438 results about "Voice analysis" patented technology

The invention provides a voice education robot based on children voice modal characteristic perception, and relates to the field of intelligent education, the voice education robot adopts an AI and end-to-end voice analysis and processing technology to extract a time sequence of pitch and sound intensity from a voice input signal, and performs time sequence association mode analysis on the time sequence; the method comprises the following steps: performing feature generality compensation on pitch time sequence correlation mode features and sound intensity time sequence correlation mode features, and meanwhile, performing fragment embedding coding on voice input signals so as to intelligently generate education reply voice through compensated features and semantic embedding features of each voice input signal fragment. Therefore, the robot can dynamically adjust the reply content and generate personalized education reply voice according to the real-time feedback and emotion change of the child, which is helpful for enhancing the interaction effect and improving the learning enthusiasm of the child.

The invention relates to the technical field of vocal music training evaluation, and discloses a vocal music training intelligent evaluation method and system based on voice analysis. The method comprises the following steps: firstly, acquiring vocal music training original data, and processing and aligning multi-modal data by using a transfer learning small sample completion method when the data is insufficient; constructing a pronunciation stability evaluation model and a comprehensive pronunciation performance evaluation model; constructing a pronunciation scene simulator for different vocal music styles; the evaluation parameters are analyzed through a Shapley value decomposition algorithm, and a lightweight index system is constructed; and establishing a training scheme optimization agent model by using Gaussian process regression and a Bayesian optimization algorithm. The system comprises a data acquisition and completion module, an evaluation module, a simulation module, an analysis module, an optimization module and the like. The vocal music training system can comprehensively and accurately evaluate vocal music training, adapts to various styles, optimizes a training scheme, and assists a singer to improve the singing level through real-time feedback and visual display.

The invention provides a virtual digital population type synchronization method, system and device, a medium and a program product, and the method comprises the following steps: analyzing an input voice signal, and obtaining a voice feature; taking the voice features as input of a lip movement prediction model, and predicting corresponding lip movement parameters; driving a face model of the virtual digital human to perform real-time rendering according to the lip movement parameters, and realizing fine movement control of lips; and obtaining user feedback data, and continuously optimizing and adjusting the lip movement prediction model based on the user feedback data. Through advanced technologies such as deep learning, voice analysis and lip movement prediction, accurate synchronization of the virtual digital population type and the voice content is realized, and the expression ability of the virtual character and the user interaction experience are improved.

The invention relates to the field of intelligent voice analysis, in particular to a fuzzy instruction analysis method and system based on dual-channel noise reduction and a dynamic semantic map. The method comprises the following steps: (1) noise reduction voice recognition: combining dual-channel voice noise reduction and voice recognition, extracting a target voice signal in a high-noise environment, completing voice-to-text conversion, and outputting text data corresponding to the target voice signal; (2) multi-modal fusion: dynamically adjusting the weights of the voice data, the visual data and the sensor data based on real-time environment perception; (3) fuzzy instruction analysis: receiving the text data output in the step (1), and combining the weights of the optimized voice data, visual data and sensor data output in the step (2) to realize semantic map updating; a target device is positioned by using the dynamically updated semantic map in combination with device layout, environmental data and user instruction history, and a fuzzy instruction is analyzed. According to the method provided by the invention, the speech recognition precision and the fuzzy instruction analysis capability can be improved, and the operation flexibility is remarkably improved.

The invention provides a physiological state risk detection method, device, equipment and program product, which can be applied to the technical field of computers. The method comprises the following steps: acquiring a facial expression image, an eyeball tracking image, a limb balance image and audio data; key point coordinate values of a plurality of facial key points in the facial expression image are processed based on a first random forest to obtain a facial result, and the facial result represents a facial expression attribute and a facial symmetry attribute; inputting an eyeball movement distance obtained from the eyeball tracking image into a second random forest, and outputting a pupil staring result; inputting the related coordinate values of the limb key points in the limb balance image into a third random forest, and outputting a limb balance state result; performing voice analysis on the audio data based on a convolutional neural network to obtain a voice definition result; and inputting the face result, the pupil staring result, the limb balance state result and the voice definition result into a fourth random forest, and outputting a stroke risk detection result.

