomous control of a robot by means of a shared control algorithm, and thus, human-robot collaborative control over the position, orientation and contact force of a robotic arm can be realized on the basis of the requirements of the operator, and the robot autonomously executes other relatively simple tasks, thereby reducing the operation burden of operators, and improving the control efficiency.

A multimodal shared telerobotic system and method for a three-arm space robot, the system at least includes a local-site system, a communication module, and a remote-site system, where the local-site system includes two force-feedback haptic devices for left and right hands, a microphone array, and upper computer software; the remote-site system includes two robotic arms provided with end-effectors, an observation arm with a stereo camera installed at an end thereof, two force sensors, a vision unit and lower computer software; an operator can control the two robotic arms of the robot outside a cabin for performing operations, and control the observation arm to obtain a better local view; and a multimodal telerobotic control method of pose control, voice control, and force control is integrated with the robot's autonomous control through a shared control algorithm.

An interactive method based on a large model, a training method, and an intelligent agent, which relate to fields of artificial intelligence, speech recognition, speech interaction, deep learning, large models, and application scenarios of knowledge search, autonomous driving, intelligent customer service, intelligent speech control, smart e-commerce, AI healthcare. The interactive method includes: acquiring a request speech; performing a speech recognition on the request speech to obtain a speech recognition feature representing a request semantics; and processing the speech recognition feature using the large model to obtain a response text, where the response text includes response words arranged in sequence, a target response word among the response words is determined by processing the speech recognition feature and an associated response word feature using an attention fusion layer of the large model, and the associated response word feature is related to an associated response word arranged before the target response word.

The invention relates to the technical field of vehicle lamp systems, in particular to an intelligent vehicle lamp system based on DLP projection, a control method and a vehicle. The intelligent vehicle lamp system based on DLP projection comprises an optical system, an intelligent control system, an execution module and a power management system, the system collects environment data in real time through a sensor, a central processing unit fuses multi-source information and generates a control instruction through an AI algorithm, and the light source brightness, the irradiation angle and the road surface projection content are dynamically adjusted; meanwhile, voice interaction and remote control are supported, and the self-adaptive lighting and safety warning functions are achieved. Through the intelligent control and DLP projection technology, the vehicle lamp performance is improved, the lighting effect is optimized, and the night driving safety is enhanced; self-adaptive adjustment is realized, and the driving experience is improved; the energy consumption is reduced by more than 30%; the battery life is prolonged; v2X communication is supported, and intelligent early warning is realized; a voice control function is provided, and operation is more convenient and safer; a road surface projection function is added, navigation arrows and warning marks can be displayed, and visual driving assistance is provided.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing text-to-speech modeling. In some implementations, a computer device receives input text in a first language to convert to a desired speech in a second language. The computer device receives one or more criteria for modifying the desired speech and converts the input text to a desired text in the second language. The computer device generates audio representations of the desired text in the second language and predicts, for each of the audio representations of the desired text and using the one or more received criteria, a pitch value and a duration value. The computer device generates the desired output speech using the predicted pitch value and the predicted duration value for each of the audio representations and provides the desired speech for output.

Systems and methods for imaging, such as with an intravascular ultrasound (IVUS) imaging device are employed with components and accessories, such as for example, catheters, a catheter interface module, mounts, a workstation, a tablet, a display, and cart. The components may be controlled or interacted with via hands-free commands, voice control, gestures, and may be enhanced with artificial intelligence and / or machine learning. Real time measurements and border detection with enhanced imaging are provided.

The invention discloses a non-contact operating room intelligent voice control method supporting multi-role voiceprint recognition, and relates to the technical field of voice interaction control, and the method comprises the following steps: S100, collecting full-band noise signals of all high-frequency operation equipment in an operating room in different operation states, extracting harmonic frequency, amplitude and phase features, and carrying out the recognition of the full-band noise signals; and constructing a harmonic noise characteristic database, and establishing and dynamically updating an environmental noise baseline model. According to the invention, through the dynamic environment noise baseline model and personalized voiceprint recognition, frequency spectrum isolation and accurate voice separation of high-frequency operation equipment noise and doctor voiceprint are realized. In combination with space and frequency spectrum dual-domain decoupling and voice integrity detection, and through dual verification of voiceprint identity and non-contact action, it is ensured that an instruction sender is true and effective. And a closed-loop defense mechanism is formed through permission level comparison and context semantic verification, so that error identification and error control are effectively prevented, and the safety, accuracy and continuity of the operation process are guaranteed.

