Rehabilitation plan generation method and device based on aphasia patient, equipment and medium

Abstract

The invention discloses a rehabilitation plan generation method and device based on aphasia patients, equipment and a medium. The method comprises the steps of obtaining an original voice signal of an aphasia patient; identifying the original voice signal to obtain original text information corresponding to the original voice signal; obtaining a rehabilitation target corresponding to the aphasia patient, extracting target text information from the original text information according to the rehabilitation target, and converting the target text information into voice information; performing feature extraction on the target text information and the voice information to obtain a language feature corresponding to the target text information and a voice feature corresponding to the voice information; and generating a rehabilitation plan corresponding to the aphasia patient according to the language features and the voice features. Therefore, the aphasia patient can customize the personalized rehabilitation scheme at any time in any environment, and the accuracy and convenience of the scheme are greatly improved.

Description

Technical Field

[0001] The present application relates to speech processing technology, which is applied in the medical field, and in particular to a method, device, equipment and medium for generating a rehabilitation plan for aphasic patients. Background Art

[0002] In the field of speech technology, there are already some similar products or systems used for aphasia rehabilitation, such as Lingraph i ca, Constant Therapy and Tactus Therapy.

[0003] However, existing aphasia rehabilitation products or systems have some defects or shortcomings. First, these products or systems usually adopt standardized rehabilitation plans and cannot be customized according to the individual needs of patients. Secondly, these systems usually require rehabilitation training in specific medical institutions or professional institutions, resulting in poor convenience. In addition, some aphasia rehabilitation systems also have problems such as unstable rehabilitation training effects and incomplete data recording. Summary of the invention

[0004] The present application provides a method, device, equipment and medium for generating a rehabilitation plan for aphasia patients, aiming to solve the problems that existing aphasia rehabilitation products or systems cannot be customized according to the individual needs of patients, are less convenient, have unstable rehabilitation training effects and incomplete data recording.

[0005] In a first aspect, the present application provides a method for generating a rehabilitation plan for an aphasia patient, comprising:

[0006] Obtaining original speech signals from patients with aphasia;

[0007] Recognize the original voice signal and obtain the original text information corresponding to the original voice signal;

[0008] Obtaining rehabilitation goals corresponding to aphasia patients, extracting target text information from original text information according to the rehabilitation goals, and converting the target text information into speech information;

[0009] Extracting features of the target text information and the voice information respectively to obtain language features corresponding to the target text information and voice features corresponding to the voice information;

[0010] Generate corresponding rehabilitation plans for aphasia patients based on language features and speech features.

[0011] In some embodiments, recognizing an original speech signal includes: amplifying the original speech signal; performing speech recognition on the amplified original speech signal to obtain tone information and context information corresponding to the original speech signal; and repairing the abnormal tone if it is determined based on the context information that the tone information contains an abnormal tone.

[0012] In some embodiments, obtaining a rehabilitation goal corresponding to an aphasia patient includes: parsing an original speech signal to obtain an abnormal signal that cannot be recognized in the original speech signal; determining an aphasia type corresponding to the aphasia patient based on the abnormal signal, and using the aphasia type as a rehabilitation goal.

[0013] Exemplarily, extracting target text information from original text information according to rehabilitation goals includes: obtaining aphasia tones corresponding to aphasia types; and extracting target text information corresponding to aphasia tones from original text information.

[0014] In some embodiments, a rehabilitation plan corresponding to an aphasia patient is generated based on language features and speech features, including: generating an oral practice plan corresponding to an aphasia patient based on language features; generating a listening practice plan corresponding to an aphasia patient based on speech features; generating a rehabilitation plan based on the oral practice plan and the listening practice plan, so as to provide rehabilitation training for the aphasia patient based on the oral practice plan and the listening practice plan.

[0015] In some embodiments, after generating a rehabilitation plan corresponding to an aphasia patient based on language features and speech features, it also includes: conducting rehabilitation training on the aphasia patient according to the rehabilitation plan; obtaining the rehabilitation progress of the aphasia patient, and optimizing the rehabilitation plan based on the rehabilitation progress; the rehabilitation progress includes at least the duration, frequency and effect of the rehabilitation training.