The invention discloses a full-volume voice analysis method and device based on a large model, equipment and a storage medium. The method comprises the following steps: acquiring voice interaction data of an agent and a user; according to an artificial experience rule and a large language model, extracting attributes associated with a product service in the voice data as increment mark information; obtaining full-amount marking information after standardization of the voice interaction data; training the large language model by taking the voice interaction data, the incremental marking information and the full marking information as training data to generate expert model information; and matching a target seat, a target user and a corresponding target product according to the expert model, and feeding back to a calling system, so as to push a call strategy matched with the prediction information to the target seat. Through incremental marking and total analysis of the voice interaction data, the outbound strategy and the call strategy are accurately matched for the seat, and the service efficiency and the success rate of the seat and the user are improved.

The invention discloses a non-contact physiological and psychological detection system based on multiple modes, relates to the cross technical field of artificial intelligence and biomedical engineering, and can collect multi-mode data such as facial images and sound signals of a user at the same time by integrating multiple sensors such as a camera and a microphone. The fusion of the multi-source data enables the system to more comprehensively capture the physiological and psychological state changes of the user, thereby improving the accuracy and reliability of evaluation. The system collects data in a non-contact mode, and discomfort and limitation possibly brought by traditional physiological monitoring equipment are avoided. According to the system, various non-contact detection technologies such as computer vision, voice analysis and natural language processing are comprehensively applied, and the physiological and psychological states of the user can be evaluated from multiple dimensions. The non-contact detection technology reduces the interference to the user, so that the detection process is more natural and efficient.

The invention discloses a children autism tendency detection method based on voice MFCC features. The method comprises the following steps: constructing a voice data set; the method comprises the following steps: extracting MFCC features in voice emotion data of normal and sick children, performing standardization processing on voice data, and finally performing feature data enhancement to obtain an MFCC feature enhanced data set, and dividing the MFCC feature enhanced data set into a training set and a test set according to a proportion; constructing a network model of a mixed local area type attention mechanism; training a network model mixed with a local area type attention mechanism; and testing the network model mixed with the local area type attention mechanism. The voice analysis is based on objective acoustic data, the influence of subjective judgment is reduced, compared with a detection method needing expensive equipment and a professional environment in the prior art, voice data collection is relatively easy, the collection speed is high, voice data can be completed through daily dialogues or specially designed voice tasks, the data processing cost is low, and the method is suitable for popularization and application. The method has the advantage of high detection accuracy.

The invention discloses an intelligent nursing record generation method and device, and the method comprises the steps: obtaining nursing voice data, and carrying out the noise reduction and sound enhancement processing to obtain a preprocessed voice stream; a speech recognition technology fusing ECAPA-TDNN and an x vector is adopted to recognize medical terminologies, and a text transcription result is generated; recognizing the voice of the target nurse from the preprocessed voice stream and the transcription result in combination with a speaker-independent model and a speaker condition model to obtain a voice transcription text of the voice; performing voice analysis and structured processing on the text by using a multi-modal self-supervised learning model and a hierarchical CNN-BiLSTM framework to obtain a structured text with clinical semantic features; key clinical information is extracted in combination with the medical ontology knowledge base, and a nursing record element set is obtained; and based on the nursing record element set, automatically generating a nursing record meeting the specification. According to the invention, the automatic generation from the nursing voice to the standardized nursing record is realized, and the efficiency and accuracy of the medical nursing record are improved.

The invention belongs to the technical field of man-machine interaction and robot control, and particularly relates to a man-machine physical twin system based on multi-modal video analysis and adaptive mapping and a control method, and the system comprises a multi-modal collection unit which is used for collecting original video streams of human body actions, expressions and voices, and compensating and repairing dynamic shielding; the semantic analysis unit comprises an action analysis module used for extracting a human skeleton key point set object interaction track from the original video stream, and an expression / voice analysis module used for outputting a facial action unit coefficient and a voice text with an emotion label; the self-adaptive mapping unit is used for establishing human body-robot joint kinematics mapping, distributing control bandwidth in real time according to task types and degrading non-key modes based on network states to guarantee action continuity, and non-contact action capture is achieved through a pure vision scheme by eliminating dependence on a wearable sensor; and the problems of failure and the like of a traditional visual scheme under shielding and illumination variation are solved.