The invention relates to the technical field of bionic humanoid robots, in particular to a multi-expression driving bionic intelligent robot head which comprises an eyebrow movable layer, a cheekbone movable layer, an eye movable layer, an upper lip movable layer and a chin movable layer located below the upper lip movable layer, and the eyebrow movable layer, the cheekbone movable layer, the eye movable layer and the upper lip movable layer are spliced and assembled by hexagonal threaded copper columns through reserved hole positions. The robot head is composed of a shell, an aluminum alloy machining plate frame, a CNC metal part, a steering engine, a rail and a pull wire, and a camera module and a voice control module are arranged in the robot head. The shell can be customized according to different figure facial features, the shell is of a high-precision, compact and adjustable structure, 26 steering engines are integrated in a limited space to control opening and closing of the face including left and right eyeballs, upper and lower eyelids, canthus, eyebrows, cheeks, mouth corners and mouth and actions of lips, and the layered design and control mode of the head of the robot enable the robot to be more intelligent. And the mounting, the dismounting and the maintenance are more convenient.

The invention discloses a display equipment intelligent voice interaction method based on a large language model, and the method comprises the steps: constructing a set of display equipment intelligent voice interaction system suitable for a complex scene based on a large language model technical framework through integrating a multi-stage audio processing module, an intelligent voice recognition module, a semantic understanding and intention recognition module and a multi-mode interaction control module; the voice enhancement technology is adopted, high-precision voice instruction capture and noise reduction processing can be achieved in a noisy environment, and geographic space parameters and operation logic implied in user intentions are accurately analyzed in combination with a deep semantic analysis engine; through a multi-mode fusion control mechanism, real-time linkage interaction between a voice instruction and display equipment is supported, natural and smooth voice control experience is provided especially for scenes such as three-dimensional space positioning and topographic data calling in a holographic geographical environment, and the system has strong error recovery capability and good expansibility and is suitable for being popularized and applied. The method is especially suitable for a voice control interaction scene in a holographic environment.

The invention provides a multi-scene illumination management system integrating voice control and remote monitoring, and relates to the technical field of illumination management, and the system comprises the steps: receiving a scene wake-up instruction collected by a microphone array and a scene switching instruction sent by a remote monitoring terminal; adding priority labels and timestamps to the scene wakeup instruction and the scene switching instruction, and when it is detected that a timestamp difference value between the scene wakeup instruction and the scene switching instruction is smaller than a conflict time threshold value, determining an instruction arbitration coefficient through preemptive priority weights of the scene wakeup instruction and the scene switching instruction, determining an effective instruction according to the instruction arbitration coefficient and all the priority labels; and when the instruction priority of the effective instruction is greater than the instruction priority of the currently executed illumination scene instruction, generating a coverage execution signal, otherwise, generating an instruction discarding signal, further outputting an illumination control signal, and adjusting light parameters of the illumination equipment through the illumination control signal. According to the invention, multi-control-source conflicts in a lighting management system can be eliminated.

The invention relates to the technical field of voice recognition, in particular to a Bluetooth headset AI voice control method and system, and the method comprises the following steps: collecting a voice sample, carrying out the feature extraction of a voice signal through employing a Mel-frequency cepstrum coefficient, and generating voice feature data; and inputting the voice feature data into an acoustic model, and improving the recognition rate of the key instruction words by the acoustic model through learning features to obtain an optimized acoustic model. According to the method, acoustic feature capture is realized through voice signal feature extraction, the recognition accuracy of the key instruction is improved in cooperation with deep learning of acoustic features, the influence of different user speech speeds on the recognition effect is overcome by applying the time alignment technology of voice input, and the stability of the control instruction in different use scenes and speech speed changes is ensured. In addition, the recognition capability of a specific command is further mined and optimized by means of statistical characteristic analysis of voice, and efficient and automatic recognition and extraction of key control commands in continuous speech streams are completed.

Various implementations include approaches for voice control in audio devices. In some cases, a method includes: listening, using at least one audio capture device, for user input to control at least one attribute of an audio device; routing the user input through a machine learning (ML) model to determine a control action for the at least one attribute based on the user input; and causing the determined control action to be performed, wherein the ML model need not have been pre-trained with the user input to determine the control action for the at least one attribute of the audio device.

The invention relates to the technical field of smart home, and discloses an equipment control method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring an original control instruction set; performing multi-language expression conversion on each original control instruction to generate various variant control instructions matched with the original control instructions, and executing the same target operation on the variant control instructions and the original control instructions; for any variant control instruction, role conversion is carried out on the variant control instruction, and a voice control instruction set corresponding to each role is generated; and training the target control model by using the voice control instruction set, so that the target control model responds to the voice control instruction set and controls the target equipment to execute the target operation. By implementing the technical scheme of the invention, the adaptability of the smart home device to different user language habits and role identities is improved, and the naturalness and flexibility of voice interaction are enhanced.

