314 results about "Speech output" patented technology

The embodiment of the invention provides a digital human interaction system and method based on multi-modal emotion recognition, and belongs to the technical field of digital human interaction. The system comprises a multi-modal sensing module used for collecting multi-modal data and preprocessing the multi-modal data to generate a standardized data stream; the cross-modal fusion and emotion recognition module is used for carrying out interactive modeling on the multi-modal features and outputting a current emotion label and emotion intensity; the reaction planning module is used for generating a composite reaction strategy; and the digital human rendering module is used for mapping the composite reaction strategy into control signals corresponding to the voice, the facial expression and the action respectively, and driving a digital human to execute corresponding voice output, facial expression change and limb action through the control signals so as to realize interaction. According to the method, multi-modal data are deeply fused through the cross-modal graph neural network and comparative learning, the weight is dynamically adjusted in combination with the modal confidence, and the emotion recognition accuracy and robustness are improved.

The invention relates to the field of artificial intelligence medical application, and discloses a lightweight intelligent traditional Chinese medicine inquiry system and a construction method thereof, and the system comprises a multi-dialect adaptive speech recognition module, a traditional Chinese medicine intelligent dialogue large language model module, a natural speech synthesis module, and a continuous learning mechanism module. The multi-dialect adaptive speech recognition module is used for converting dialect speech input of a patient into a standard text; the traditional Chinese medicine intelligent dialogue big language model module is the core of the system and is used for carrying out natural language understanding, dialectical reasoning and inquiry dialogue generation, and the natural speech synthesis module is used for converting a text response generated by the system into speech output; and the continuous learning mechanism module realizes continuous optimization of the large language model through incremental learning architecture and clinical feedback integration. According to the method, while the professional traditional Chinese medicine diagnosis capability is maintained, the calculation complexity is remarkably reduced, and the universality and sustainable development capability of system application are improved.

An information processing system, method, and program for conducting interviews with applicants is provided. [Solution] The method includes starting a conference session in an interview preparation mode, and switching the conference session to the interview mode when an instruction to switch to the interview mode is received from a user, starting an interview with an avatar selected in the interview preparation mode as the interviewer, displaying an avatar in the interview preparation mode, outputting a first utterance for breaking the ice as the avatar's speech, outputting a second utterance for setting the avatar as the avatar's speech, and displaying selectable options for multiple setting items of the avatar, and accepting an avatar selection including a first response to the first utterance and a second response or selection of an option to the second utterance, and a switching instruction, a first display control step of displaying an avatar changed in accordance with the avatar selection, and a second display control step of displaying the changed avatar.

The invention relates to the technical field of voice semantics, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a voice generation method, device and equipment based on pseudo-autoregression modeling and a medium, and the method comprises the steps: obtaining a training sample containing a text sequence, a prompt voice segment and a target semantic token sequence; performing continuous fragment mask training on the text-to-semantic model to obtain a pseudo-autoregression trained text-to-semantic model; generating candidate speech output by using the text-to-semantic model and the initial semantic-to-acoustic model which are subjected to pseudo-autoregression training, and constructing a preference data pair; updating the semantics-to-acoustics model based on the preference data pair to obtain a preference optimized semantics-to-acoustics model; and generating target voice output based on the target text and the target prompt voice. According to the method, the time sequence modeling capability of the model is enhanced through pseudo-autoregression training, and the voice generation quality is directly optimized through the preference data pair, so that the voice alignment precision and the subjective listening feeling performance are improved.

The invention discloses an information acquisition system and method suitable for visually impaired people. The system comprises a hardware layer, a driving layer, an operating system layer, a middleware layer and an application layer which are sequentially in communication connection through interfaces. The application layer comprises a voice interaction module, a large model integration module and a braille conversion module; the hardware layer is used for collecting a voice input instruction and outputting a braille character sequence and a voice output result; the voice interaction module is used for converting a voice input instruction into a text input instruction and converting a text output result into a voice output result; the large model integration module is used for analyzing the text input instruction and generating a text output result; and the braille conversion module is used for converting the text output result into a braille character sequence, so that a hardware layer outputs the braille character sequence based on a timestamp alignment technology. Therefore, based on powerful semantic understanding and information retrieval of the large model integration module, accurate information acquisition is realized, and a five-layer decoupling architecture is adopted, so that the convenience of later system maintenance is improved.