The invention provides an alarm device based on artificial intelligence voice analysis, and relates to the technical field of voice analysis. An audio acquisition sensor is arranged in a key monitoring area through an audio sensing arrangement module; an environment fluctuation identification module obtains an area environment fluctuation coefficient of the key monitoring area; an alarm threshold configuration module determines a regional alarm threshold based on the regional environment fluctuation coefficient; the abnormal keyword library module traverses the historical voice data record sequence extracted by the historical voice data acquisition module to construct a regional abnormal keyword library; the voice anomaly analyzer module constructs a regional intelligent voice anomaly analyzer based on a regional anomaly keyword library and a regional alarm threshold value; and the anomaly recognition module performs anomaly recognition on the real-time voice data by using the regional intelligent voice anomaly analyzer to obtain alarm information. According to the method and the device, the technical problem of frequent false alarm and missing alarm caused by lack of accurate identification means for audio content in a complex environment in the prior art is solved, and the alarm accuracy and the response speed are improved.

The invention relates to the field of power supply work order service management, in particular to a power supply service management method and system based on multi-source data. The method comprises the following steps: collecting a current fault repair work order based on a power supply service platform, carrying out deep work order text semantic analysis and standard fault instance modeling, and constructing a global fault instance map; recognizing a client real-time repair call audio stream, carrying out time window voice analysis one by one, and carrying out intelligent fault work order filling, thereby obtaining a real-time audio intelligent fault work order; performing fault demand decomposition on the real-time audio intelligent fault work order and the global fault instance map, performing power supply service resource dynamic configuration regulation and control, and constructing a service resource regulation and control engine; and performing global fault work order real-time processing based on the service resource regulation and control engine, performing overdue work order early warning, and generating a service timeliness early warning strategy. Through dynamic resource allocation and preventive work order creation, the power supply service efficiency, the power grid reliability and the intelligent level are improved.

The invention relates to the technical field of smart home, and discloses a smart home control method and device for realizing user interaction based on a smart mirror, and the method comprises the steps: confirming a plurality of user registration instructions, obtaining a registration voice stream based on the user registration instructions, carrying out the feature extraction of the registration voice stream, obtaining reference voiceprint features, summarizing the reference voiceprint features, and carrying out the collection of the reference voiceprint features. The method comprises the following steps: obtaining a plurality of reference voiceprint features, confirming to receive a pre-confirmed voice wake-up word, carrying out voice collection based on the voice wake-up word to obtain a user voice stream, obtaining a voiceprint label by using the user voice stream and the plurality of reference voiceprint features, carrying out voice analysis on the user voice stream to obtain a control instruction, and sending the control instruction to a server. And performing permission verification by using the voiceprint tag and the control instruction to obtain a permission verification result, and obtaining response feedback based on the permission verification result. According to the invention, the problem that the personalized intelligent service cannot be provided because the current user identity cannot be distinguished and the control authority cannot be verified according to the user identity in the smart home interaction scene can be solved.

The invention provides a potential user mining method and system based on voice analysis, and relates to the technical field of voice analysis. Voice data published by a client on a platform is preprocessed, and the preprocessed voice data is analyzed from the aspects of emotional tendency and emotional abundance; an emotional abundant coefficient and an emotional tendency coefficient are respectively generated, a comprehensive emotional tendency coefficient of each section of effective voice is calculated through the emotional abundant coefficient and the emotional tendency coefficient, and the comprehensive emotional tendency coefficient is further analyzed to generate an emotional recommendation coefficient and a comprehensive recommendation coefficient; and evaluating potential mining values of the users according to the emotion recommendation coefficient and the comprehensive recommendation coefficient, and classifying the users. According to the method, the emotional abundance degree of the language is analyzed, the defect of tone analysis in traditional language analysis is overcome, evaluation of the mining value of the client is more accurate, pushing resources are saved, and high-quality clients are more easily mined.