The invention discloses a large model tool calling method and system based on risk assessment, and the method comprises the following steps: receiving a natural language instruction of a user, and obtaining a calling request of the user based on a large model; generating a risk score based on the user call request; generating a confirmation strategy based on the risk score, the user preference adjustment factor and the emergency degree adjustment factor; executing a corresponding confirmation process based on the confirmation strategy; based on the confirmation process, the controller executes tool calling; by the adoption of the technical scheme, the problem of balance between safety and user experience in tool calling is solved, a safer and more intelligent interaction mechanism is provided for voice control and large language model driven tool calling, a risk self-adaptive confirmation process and a multi-stage confirmation mechanism provide sufficient safety guarantee, and meanwhile the safety of a user is improved. And the user interaction experience is improved to the greatest extent.

The invention relates to the technical field of intelligent management, in particular to an intelligent medicine safety management system based on voice navigation and an application method of the intelligent medicine safety management system. The storage unit is arranged to be used for storing a plurality of medical articles, and the medical articles are provided with attribute information including the valid period; the triggering module is used for opening the storage unit and triggering and reminding the position of the matched medical article or triggering the medical article to be discharged to the medicine outlet; the identity recognition module is used for recognizing personnel information of personnel operating the mobile medicine vehicle; and the voice control module is configured to receive voice information of a person at first, then identify key information including the medical articles from the voice information, then find the positions of the corresponding medical articles from the storage unit, and then transmit the position information to the trigger module to obtain the corresponding medical articles. The defects of an intelligent management system in the aspects of traceability and accurate management are overcome.

The invention provides an intelligent automatic door sound control method and system, and relates to the technical field of intelligent control. The method comprises the following steps: acquiring voiceprint control data of an authorized object, and establishing a voiceprint control database; acquiring real-time voice control detection data, and performing object recognition based on voiceprint features in combination with the voiceprint control database to determine a real-time target object; extracting object voice control feature information from the voiceprint control database, and combining real-time voice control detection data to carry out matching analysis based on object features to form object matching analysis result data; and performing control analysis according to the object matching analysis result data to form object sound control data. According to the method, the intelligent technology is utilized to perform feature extraction and effective and accurate comparison and recognition on the sound data of the automatic door needing to be controlled, so that the high-recognition control effect of the automatic door based on the sound data is achieved, and the application range and scene of the automatic door are effectively expanded.

The invention provides a voice interaction control method and device of a browser, electronic equipment and a storage medium, and the method comprises the steps: obtaining a voice control instruction input by a user, and determining a target control intention based on the voice control instruction; obtaining a target document object model tree corresponding to the current webpage of the browser; sending the target control intention and the target document object model tree to a server, and receiving at least one control instruction generated by the server based on the target control intention and the target document object model tree; and executing the at least one control instruction, and controlling the webpage to render an interaction result corresponding to the voice control instruction. In this way, the steps of maintaining and developing each website and exhausting all webpage functions to generate the instruction set can be reduced, and the control efficiency of browser voice interaction control can be improved.

The invention relates to a robot autonomous navigation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a plurality of sensing data sets from different sensors; wherein the sensing data sets carry the same timestamp; generating a semantic map and a geometric map of the target area according to the sensing data sets; acquiring voice control information, and matching at least one semantic tag in the semantic map according to the voice control information; and generating a navigation path according to the matched semantic tag and the geometric map, and completing an autonomous navigation task of the robot according to the navigation path. The method can improve the autonomous navigation stability of the robot.

The invention relates to an Internet of Things smart home voice terminal control method and system based on a cloud platform, and belongs to the technical field of smart home voice control. The method comprises the following steps: by taking home position data of a user currently performing voice interaction as priori knowledge, performing weight dynamic adjustment on acquired voice data to complete adaptive beam forming processing; feature extraction is carried out on the voice data after beam forming processing, voice features are packaged into an encrypted data packet, and the encrypted data packet is sent to a cloud platform through an optimal transmission path; and constructing an instruction library associated with information on the cloud platform, and matching a device instruction in the instruction library through semantics analyzed by the voice features. According to the method, dual-frequency WiFi positioning and sound source positioning are fused, self-adaptive beam forming is driven by priori knowledge, reverberation elimination and weight dynamic adjustment are combined, and the voice definition and recognition rate under strong noise are remarkably improved; an instruction library is mined and constructed through association rules, and accurate instruction matching is realized by adopting multi-dimensional arbitration.

