317 results about "Voice analysis" patented technology

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 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 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.

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 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 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.

The invention discloses an auditory-based humanoid robot control method and system, and relates to the technical field of voice analysis, and the method comprises the steps: analyzing the noise condition of a voice signal and the position information of a starting person, carrying out the denoising of the voice signal according to the noise condition and the position information of the starting person, specifically enhancing the voice signal, and effectively removing the noise. The reliability of voice signal data is improved, and a basis is provided for subsequent voice analysis and recognition. Segmenting the voice signal to obtain a plurality of voice signal segments, analyzing the association degree of the text content segments, and associating the plurality of text content segments to obtain the semantic content. The voice is segmented through the characteristics of the voice signal, and text content association is carried out according to the association condition of the text content segments to obtain accurate semantics, so that the recognition capability of the robot on long voice is improved. The precision and effect of robot control are improved, and the command execution stability of the robot is ensured.

The invention relates to the field of voice analysis, in particular to a robot control method based on voice analysis, and the method comprises the steps: obtaining image information in a space region where a target robot is located, determining semantic tags, determining a potential association semantic tag group, and screening out a semantic guiding corpus group for the target robot; when voice control data is received, instruction fuzzy parameters of the voice control data are determined so as to judge instruction fuzzy tendency, optimization is carried out on the voice control data with the instruction fuzzy tendency, specifically, confidence centralized clusters and semantic discrete clusters are determined, semantic expansion is carried out on the semantic discrete clusters, and then an expansion text is obtained; and screening the expanded text based on the semantic oriented corpus group to obtain a confidence instruction text. According to the method, the semantic oriented corpus group is constructed in combination with the image information, the analysis of the voice control data with the instruction fuzzy tendency is guided, the analysis accuracy of the voice control data under the semantic fuzzy condition is improved, and the control instruction recognition precision is ensured.

The invention discloses an intelligent interaction method and system for a meta-universe scene, and relates to the technical field of meta-universe scene interaction. The method comprises the following steps: acquiring scene interaction information and performing information analysis to obtain a voice analysis result, an action analysis result and a face analysis result; performing multi-modal sentiment analysis based on an analysis result to obtain a sentiment intention of the user; interacting with the user according to the emotional intention to obtain first interaction feedback information; acquiring a scene interaction log and performing log analysis to obtain an interaction recommendation result; interacting with the user according to the interaction recommendation result to obtain second interaction feedback information; and comprehensively analyzing the interaction feedback information and updating and optimizing the interaction process. According to the method, from two perspectives of scene interaction information and scene interaction logs, emotional intentions of users are obtained by adopting multiple technologies such as deep learning and neural networks, so that the accuracy of results, the usability and selectivity of interaction and the experience effect of the users are improved to a great extent.

The invention relates to a gas cylinder filling method, an early warning method, an assessment method, a system and a medium in the technical field of industrial safety production. The gas cylinder filling safety assessment method based on voice analysis comprises the following steps: acquiring acoustic data of an operator; and analyzing the acoustic data and calculating to obtain a knowledge proficiency score Spro. And acoustic data are extracted, and a psychological quality score Semo is obtained through calculation. Collecting motion posture data of the gas cylinder and calculating to obtain an operation stability score Ssta; and carrying out weighted fusion on the Stro, the Semo and the Ssta to obtain an assessment score Stotal. And setting a score line based on the assessment requirement, and if the Stotal is greater than or equal to the score line, determining that the operator passes the assessment. According to the invention, through innovative multi-mode assessment, the ability of the operator is changed from feeling-based ability to data-based ability, the final result can be known, and the specific weak link can be known according to the specific condition of each link, so that the psychological quality and emergency response ability of the operator can be effectively assessed.

The invention provides an embedded health management system based on voice analysis for traditional Chinese medicine diagnosis. The embedded health management system comprises a sound collection module used for collecting illness state description voice of a user and preprocessing the illness state description voice; the feature extraction module is used for carrying out analysis and feature extraction on the non-interference voice; the traditional Chinese medicine diagnosis module is used for obtaining a traditional Chinese medicine diagnosis result through a pre-training diagnosis model based on the sound features and the description symptoms of the user; the result feedback module is used for providing preliminary traditional Chinese medicine dialectical suggestions to the user on the basis of the traditional Chinese medicine diagnosis result and in combination with the traditional Chinese medicine dialectical relationship describing the symptoms; the data storage and transmission module is used for storing and transmitting voice data and a diagnosis report of a user; and the health management module is used for formulating a personalized health management scheme. The traditional Chinese medicine diagnosis theory is combined with the modern voice analysis technology and the embedded technology, a new and objective method is provided for traditional Chinese medicine diagnosis, and the accuracy and efficiency of traditional Chinese medicine diagnosis are improved.