[0016] In some embodiments, feature extraction is performed on target text information and voice information respectively, including: inputting the target text information and voice information into a preset natural language processing module respectively, the natural language processing module recognizes and outputs a text feature vector and a voice feature vector; and constructing language features based on the text feature vector and constructing voice features based on the voice feature vector.

[0017] In a second aspect, the present application provides a rehabilitation plan generating device, comprising:

[0018] A signal acquisition module, used to acquire the original speech signal of the aphasia patient;

[0019] A speech recognition module, used to recognize the original speech signal and obtain original text information corresponding to the original speech signal;

[0020] A target acquisition module, used for acquiring a rehabilitation target corresponding to the aphasia patient, extracting target text information from the original text information according to the rehabilitation target, and converting the target text information into voice information;

[0021] A feature extraction module, used to extract features from the target text information and the voice information respectively, to obtain language features corresponding to the target text information and voice features corresponding to the voice information;

[0022] A plan generating module is used to generate a rehabilitation plan corresponding to the aphasia patient according to the language features and the speech features.

[0023] In a third aspect, the present application further provides a computer device, including:

[0024] Memory and processor;

[0025] The memory is used to store computer programs;

[0026] The processor is used to execute the computer program and implement the steps of the method for generating a rehabilitation plan for aphasic patients as described in the first aspect above when executing the computer program.

[0027] In a fourth aspect, the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to implement the steps of the method for generating a rehabilitation plan for aphasia patients as described in the first aspect above.

[0028] The present application discloses a method, device, equipment and medium for generating a rehabilitation plan based on aphasia patients. First, the original voice signal of the aphasia patient is obtained; then, the original voice signal is recognized to obtain the original text information corresponding to the original voice signal; then, the rehabilitation goal corresponding to the aphasia patient is obtained, and the target text information is extracted from the original text information according to the rehabilitation goal, and the target text information is converted into voice information; further, the target text information and voice information are respectively extracted to obtain the language features corresponding to the target text information and the voice features corresponding to the voice information; finally, the rehabilitation plan corresponding to the aphasia patient is generated according to the language features and the voice features. This enables aphasia patients to customize personalized rehabilitation plans at any time in any environment, greatly improving the accuracy and convenience of the plans.

[0029] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 is a schematic flow chart of the steps of a method for generating a rehabilitation plan for aphasic patients provided in one embodiment of the present application;

[0032] Figure 2 is a schematic flow chart of the steps of an original speech signal recognition method provided by an embodiment of the present application;

[0033] Figure 3 is a schematic flow chart of the steps of a method for generating a rehabilitation plan provided in an embodiment of the present application;

[0034] Figure 4 is a structural schematic diagram of a rehabilitation plan generating device provided in an embodiment of the present application;

[0035] Figure 5 It is a schematic block diagram of the structure of a computer device provided in one embodiment of the present application.

[0036] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0038] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0039] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0040] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0041] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0042] In the field of speech technology, there are already some similar products or systems used for aphasia rehabilitation, such as Lingraph ica, Constant Therapy and Tactus Therapy.

[0043] However, existing aphasia rehabilitation products or systems have some defects or shortcomings. First, these products or systems usually adopt standardized rehabilitation plans and cannot be customized according to the individual needs of patients. Secondly, these systems usually require rehabilitation training in specific medical institutions or professional institutions, resulting in poor convenience. In addition, some aphasia rehabilitation systems also have problems such as unstable rehabilitation training effects and incomplete data recording.

[0044] To solve the above problems, please refer to Figure 1 , Figure 1 It is a schematic flow chart of a method for generating a rehabilitation plan for aphasic patients provided in one embodiment of the present application.

[0045] The method for generating a rehabilitation plan based on aphasia patients can be implemented by a computer device, which can be deployed on a single server or a server cluster, or can be deployed on a handheld terminal, a notebook computer, a wearable device, a robot, etc.

[0046] The provided method can be applied in the medical field to provide aphasia patients with personalized rehabilitation plans that can be generated in any environment.