A smart adjustable bed system combines an adjustable bed, a smart hub, a server, and smart devices to provide a system for controlling the raising and lowering of the adjustable bed. The smart hub acts as a gateway interconnecting the smart adjustable bed and a remote server capable of powerful voice recognition and artificial intelligence at a shared price. The system includes methods of using the system to allow an additional smart device such as a tablet computer to act as a remote control for the smart adjustable bed. The system further enables voice controls to be used to raise and lower the adjustable bed. Lastly, the voice recognition of the smart hub can be used to detect snoring and to send a signal to the adjustable bed to raise the bed to a position until the user reaches a position where snoring stops.

The invention provides an out-of-vehicle voice control method and device, a storage medium and electronic equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: firstly obtaining audio signals collected by a microphone array on a vehicle for different areas outside the vehicle; the audio signals are preprocessed; performing sound source positioning and sound source separation according to the preprocessed audio signal to obtain a multi-channel audio signal; then performing wake-up word recognition based on the multi-channel audio signal, and determining a target channel where the wake-up word is located; and executing a corresponding vehicle voice control command according to the audio signal corresponding to the target channel. According to the method and the device, the audio signals are acquired through the microphone arrays in different areas around the vehicle, and the multichannel audio signals are obtained through preprocessing, sound source positioning and separation, so that accurate wake-up word recognition and voice control command execution are realized, outdoor complex environmental noise can be effectively shielded, and the accuracy of out-of-vehicle voice control is greatly improved.

The invention relates to the technical field of garbage cans, and discloses an intelligent mobile garbage can with voice control and remote control functions and a control method thereof.The intelligent mobile garbage can comprises a garbage can body, a can cover is installed on the top of the garbage can body, and an annular microphone array is installed on the front side of the garbage can body; the garbage can comprises a garbage can body, a TOF camera is installed on the front side of the garbage can body, an ultrasonic sensor is installed outside the garbage can body, a buzzer alarm is installed on the left side of the garbage can body, and a magnetic type charging contact is installed at the bottom of the garbage can body. According to the invention, the sound source orientation precision of + / -5 degrees is realized through the annular microphone array + TDOA algorithm, the instruction recognition rate of 92% or above is still kept in a noise environment in combination with the DPRNN model, the false triggering probability is remarkably reduced, dual identity verification: voiceprint comparison and off-line / on-line instruction analysis dual verification is carried out, illegal user control or pet false triggering is prevented, and the safety of a pet is improved. And the safety is improved by more than 80%.

According to the smart home voice control method and system, the computer equipment and the storage medium provided by the invention, the voice is converted into the characters, the keywords are extracted according to the characters, the first keyword or the second keyword is obtained from the keywords, and the complete control instruction is obtained and formed; the corresponding equipment is executed and operated to perform corresponding actions according to the obtained control instruction, and no response is made when the character data between the first keyword and the second keyword is obtained, so that the keywords in the user voice can be accurately obtained, the corresponding control instruction can be obtained, the instruction is prevented from being interrupted by a dialogue, the recognition accuracy of the user intention is improved, and the user experience is improved. And the actual demand of the user can be better understood. In the embodiment of the invention, the voice data which fails to respond are input into the first model, the processing of the first model is combined with the instruction matching library in the server, and the control instruction set which is converted into the response is performed in the first model, so that the problem of less data in the local instruction matching library can be avoided.

The invention provides a surgical anatomy monitoring method and system based on AR glasses, and relates to the technical field of augmented reality, and the method comprises the steps: obtaining medical knowledge data through augmented reality equipment, and generating a digital data set containing a three-dimensional model, a text and a two-dimensional image; acquiring real-time image data from the surgical site, extracting corresponding anatomical structure data, and generating a three-dimensional model data set; presenting the three-dimensional model data set through augmented reality equipment, and superposing the surgical operation guidance data to generate an interactive display result; and receiving a voice control instruction, adjusting the three-dimensional model data set or the surgical operation guidance data, and generating adjusted display content. According to the method, the shielded organ structure in the image data can be analyzed, a complete anatomical structure is generated by combining database inference, and related information is automatically labeled. According to the system, by integrating medical knowledge, the augmented reality technology and image recognition analysis, visual and accurate visualization assistance is provided for an operation, and the operation precision and the teaching effect are improved.