The invention discloses a sign language-voice conversion system, and belongs to the technical field of auxiliary communication and wearable computing. The system comprises a wearable myoelectricity acquisition module used for acquiring double-arm myoelectricity signals when a user executes sign language; the mobile terminal module is wirelessly connected with the acquisition module and is used for receiving and preprocessing the signal and uploading the signal; the cloud processing module is used for receiving the signal, converting the signal into text information through a sign language recognition model, and further calling a voice synthesis service to convert the text into voice data; and the wearable audio output module is used for receiving and playing the voice data. Through an innovative end-to-end hardware system architecture, natural, accurate and real-time translation and voice output of sign language gestures are realized, communication barriers between hearing-impaired people and healthy hearing people are effectively solved, and the system has the advantages of flexible deployment, user friendliness and privacy protection.

To improve the accuracy of a questionnaire collected from a user who drove a test-drive vehicle.SOLUTION: A questionnaire apparatus which can be disposed in a test-drive vehicle includes an input unit to which voice can be input, an output unit which can output voice, and a control unit. The control unit outputs, while a user is driving the test-drive vehicle, voice for a questionnaire to a user via the output unit at a predetermined timing, and executes processing to receive answers of the user to the questionnaire via the input unit.SELECTED DRAWING: Figure 4

The invention discloses an automobile seat motor intelligent sliding rail adjusting system based on AI voice interaction, and the system comprises the following modules: a local voice wake-up module which is used for monitoring the voice input of a user, and activating a voice recognition module after detecting a preset wake-up keyword; the voice recognition module is used for generating a standardized text instruction; the semantic modeling module is used for executing word vector modeling processing on the standardized text instruction; the control parameter mapping module is used for inputting the semantic feature vector into a trained neural network model; the slide rail state detection module is used for collecting slide rail state information in real time; the voice synthesis module is used for converting the content in the prompt information field into a voice output content template; the vehicle-mounted audio output module is used for generating broadcast content; and the voice interaction log module is used for recording information involved in the voice interaction process. Semantic modeling and control mapping are fused, and the intelligent voice-driven seat adjusting system is constructed.

Methods and systems are disclosed for iteratively training a user and a ML model to produce accurate inner speech outputs. The methods and systems access a ML model and perform a first training iteration in which EMG data corresponding to inner speech is processed by the machine learning model to decode the EMG data into a set of predicted phonemes, phoneme sounds, words or phrases. The methods and systems present the set of predicted phonemes, phoneme sounds, words or phrases to the user and form a first set of training data comprising the set of predicted phonemes, phoneme sounds, words or phrases, the EMG data, and the set of specified phonemes, phoneme sounds, words or phrases as ground truth information. The methods and systems update parameters of the ML model based on the first set of training data prior to starting a second training iteration.

The invention discloses a sign language recognition method based on double-arm electromyographic signals, and belongs to the technical field of human-computer interaction and biological signal processing. The method comprises the steps that multi-channel electromyographic signals generated when sign language gestures are executed are synchronously collected through electromyographic arm rings worn on the left forearm and the right forearm of a user; performing preprocessing and feature extraction on the signal to obtain a time sequence feature sequence of left and right arms; the time sequence feature sequence is input into a pre-trained two-arm collaborative recognition model, and the model outputs a sign language gesture recognition result by fusing the spatial-temporal features of the left arm and the right arm; and finally, the recognized text information is converted into voice to be output. According to the method, the cooperation and time sequence relation of the double-arm electromyographic signals is creatively utilized, the problems that a traditional visual recognition method is greatly interfered by the environment, privacy is invaded, and double-hand linkage complex gestures cannot be effectively analyzed through single-arm electromyographic recognition are solved, and natural, accurate and real-time recognition and translation of the double-hand sign language gestures are achieved.

The invention discloses a controllable voice generation method and device based on multi-agent dynamic scheduling, and belongs to the technical field of voice synthesis, and the method comprises the steps: constructing a multi-agent voice generation frame comprising a central scheduling module, an identity agent, an emotion agent and an environment agent; a central scheduling module analyzes a user instruction and outputs a structured task plan to drive each agent to generate primary voice output of identity, emotion and environment dimensions, and a cooperation cost matrix between the agents is constructed according to the primary voice output; the optimal execution path of the multiple agents is solved through an optimization algorithm based on the cost matrix, the agents are executed in a cascading mode based on the optimal execution path, and finally sound mixing is completed and high-quality voice is output. According to the method, the naturalness, the semantic consistency and the overall quality of the synthesized voice in a complex scene can be remarkably improved, and the method is suitable for various man-machine interaction application scenes such as intelligent voice assistants, virtual digital humans, immersive entertainment, barrier-free voice services, personalized content creation and the like.