The invention discloses a transparent HUD interaction system based on event-frame-electro-oculogram three-source fusion. The transparent HUD interaction system comprises an event camera, an electro-oculogram sensor and a frame type camera. The voice analysis module is used for collecting a voice instruction, extracting a specified interface element in the voice instruction as a voice interaction target and generating a voice confidence coefficient; the three-source fusion module is used for fusing the eye movement event flow, the eye electric signal and the eye image frame to obtain a fixation vector; the prediction module is used for predicting a gaze vector and gaze confidence at the next moment according to the gaze vector sequence in the recent preset time period; the interaction target confirmation module is used for acquiring a sight line interaction target, and confirming the interaction target when the sight line interaction target is consistent with the voice interaction target and the product of the voice confidence coefficient and the gaze confidence coefficient is greater than or equal to a preset gating threshold value; and the transparent display module is used for projecting the interactive interface on a vehicle-mounted transparent interface and displaying the real-time interactive information. The method is higher in recognition accuracy.

The invention relates to the field of speech analysis, and discloses a natural sound interference stripping algorithm and an application thereof in noise monitoring, which are used for efficiently and accurately stripping interference components in a target speech signal in a complex natural sound environment. Comprising the following steps: synchronously acquiring an environmental sound signal by using a spatially distributed microphone array, generating an original mixed voice signal with spatial coherence, performing real-time fractional order differential processing, strengthening resonance characteristics, realizing spatial separation of a voice guided wave mode and an interference radiation mode through real-time phase analysis, and extracting an interference radiation mode component. And reconstructing a time domain interference waveform, and outputting a pure target voice signal according to the original mixed voice signal and the reconstructed interference waveform. The system has the functions of residual interference sound energy recovery, equipment vibration suppression, environment sudden change monitoring, system resetting, bimodal output and the like, the stability, reliability and practicability of the system are effectively improved, and pure voice can be accurately extracted in a complex environment.

The invention relates to a self-adaptive voice semantic communication method based on hierarchy time sequence importance, which belongs to the field of voice analysis, and comprises the following steps: a sending end performs priority division on a discrete feature matrix according to hierarchy and time sequence attributes of voice features, and screens the features according to importance scores in a feature matrix packaging and selecting link; the method comprises the following steps: interacting with wireless communication through a channel adaptive scheduling module, introducing a channel feedback mechanism, and dynamically adjusting transmission power and a resource allocation strategy by sensing current channel state information; and after completing signal demodulation, a receiving end inputs the acquired sparse feature flow into a voice restoration module, and globally reconstructs the received features by using voice priori knowledge of deep pre-training. According to the method, a hierarchical speech feature extraction technology based on a discrete codebook and a generative semantic repair technology are combined, so that the speech word error rate in a severe channel environment is reduced to the maximum extent, and the semantic intelligibility of a receiving end is improved.

The present invention discloses a voice analysis method for key feature parameters of freezing gait symptoms in Parkinson's disease based on the AdaBoost algorithm. Step 1: Collect continuous and stable vowels of Parkinson's disease patients and record whether the Parkinson's disease patients have freezing gait symptoms; Step 2: Perform denoising preprocessing on the voice signals and remove the silent segments; Step 3: Extract various voice features; Step 4: Use the CART algorithm to perform feature selection on the original features and screen out the key features that can effectively represent the information of freezing gait symptoms; Step 5: Train the AdaBoost model; Step 6: Input the feature vector of the voice to be measured into the model to obtain the key feature parameters of the freezing gait symptoms in Parkinson's disease. The present invention uses the AdaBoost algorithm to analyze the freezing gait symptoms in Parkinson's disease, improves the model accuracy by using ensemble learning, and reduces the cost of early analysis of the freezing gait symptoms in Parkinson's disease.