The invention relates to a service compliance dynamic evaluation system based on real-time voice recognition, and belongs to the cross technical field of artificial intelligence and service compliance management. The system comprises a voice signal enhancement acquisition unit, a voice analysis and risk initial judgment unit, a dynamic evaluation iteration unit and a compliance risk disposal unit. The voice signal enhancement acquisition unit processes low-quality voice and generates a voice data set; the voice analysis and risk initial judgment unit is used for transferring voice in real time, extracting a dialogue intention and identifying violation contents and interactive emotions; the dynamic evaluation iteration unit outputs compliance scores and violation details and is in butt joint with a manual labeling platform; and the compliance risk disposal unit generates a risk label, carries out linkage training and appeal review, and forms a compliance risk disposal scheme. According to the invention, full quality inspection of service scenes in multiple industries such as finance, operators and the like is realized, the voice transfer accuracy and compliance rectification rate are improved, the verbal skill violation complaint rate is reduced, and dynamic monitoring and closed-loop disposal of service compliance are achieved.

The invention relates to a user portrait construction and updating method of an information system based on intelligent IVR. The method comprises the following steps: step 1, collecting user voice data through an IVR system; step 2, performing voice analysis on the recorded voice interaction data; 3, associating the historical behavior data of the user with the voice data, and establishing a user behavior model; step 4, constructing a user portrait; and 5, updating the user portrait. According to the method, real-time voice interaction between the user and the IVR system is fully utilized, and the emotion and demand of the user can be captured more accurately, so that a more refined user portrait is constructed.

Quantum circuits for QFT and Inverse QFT (IQFT) are disclosed that can be applied for use in signal and speech, analysis synthesis and compression. A unique method perceptual selection of QFT components is also outlined.

The invention relates to the technical field of speech analysis, in particular to an Alzheimer's disease recognition method and system based on speech features, and the method comprises the following steps: extracting frame-level parameters to construct a sequence, recognizing sparse and fractured sections, generating an abnormal trend, and completing speech feature recognition. According to the method, multiple parameters such as the mean value of amplitude absolute values, the maximum difference value and the minimum difference value are serialized and integrated, a double analysis mechanism for the sparsity and the jump of the voice amplitude fluctuation is formed by combining multi-section continuous ratio comparison and mutation trend positioning, the overlapping degree of trend indexes in adjacent frame sections is calculated, and sites in a trend structure are extracted; a trend structure line of the time sequence is established, directional change and point location density of the trend structure line are extracted, quantitative classification of abnormal trends in the frame sequence is completed, cross-scale feature coupling recognition from voice micro fluctuation to time sequence trends is achieved, the discrimination degree and accuracy of voice features of the Alzheimer's disease are improved, and the recognition accuracy of the Alzheimer's disease is improved. And the stability and the discrimination efficiency of the identification result are obviously improved.

Methods and apparatus to improve user experience on computing devices are disclosed. An example computing device includes a microphone to capture audio corresponding to spoken words. The example computing device further includes a speech analyzer to: detect a keyword prompt from among the spoken words, the keyword prompt to precede a query statement of a user of the computing device; and identify topics associated with a subset of the spoken words, the subset of the spoken words captured by the microphone before the keyword prompt. The example computing device also includes a communications interface to, in response to detection of the keyword prompt, transmit information indicative of the query statement and ones of the identified topics to a remote server.

The invention discloses a service control method based on voice analysis and a large language model, relates to the technical field of voice interaction, and solves the technical problems that in the prior art, an enterprise service system needs a user to manually fill in form fields item by item, so that operation is tedious and low in efficiency, and a process is interrupted due to lack of an intelligent completion mechanism due to lack of necessary parameters. According to the invention, a full-closed-loop control chain from the voice instruction to the service operation is constructed, the intention of the user voice input is analyzed through the fine-tuning large language model, and the service interface is dynamically matched, so that the system function operation is directly driven by the voice, and a two-way cooperation mechanism of voice input-system operation-result feedback is formed; and meanwhile, a dynamic parameter completion technology is adopted, the interface field needing to be filled is automatically verified in the parameter extraction stage, missing parameters are completed through context completion or voice guidance, the operation bottleneck of traditional form item-by-item filling is eliminated, missing of the field needing to be filled is avoided, and the service execution efficiency and the process robustness are remarkably improved.