The invention relates to the technical field of voice processing and enhancement, in particular to a noise isolation and target voice enhancement system based on specific voice pre-storage, and the system extracts pre-stored features from a pre-stored target voice database module through collecting environment audio signals in real time and carrying out frame segmentation and frequency domain transformation; adaptive modulation of amplitude and phase of each sub-band signal is realized by combining energy sensing sub-band modulation, then environmental noise energy is identified through dynamic noise isolation and multi-stage suppression is carried out, and finally continuous and clear target voice output is generated through enhanced fusion. The method can achieve the effective enhancement and environmental noise suppression of the target voice in a complex and changeable environment, improves the voice recognition precision and definition, supports the dynamic switching of multiple teachers and multiple classes, adapts to the target voiceprint change, and achieves the high-robustness voice enhancement and noise reduction in teaching, conference and multi-target scenes.

The invention relates to the technical field of voice semantics, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a voice interaction control method, device, equipment and medium, and the method comprises the steps: obtaining multi-mode perception data, and constructing a dynamic scene model; session feature parameters are extracted and input into a decision model to generate a strategy parameter set; a dialogue process and expected voice output are generated according to the strategy parameter set and voice characteristics of the voice interaction device; controlling the voice interaction device to execute voice output and collect actual voice output; monitoring an error between the actual voice output and the expected voice output, and performing compensation adjustment; and collecting feedback data after the voice interaction session is ended, and optimizing the model and the control parameters according to the feedback data. According to the method, closed-loop control of perception, decision, output and feedback is established, so that the voice interaction equipment can dynamically adjust voice output according to a real-time environment and user characteristics and continuously perform self-learning optimization, and the accuracy and naturalness of voice interaction are improved.

The present disclosure provides a work machine capable of setting a restricted area on the basis of an instruction in a natural language. This work machine (shovel 100) comprises an attachment (AT) for work, an information acquisition unit (301), a language conversion unit (303), an instruction acquisition unit (302), and an area setting unit (306). The information acquisition unit (301) acquires information pertaining to the posture of the attachment (AT) and the surrounding environment. The language conversion unit (303) converts the information acquired by the information acquisition unit (301) into a natural language. The instruction acquisition unit (302) acquires an instruction in the natural language from an operator. The area setting unit (306) sets restricted areas (RA1 to RA10) in which entry or operation speed is restricted at a work site. The area setting unit (306) sets the restricted areas (RA1 to RA10) on the basis of a result obtained by interpreting, using a language model (LM), the instruction acquired by the instruction acquisition unit (302) and the information converted into the language by the language conversion unit (303), or on the basis of a result obtained by interpreting the instruction acquired by the instruction acquisition unit (302) using the language model (LM), in combination with the information acquired by the information acquisition unit (301).

The invention discloses an unmanned aerial vehicle natural language control and interaction method and system based on a multi-mode large model, and belongs to the field of unmanned aerial vehicle interaction.The method comprises the steps that a current environment image and a user voice instruction of an unmanned aerial vehicle are obtained and converted into a text; performing intention classification on the text instruction information, and judging whether the current task is a flight control task or a question and answer interaction task; if the task is a flight control task, inputting the environment image and the text instruction into a multi-mode large model for vision-language joint reasoning, and generating a structured flight control instruction; if the task is a question-answer interaction task, performing knowledge retrieval by using the large model to generate question-answer information and outputting voice; adjusting the flight state of the unmanned aerial vehicle according to the structured instruction; and after the task is completed, the unmanned aerial vehicle is controlled to enter an obstacle avoidance self-stabilization mode and waits for a next instruction. According to the method, the mapping from the unstructured natural language to the bottom layer action of the unmanned aerial vehicle is realized, and the intelligent level of man-machine interaction and the flight safety in a complex environment are effectively improved.

A smartphone includes: a first biological information acquisition unit that acquires first biological information being biological information about a driver while driving a vehicle; a driving behavior acquisition unit that acquires driving behavior information indicating driving behavior of the driver; a danger level calculation unit that calculates a driving danger level indicating a danger degree while the driver is driving the vehicle, based on the first biological information and the driving behavior information; a speech output unit that performs speech output for the driver, in accordance with a degree of change in the driving danger level; a response acquisition unit that acquires response information indicating a response from the driver to the speech output; and an output control unit that controls the speech output unit based on the response information.