[0047] like Figure 1 As shown, the method for generating a rehabilitation plan for aphasic patients provided in this embodiment includes steps S101 to S105. The details are as follows:

[0048] S101. Obtain original speech signals from an aphasia patient.

[0049] Specifically, by collecting the original voice signals of aphasia patients in any scenario, such as when aphasia patients are in the hospital, their original voice signals can be collected through a dedicated microphone, and when aphasia patients are at home or in any other scenario, the original voice signals of aphasia patients can be collected through the audio input module of any terminal such as mobile phones and computers. Furthermore, the provided method can collect the original voice signals of multiple aphasia patients at any time and formulate corresponding rehabilitation plans. The convenience and flexibility of the treatment of aphasia patients have been improved.

[0050] In some embodiments, the obtaining of the original voice signal of the aphasia patient includes: playing a preset prompt voice to the aphasia patient, and obtaining the original voice signal of the aphasia patient's answer based on the prompt voice.

[0051] Furthermore, the provided method can test the response content of aphasic patients to preset prompt voices to determine whether aphasic patients have hearing impairments, and can also standardize the design of rehabilitation plans.

[0052] S102. Recognize the original voice signal and obtain original text information corresponding to the original voice signal.

[0053] Specifically, by recognizing the original voice signal of the aphasia patient, converting the voice signal into text form, and obtaining the corresponding original text information, it is possible to analyze the content of the original voice signal input by the aphasia patient to prepare for the generation of a rehabilitation plan.

[0054] In some embodiments, please refer to Figure 2 , Figure 2 The provided original speech signal recognition method includes steps S102a to S102c.

[0055] S102a. Amplify the original speech signal.

[0056] S102b. Perform speech recognition on the amplified original speech signal to obtain tone information and context information corresponding to the original speech signal.

[0057] S102c. If it is determined according to the context information that there is an abnormal tone in the tone information, the abnormal tone is repaired.

[0058] Since the original speech signal of aphasia patients may have problems such as being too quiet or blurred, which may affect text conversion. Therefore, the method provided first amplifies the original speech signal, then identifies the corresponding tone information and context information of the amplified original speech signal, and then combines the context information to determine whether there is an error in each tone corresponding to the original speech signal. For example, if (……wōgēnníshuō……) appears in the confirmed text, it can be confirmed that the tone errors of ō and í are abnormal tones and need to be corrected to ǒ and ǐ. The above method can then repair the abnormal tones in the original speech signal to ensure the accuracy of the converted text information content.

[0059] S103. Obtain rehabilitation goals corresponding to aphasia patients, extract target text information from original text information according to the rehabilitation goals, and convert the target text information into voice information.

[0060] Specifically, the rehabilitation goal of aphasia can be determined based on the case information corresponding to the aphasia patient, or it can be determined based on the original voice signal. The embodiment of the present application does not limit the method for obtaining the rehabilitation goal. At the same time, after confirming the rehabilitation goal corresponding to the aphasia patient, the provided method extracts the target text information from the original text information based on the rehabilitation goal, and then can convert the target text information used for the rehabilitation of the aphasia patient into voice information for training. At the same time, the rehabilitation text information and voice information corresponding to the rehabilitation goal can also be extracted from the preset rehabilitation database for subsequent determination of the rehabilitation plan.

[0061] In some embodiments, obtaining a rehabilitation goal corresponding to an aphasia patient includes: parsing an original speech signal to obtain an abnormal signal that cannot be recognized in the original speech signal; determining an aphasia type corresponding to the aphasia patient based on the abnormal signal, and using the aphasia type as a rehabilitation goal.

[0062] By analyzing abnormal signals whose contents cannot be identified in the original speech signals, the abnormal signals may be signals with any abnormalities such as unclear content / abnormal tone, and then the aphasia type corresponding to the aphasia patient can be determined based on the abnormal signals, such as any aphasia type such as inability to pronounce vowels / inability to pronounce retroflex syllables / inability to read syllables in a connected manner, so as to determine the rehabilitation plan for the aphasia patient in a targeted manner and improve the accuracy of the generated rehabilitation plan.