The invention relates to the technical field of voice recognition and intelligent household electrical appliance control, in particular to an induction cooker control method based on voice recognition, which comprises the following steps: synchronously acquiring a voice signal and a lip motion signal, and generating multi-modal sensing data through timestamp alignment; performing cross-modal anti-noise processing on the data, and outputting a fusion feature tensor fusing acoustic and visual features; semantic analysis and danger instruction recognition are executed, and a risk filtering control instruction containing temperature / fire parameters is generated; calling a thermodynamic dynamic model to calculate a power control parameter based on the instruction parameter; converting a power parameter into a space vector modulation waveform to drive a load circuit, and synchronously collecting the pot bottom temperature; and triggering an anti-noise process and thermodynamic model parameter updating according to the deviation between the actual temperature and the target temperature. Noise interference is reduced through multi-modal signal cross validation, dangerous instructions are intercepted in combination with knowledge graph constraints, the noise suppression capability and the temperature control precision are continuously optimized, and the safety and reliability of voice control in a complex environment are improved.

The invention provides a vehicle-mounted voice control method, device and system, and relates to the technical field of intelligent automobiles, low-power-consumption accurate wakeup is realized through fusion of wearable equipment and a vehicle-mounted sensor, a voice instruction is analyzed in combination with a local-cloud hybrid model, a security level label is given according to the real-time state of a vehicle, and the dangerous operation interception rate is increased. The reinforcement learning dialogue strategy is constructed based on the security level, multi-level interruption and backtracking are supported, and the complex instruction processing efficiency is improved. A safety key instruction is exclusively executed on a real-time system core through a hardware isolation mechanism, microsecond-level response jitter of braking, steering and other operations is achieved, and a full-link safety closed loop is constructed. According to the method, the accuracy and safety of voice interaction are effectively improved, the problems of response delay, decision adventure, unreliable execution and the like of a traditional system are remarkably improved, and the human-vehicle interaction experience and the driving safety level are enhanced.

A method for performing wake-up control on a voice-controlled device with aid of detecting voice feature of self-defined word and an associated processing circuit are provided. The method may include: performing feature collection on audio data of at least one audio clip to generate at least one feature list of the at least one audio clip, in order to establish a feature-list-based database in the voice-controlled device; performing the feature collection on audio data of another audio clip to generate another feature list of the other audio clip; and performing at least one screening operation on at least one feature in the other feature list according to the feature-list-based database to determine whether the other audio clip is invalid, in order to selectively ignore the other audio clip or execute at least one subsequent operation, where the at least one subsequent operation includes waking up the voice-controlled device.

The invention relates to the technical field of voice control of household electrical appliances, particularly provides a voice control method of an intelligent household electrical appliance and the intelligent household electrical appliance, and aims to solve the problem that an existing voice control system cannot accurately recognize an effective voice instruction in a noisy environment. In order to achieve the purpose, the voice control method of the intelligent household electrical appliance comprises the following steps: after a voice control function is started, collecting audio data within a preset duration; environment noise and voice instructions of the surrounding environment in the audio data are recognized; when the environmental noise is greater than or equal to a preset noise threshold value, acquiring a voice keyword in the voice instruction; according to the voice control method disclosed by the invention, when the surrounding environment noise is greater than the preset noise threshold value, the environment noise and the voice instruction in the acquired audio data can be identified, and the intelligent household electrical appliance is controlled by identifying the keyword in the voice instruction; the accuracy of recognizing the voice instruction in the audio data is improved.

The invention provides a software control method, system and equipment based on a digital human system and a medium, and relates to the technical field of artificial intelligence, and the method comprises the following steps: obtaining multi-modal input information input by a user; sending the multi-modal input information to a large language model, and obtaining keyword information and operation information fed back by the large language model; according to third-party software information in the keyword information, third-party software is controlled to execute the operation information, and output text information is generated; inputting the output text information to a voice synthesis module to obtain output voice; and based on the output voice, controlling a digital person simulated by the digital person system to play the output voice. According to the technical scheme provided by the embodiment of the invention, the digital human system can control the third-party software, the use convenience of the digital human is improved, the application scene of the digital human is enriched, and the interaction experience of the user is enhanced.

A system for controlling unmanned vehicles such as drones, ground vehicles and robots includes multiple human-to-machine interface components to manage interactions efficiently and effectively between humans and robots with respect to control mechanisms (i.e., inputs such as voice-commands or joystick use) and monitoring (i.e., outputs such as camera or other sensor feeds, geolocation overlay, or audio feedbacks). A system according to the principles of the invention includes numerous modalities for control (e.g., voice-control, gesture-control, touch screen, joystick or other hand-held controllers) as well as monitoring (visual screen display, heads-up-display, audio feedbacks, geolocation overlay, haptic feedback, wearable sensor devices). The system is preferably expandable and may include additional modalities in the future, such as eye-tracking as compared to voice or gesture control.