To provide a cooking system capable of appropriately performing notification corresponding to a heating state by a cooker to a person who has performed cooking when no person exists in a cooking space.SOLUTION: A cooking system includes a cooker 10 for heating a cooking appliance by a heating part, an alarm 20, and a communication part 30 for transmitting information between the cooker 10 and the alarm 20. The alarm 20 includes a notification output part 22b that outputs notification information, a sound output part 24 that outputs the notification information by sound, a human body detector 23 that determines whether or not a person is present in the cooking space, and a determination processor 22c that sets a time-up time in which the larger the amount of heat is, the shorter the time becomes on the basis of the amount of heat at a heating part as cooking state information acquired from the cooker 10 via the communication part 30. The notification output part 22b outputs the notification information when a time during which no person is detected by the human body detector 23 exceeds the time-up time in a situation in which heating continues in the heating part.SELECTED DRAWING: Figure 2

The invention provides a standardized training system based on a large model and a virtual generation technology, belongs to the technical field of artificial intelligence medical education, deeply fuses a large model technology in the field of artificial intelligence and a virtual generation technology in the field of virtual reality, and improves the training efficiency by integrating an advanced voice interaction function. Voice instructions of intern doctors can be responded in real time, and natural and smooth dialogue communication is achieved. Meanwhile, by means of the virtual generation technology, the system can generate a highly-vivid virtual patient image, the appearance, expression and action of the patient are adjusted according to specific cases, and the reality sense of simulation is further enhanced. In addition, a synchronous mouth shape technology is also adopted, so that the mouth shape of the virtual patient is accurately matched with voice output, and the immersion experience of interaction is improved. By combining customized training and a controllable generation strategy of a large model, complex cases can be effectively simulated, real medical data can be fully utilized on the premise of protecting patient privacy, and simulation accuracy and practicability are improved.

The invention discloses a voice real-time question and answer processing method based on a large model and a domain knowledge base, which belongs to the technical field of computer data processing, and comprises the following steps: acquiring a voice input stream of a user, carrying out intelligent sound wave deconstruction on the voice input stream, generating a text stream, and carrying out dependency syntactic analysis and semantic role labeling; generating intention information and key information, dynamically accessing a domain knowledge base, executing predictive loading, generating a preloaded data subset, performing fusion processing by combining the intention information, the key information and the preloaded data subset, generating a fusion result, performing accuracy verification and correction, generating a natural language answer, and converting the natural language answer into voice output. The technical scheme of combining knowledge predictive loading driven by intention analysis, context fusion and answer traceability correction is adopted, and low-delay response, high-precision intention understanding and high-factuality answer of voice questions and answers can be achieved.

The invention relates to the technical field of conference room sound equipment control, in particular to a multimedia conference room sound equipment system based on artificial intelligence, which acquires image positions and head postures of participants in real time through a personnel positioning module, automatically establishes a spatial mapping relation between the personnel and channels in combination with microphone layout, and realizes dynamic binding of microphone channels. A main speaking channel is automatically recognized based on voice activity detection of audio data, differentiated control is performed on channel gains through a sound output module, and background noise of a non-speaking microphone is effectively suppressed. The behavior characteristics and the interaction intention of a main speaker are extracted, joint modeling is carried out on the behavior characteristics and the interaction intention based on a reinforcement learning model, prediction of a next speaker and dynamic updating of a main channel are achieved, and strategy parameters are continuously optimized based on speech feedback. Manual operation is reduced, and voice output definition and natural fluency of conference interaction are improved.

The invention provides a multi-mode voice interaction method and device and intelligent equipment, is suitable for the technical field of intelligent voice interaction, is applied to the intelligent equipment, and comprises the following steps: in response to a detected voice activity, extracting first voice data in the voice activity, and obtaining video data shot synchronously with the first voice data, a plurality of different users are shot in the video data. And screening out a target user sending the first voice data from the video data. And performing semantic integrity analysis on the text content corresponding to the first voice data. And when the semantic integrity analysis result is that the semantics is incomplete, continuously acquiring second voice data of the target user for a plurality of times, and generating a corresponding target statement with complete semantics after the first voice data and the second voice data are combined. Generating reply data according to the target statement, and outputting the reply data through voice. According to the embodiment of the invention, accurate, coherent and real-time voice interaction with the user needing interaction can be realized.

The invention provides an information processing system. The information processing system comprises an image acquisition device used for acquiring front image data; the analysis server device is used for analyzing the collected image data; the voice output device is used for carrying out voice prompt on visually impaired people according to the analyzed image data; and the display device is used for performing augmented reality display according to the analyzed image data.