The invention relates to the technical field of vehicles, and discloses a vehicle-mounted image generation device, a vehicle machine system and a vehicle. The method comprises the following steps: at least acquiring first point cloud data and first image data through a data fusion module, and converting the two data into a bird's-eye view feature map through a preset conversion algorithm; performing semantic analysis on the user voice through a preset semantic analysis model by using a voice analysis module; generating a vehicle-mounted application image at least applied to head-up display and / or screen display according to the bird's-eye view feature map and the semantic analysis result by using an image generation engine through a preset compression model; and terminating the generation process of the vehicle-mounted application image in a preset time period after the automatic emergency braking signal is received through the emergency interruption module, and at least applying the graphic processing computing power of the generation process to a vehicle collision avoidance decision. Therefore, the problem that in an existing vehicle-mounted image generation technology, due to the fact that the computing power is too large, vehicle decision making is not timely under the emergency situation can be solved, and the driving safety of a user can be guaranteed.

The invention relates to the technical field of voice analysis, and particularly discloses a vocal music training method and system based on artificial intelligence, and the method comprises the steps: collecting and analyzing the body posture parameters of a target vocal music training person, carrying out the preprocessing, detecting the posture abnormality, forming a first abnormal training set, capturing and analyzing the pronunciation feature parameters, and recognizing the pronunciation abnormality, thereby obtaining a vocal music training result; and integrating the first abnormal training set and the second abnormal training set to generate a total abnormal parameter training set, matching a correction set, and visually displaying the body posture abnormal degree and the abnormal reason and the pronunciation abnormal degree and the reason, so that the target vocal music training personnel can visually see own posture and pronunciation problems, and self-adjustment and correction are facilitated.

An oral function visualization system includes: an outputter that outputs information for prompting a user to utter a predetermined voice; an obtainer that obtains an uttered voice of the user uttered in accordance with the output; an analyzer that analyzes the uttered voice obtained by the obtainer; and an estimator that estimates a state of oral organs of the user from a result of analysis of the uttered voice by the analyzer. The outputter outputs, based on the state of the oral organs of the user estimated by the estimator, information for the user to achieve a state of the oral organs suitable for utterance of the predetermined voice.

The invention discloses an oven voice recognition control method based on artificial intelligence and a related device, and relates to the technical field of voice analysis, and the method comprises the steps: carrying out the preprocessing of voice instruction information; performing feature extraction on the voice instruction information to obtain a target acoustic feature; based on the target acoustic features, performing language recognition by using confidence analysis; performing semantic analysis on the voice instruction information based on language categories to obtain semantic text information; performing Mel smoothing coefficient calculation on the voice instruction information to extract voiceprint features, and determining voice output emotion according to the age group of the user to perform response text matching; performing rhythm analysis on the target response text information, and performing rhythm adjustment on the initial response voice based on rhythm analysis data; and performing operation instruction matching based on the semantic text information, outputting the target response voice, and controlling the oven to execute the target operation instruction. According to the invention, the voice recognition control of the oven can meet the high-intelligence requirement of a user.

The invention discloses an AI psychological counseling method and system based on multi-modal sentiment analysis and body intelligence fusion. The method comprises the steps that text, voice and image feature vectors of a patient are extracted; aligning feature dimensions through linear projection, adding space / time sequence position codes, inhibiting noise in combination with cross-modal attention and a gating weighting mechanism, hierarchically fusing text, image and voice features, and generating fusion features; based on facial actions, postures and voice analysis, identifying seven-estrus states of traditional Chinese medicine, outputting emotion probability prediction distribution of a patient, and performing element-by-element product on the emotion probability prediction distribution and the prediction distribution to obtain a video generation vector; a video frame is generated by using StyleGAN-V, the consistency of content and emotion is constrained through emotion driving loss, and a personalized virtual human image is configured. The system comprises a data acquisition module, a feature extraction module, a multi-modal fusion module, an emotion recognition module and a video generation module. According to the method, a closed loop of'emotion analysis-emotion quantification-video generation 'is constructed, and the accuracy and universality of remote psychological consultation are improved.