[0063] Exemplarily, extracting target text information from original text information according to rehabilitation goals includes: obtaining aphasia tones corresponding to aphasia types; extracting target text information corresponding to aphasia tones from original text information. Thus, the provided method can accurately extract target text information for rehabilitation training from the converted original text information.

[0064] S104. Perform feature extraction on the target text information and the voice information respectively to obtain language features corresponding to the target text information and voice features corresponding to the voice information.

[0065] Specifically, the provided method can extract language features and speech features of aphasia patients by performing feature extraction on target text information and speech information, so as to confirm the feature types that need to be targeted for the rehabilitation plan generated therefor.

[0066] In some embodiments, feature extraction is performed on target text information and voice information respectively, including: inputting the target text information and voice information into a preset natural language processing module respectively, the natural language processing module identifies and outputs a text feature vector and a voice feature vector; and forming a language feature according to the text feature vector and forming a voice feature according to the voice feature vector. The provided method can extract language features and voice features based on the natural language processing module.

[0067] S105. Generate a rehabilitation plan corresponding to aphasia patients based on language features and speech features.

[0068] Specifically, by generating a personalized rehabilitation plan for aphasia patients based on their language and voice features, rehabilitation training can be performed on aphasia patients in any scenario based on the rehabilitation plan. This enables aphasia patients to customize personalized rehabilitation plans at any time in any environment, greatly improving the accuracy and convenience of the plans.

[0069] In some embodiments, please refer to Figure 3 , generating a rehabilitation plan corresponding to an aphasia patient according to the language features and the speech features, including steps S105a to S105c.

[0070] like Figure 3 The steps S105a to S105c include:

[0071] S105a. Generate an oral practice plan corresponding to aphasia patients based on language features.

[0072] S105b. Generate a listening practice plan corresponding to aphasia patients based on speech features.

[0073] S105c. Generate a rehabilitation plan according to the oral practice plan and the listening practice plan, so as to conduct rehabilitation training for the aphasia patient according to the oral practice plan and the listening practice plan.

[0074] The provided method generates a corresponding oral practice plan based on the language features of aphasic patients. For example, based on the language features, it is confirmed that aphasic patients have great obstacles in pronouncing some syllables, and a targeted oral practice plan is generated. Based on the voice features, it is confirmed that aphasic patients have great obstacles in listening to some syllables, and then a corresponding voice practice plan is generated. The provided method can provide targeted training for aphasic patients based on their language and voice obstacles, thereby improving the effect of rehabilitation training.

[0075] In some embodiments, after generating a rehabilitation plan corresponding to an aphasia patient based on language features and speech features, it also includes: conducting rehabilitation training on the aphasia patient according to the rehabilitation plan; obtaining the rehabilitation progress of the aphasia patient, and optimizing the rehabilitation plan based on the rehabilitation progress; the rehabilitation progress includes at least the duration, frequency and effect of the rehabilitation training.

[0076] The method provided in the present application determines the corresponding rehabilitation plan for the aphasia patient, conducts targeted rehabilitation training for the patient, and records the rehabilitation progress such as the duration, frequency and effect of the rehabilitation training of the aphasia patient. The rehabilitation plan of the aphasia patient can be optimized through computer equipment, or the attending physician of the aphasia patient can adjust the rehabilitation plan. The provided method can assist doctors in providing targeted treatment to patients, thereby reducing the workload of doctors and improving the efficiency of treatment.

[0077] Compared with traditional aphasia rehabilitation treatment methods, the method provided by the present invention has the following advantages:

[0078] Personalized customization: According to the patient's voice and language characteristics, a rehabilitation plan is tailored for the patient to improve the rehabilitation effect.

[0079] Anytime, anywhere: Patients can use the system for rehabilitation training at home, which is convenient and fast.

[0080] Data support: The system can record the patient's rehabilitation progress, provide data support to doctors, and optimize rehabilitation plans.