The invention is applied to the technical field of dialogue interaction systems, and particularly discloses an induced dialogue interaction system based on a psychological intervention artificial intelligence model, which comprises a voice recognition module, a deep language module, a voice output module, a closed feedback module and an abnormal condition processing module, the voice recognition module is connected with the deep language module through wireless signals, and the deep language module is connected with the voice output module through wireless signals. According to the induced dialogue interaction system based on the psychological intervention artificial intelligence model, psychological theories such as a social emotion selection theory, a communication adaptation theory and the like are introduced in the system, and an old people age layering optimization deep language model is combined, so that the recognition and fitness reply ability of the model to common emotion expression of old people is enhanced; meanwhile, by means of intervention boundary setting, psychological intervention scenes of the old people are accurately adapted, and intervention safety and effectiveness are guaranteed.

Voice-interaction massage device for massaging at least one penis, comprising the following: a housing comprising a first massage chamber and a second massage chamber, each of the first massage chamber and the second massage chamber being configured to accommodate at least part of the penis; a massage module incorporated in the housing, wherein the massage module is configured to massage at least a part of the at least one penis that is inserted into at least one of the two massage chambers; a loudspeaker; and a first sensor configured to detect movements of the penis in the first massage chamber; a control unit that is electrically connected to the speaker and the first sensor; the control unit, as soon as the first sensor detects movements of the penis in the first massage chamber, activates the speaker to output an initial voice message.

A user is assisted in performing a voice operation appropriately.A situation determination section determines a situation. A state control section controls a voice command appropriate for the determined situation to put the voice command into a receivable state. For example, the user is informed of what the voice command in a receivable state is, by means of display or voice output. The user can utter a voice command without performing a user action to prevent false recognition, such as the utterance of a wake word. This reduces the troublesomeness and burden of the user.

A system is provided.SOLUTION: A learning system comprising: means for receiving an input of an alphabet; means for acquiring an English word based on the input alphabet; means for outputting the acquired English word by voice; and means for displaying an illustration corresponding to the English word.SELECTED DRAWING: Figure 1

The present disclosure provides a method for training a noise reduction model, a speech noise reduction method, an apparatus and an electronic device. The method comprises: obtaining source noisy speech data, and performing reverberation processing on the source noisy speech data to generate corresponding training samples, wherein the training samples comprise a plurality of samples, and each sample comprises multi-channel reverberation noisy speech data; training a to-be-trained speech noise reduction model based on the multi-channel reverberation noisy speech data included in the training samples to obtain a trained first speech noise reduction model. In the present disclosure, the human ear has a good listening experience for the noise reduction speech output by the trained speech noise reduction model, improves the propagation accuracy of the information carried in the speech data, reduces the influence of noise on the propagation of the information carried in the speech data, improves the robustness of the speech noise reduction model, strengthens the applicability and practicality of the speech noise reduction model, and optimizes the training method and training effect of the speech noise reduction model.

The invention provides a voice processing method and device, equipment, a storage medium and a program product, and relates to the technical field of data processing, and the method comprises the steps: carrying out the feature extraction of to-be-processed voice data, and obtaining the acoustic features of the voice data; determining a first emotion category of the voice data based on the acoustic features; determining a first emotion parameter corresponding to the first emotion category; and generating voice output data based on the first emotion parameter and the acoustic feature, and outputting the voice output data. According to the invention, the output voice output data can reflect emotional changes, so that the user experience is improved.

The utility model relates to the technical field of vehicle-mounted domain control, and discloses a voice interaction device based on vehicle information, which comprises a vehicle-mounted processor, a voice input module, a voice output module, an audio processor, a first sound sensor and a vehicle speed sensor, the audio processor is used for carrying out noise reduction processing on interactive voice information data acquired by the voice input module by utilizing the intensity and frequency of noise in the vehicle body detected by the first sound sensor; the vehicle-mounted processor controls the output volume of the voice output module according to the vehicle speed value detected by the vehicle speed sensor. According to the utility model, the data after voice processing is stronger in interference resistance, the processed data is cleaner, and the voice recognition rate is increased; and the output volume can be automatically and adaptively increased, so that a driver can hear clearly in a complex environment.

The present invention is to provide a driving assistance device capable of avoiding the uneasiness of an occupant who is driving. To solve the above problem, the driving assistance device 11 includes: a cause determination section 204 that determines the cause of the generation of the alarm sound based on the behavior information acquired by the behavior information acquisition section 201 and the surrounding information acquired by the surrounding information acquisition section 40 when the occupant state determination section 203 determines that the occupant is affected by the alarm sound; and a voice output device 91 and a display device 92 that notify the occupant of the cause of the generation of the alarm sound determined by the cause determination section 204.