The invention belongs to the technical field of speech analysis, and discloses a spoken English pronunciation quality evaluation method based on multi-modal speech feature analysis, which comprises the following steps: acquiring a spoken English speech signal of a target user, and performing multi-domain decomposition on the speech signal to obtain multi-modal speech features; performing time-frequency domain corresponding relation analysis and feature extraction on the multi-mode speech features to obtain a pronunciation detail feature sequence; performing multi-scale matching on the pronunciation detail feature sequence and a preset standard pronunciation template, constructing a multi-dimensional representation model based on a multi-scale matching result, and calculating a fine-grained quality score of a phoneme unit in each multi-dimensional representation model in combination with rhythm and rhythm parameters in the multi-modal speech features, the rhythm coherence score and the overall fluency score are fused to generate a comprehensive pronunciation quality evaluation result and a visual diagnosis report of pronunciation deviation; the oral English pronunciation evaluation method realizes comprehensive and refined evaluation of oral English pronunciation, and provides a scientific guidance basis for personalized language learning.

A system and a method for controlling a lamp of a vehicle are provided, The system includes a voice recognition device to recognize a voice signal from a user, a voice analyzing device to analyze context of the recognized voice signal to determine a lamp device to be controlled, and to determine a control intent of the user with respect to the determined lamp device, and a controller to control the lamp device, based on the determined control intent of the user.

A cloud-integrated, AI-powered smart speaker for language learning, which includes the following: A microphone array for speech capture; ◯ an on-device AI module with a Neural Processing Unit (NPU) or Tensor Processing Unit (TPU) for real-time speech analysis; • Wi-Fi and 5G connectivity for secure data synchronization with cloud servers; ◯ a cloud-based AI engine that uses serverless computing services to trigger AI models for advanced language assessment and adaptive learning; ◯ a cloud storage system with relational databases for structured data, such as user profiles and progress metrics, and object storage for unstructured data, such as audio recordings, secured with AES-256 encryption and RBAC for data protection; ◯ a true-to-life speaker for AI-generated speech output; ◯ a screen (OLED / E-Ink) for text corrections and real-time lesson guidance; ◯ Touch and gesture sensors for user interaction; ◯ A battery module with USB-C charging function for portability.

The invention relates to the technical field of artificial intelligence and multimedia, and particularly discloses a video generation method based on voice analysis, and the method comprises the following steps: analyzing an input voice, and extracting a multi-modal voice feature; inputting the multi-modal speech features into a pre-trained scene association model, and outputting a scene label set; on the basis of dialect features in the input voice, region categories are recognized through a dialect classifier, and a corresponding visual element library is loaded from a culture database according to the region categories; selecting a scene template according to scene type labels in the scene label set, and selecting a character action template in combination with emotion type labels and interaction object relation labels; and calculating time sequence distribution of the video elements based on the speech speed change parameters, and rendering the scene template, the character action template and the rhythm of the input speech according to the time sequence distribution through a time sequence alignment algorithm to generate a target video. The method can improve the accuracy of the video generated based on the voice.

The present application discloses a healthy elderly care system, method, storage medium and computer program product, which relates to the field of elderly care service technology. The healthy elderly care system includes a user information collection module for collecting user voice information and user visual information, a voice analysis agent for performing voice analysis on user voice information, a visual analysis agent for performing visual analysis on user visual information, a mental health agent for performing mental health analysis based on the voice analysis results and the visual analysis results, a central control agent for generating digital human interaction information by integrating the analysis results of each agent, and a digital human interaction module for outputting digital human interaction information. The present application can effectively monitor and improve the mental health of the elderly.