[0081] Various rehabilitation training: The system provides a variety of rehabilitation training, including pronunciation exercises, language comprehension exercises, etc., to provide patients with comprehensive rehabilitation support.

[0082] See also Figure 4 As shown, Figure 4: is a schematic diagram of the structure of the rehabilitation plan generation device 200 provided in an embodiment of the present application. The rehabilitation plan generation device 200 is used to execute the steps of the rehabilitation plan generation method based on aphasia patients shown in the above embodiments. The rehabilitation plan generation device 200 can be a single server or a server cluster, or the rehabilitation plan generation device 200 can be a terminal, which can be a handheld terminal, a laptop computer, a wearable device or a robot, etc.

[0083] like Figure 4 As shown, the rehabilitation plan generating device 200 includes:

[0084] The signal acquisition module 201 is used to acquire the original speech signal of the aphasia patient;

[0085] The speech recognition module 202 is used to recognize the original speech signal and obtain the original text information corresponding to the original speech signal;

[0086] A target acquisition module 203 is used to acquire a rehabilitation target corresponding to the aphasia patient, extract target text information from the original text information according to the rehabilitation target, and convert the target text information into voice information;

[0087] A feature extraction module 204 is used to extract features from the target text information and the voice information respectively, and obtain language features corresponding to the target text information and voice features corresponding to the voice information;

[0088] The plan generating module 205 is used to generate a rehabilitation plan corresponding to the aphasia patient according to the language features and the speech features.

[0089] In some embodiments, the speech recognition module 202 is also used to amplify the original speech signal; perform speech recognition on the amplified original speech signal to obtain the tone information and context information corresponding to the original speech signal; if it is determined based on the context information that there is an abnormal tone in the tone information, repair the abnormal tone.

[0090] In some embodiments, the target acquisition module 203 is used to parse the original speech signal and obtain the abnormal signal that cannot be recognized in the original speech signal; determine the aphasia type corresponding to the aphasia patient according to the abnormal signal, and use the aphasia type as a rehabilitation target.

[0091] Exemplarily, the target acquisition module 203 is further configured to acquire the aphasia tone corresponding to the aphasia type; and extract the target text information corresponding to the aphasia tone from the original text information.

[0092] In some embodiments, the plan generation module 205 is also used to generate an oral practice plan corresponding to aphasia patients according to language features; generate a listening practice plan corresponding to aphasia patients according to speech features; generate a rehabilitation plan according to the oral practice plan and the listening practice plan, so as to perform rehabilitation training for aphasia patients according to the oral practice plan and the listening practice plan.

[0093] In some embodiments, after generating a rehabilitation plan corresponding to an aphasia patient based on language features and speech features, the device further includes: a plan optimization module, used to perform rehabilitation training on the aphasia patient according to the rehabilitation plan; obtain the rehabilitation progress of the aphasia patient, and optimize the rehabilitation plan based on the rehabilitation progress; the rehabilitation progress includes at least the duration, frequency and effect of the rehabilitation training.

[0094] In some embodiments, the feature extraction module 204 is also used to input the target text information and voice information into a preset natural language processing module respectively, and the natural language processing module recognizes and outputs text feature vectors and voice feature vectors; language features are formed according to the text feature vectors, and voice features are formed according to the voice feature vectors.

[0095] It should be noted that technical personnel in the relevant field can clearly understand that, for the convenience and conciseness of description, the specific working processes of the rehabilitation plan generating device and each module described above can refer to the corresponding processes in the embodiments of the rehabilitation plan generating method based on aphasia patients described in the above embodiments, and will not be repeated here.

[0096] The above-mentioned method for generating a rehabilitation plan based on aphasia patients can be implemented in the form of a computer program. The computer program can be used in Figure 4 Run on the device shown.

[0097] See also Figure 5 , Figure 5 1 is a schematic block diagram of the structure of a computer device provided in an embodiment of the present application. The computer device includes a processor, a memory and a network interface connected via a device bus, wherein the memory may include a storage medium and an internal memory.

[0098] The storage medium can store an operating device and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any method for generating a rehabilitation plan based on an aphasia patient.

[0099] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0100] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for generating a rehabilitation plan based on an aphasia patient.

[0101] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0102] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0103] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0104] Obtaining original speech signals from patients with aphasia;

[0105] Recognize the original voice signal and obtain the original text information corresponding to the original voice signal;

[0106] Obtaining rehabilitation goals corresponding to aphasia patients, extracting target text information from original text information according to the rehabilitation goals, and converting the target text information into speech information;

[0107] Extracting features of the target text information and the voice information respectively to obtain language features corresponding to the target text information and voice features corresponding to the voice information;

[0108] Generate corresponding rehabilitation plans for aphasia patients based on language features and speech features.

[0109] In some embodiments, recognizing an original speech signal includes: amplifying the original speech signal; performing speech recognition on the amplified original speech signal to obtain tone information and context information corresponding to the original speech signal; and repairing the abnormal tone if it is determined based on the context information that the tone information contains an abnormal tone.

[0110] In some embodiments, obtaining a rehabilitation goal corresponding to an aphasia patient includes: parsing an original speech signal to obtain an abnormal signal that cannot be recognized in the original speech signal; determining an aphasia type corresponding to the aphasia patient based on the abnormal signal, and using the aphasia type as a rehabilitation goal.

[0111] Exemplarily, extracting target text information from original text information according to rehabilitation goals includes: obtaining aphasia tones corresponding to aphasia types; and extracting target text information corresponding to aphasia tones from original text information.

[0112] In some embodiments, a rehabilitation plan corresponding to an aphasia patient is generated based on language features and speech features, including: generating an oral practice plan corresponding to an aphasia patient based on language features; generating a listening practice plan corresponding to an aphasia patient based on speech features; generating a rehabilitation plan based on the oral practice plan and the listening practice plan, so as to provide rehabilitation training for the aphasia patient based on the oral practice plan and the listening practice plan.

[0113] In some embodiments, after generating a rehabilitation plan corresponding to an aphasia patient based on language features and speech features, it also includes: conducting rehabilitation training on the aphasia patient according to the rehabilitation plan; obtaining the rehabilitation progress of the aphasia patient, and optimizing the rehabilitation plan based on the rehabilitation progress; the rehabilitation progress includes at least the duration, frequency and effect of the rehabilitation training.

[0114] In some embodiments, feature extraction is performed on target text information and voice information respectively, including: inputting the target text information and voice information into a preset natural language processing module respectively, the natural language processing module recognizes and outputs a text feature vector and a voice feature vector; and constructing language features based on the text feature vector and constructing voice features based on the voice feature vector.

[0115] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement the steps of the method for generating a rehabilitation plan for aphasia patients provided in the above embodiments of the present application.

[0116] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the computer device.

[0117] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for generating a rehabilitation plan for aphasic patients, characterized in that: include: Obtaining original speech signals from patients with aphasia; Recognize the original voice signal to obtain original text information corresponding to the original voice signal; Acquiring a rehabilitation goal corresponding to the aphasia patient, extracting target text information from the original text information according to the rehabilitation goal, and converting the target text information into voice information; Performing feature extraction on the target text information and the voice information respectively to obtain language features corresponding to the target text information and voice features corresponding to the voice information; A rehabilitation plan corresponding to the aphasia patient is generated according to the language features and the speech features.

2. The method according to claim 1, characterized in that The identifying of the original voice signal comprises: amplifying the original speech signal; Performing speech recognition on the amplified original speech signal to obtain tone information and context information corresponding to the original speech signal; If it is determined according to the context information that there is an abnormal tone in the tone information, the abnormal tone is repaired.

3. The method according to claim 1, characterized in that Obtaining the rehabilitation goals corresponding to the aphasia patient, including: Analyzing the original voice signal to obtain an abnormal signal that cannot be identified in the original voice signal; The aphasia type corresponding to the aphasia patient is determined according to the abnormal signal, and the aphasia type is used as the rehabilitation target.

4. The method according to claim 3, characterized in that The step of extracting target text information from the original text information according to the rehabilitation goal includes: Obtaining the aphasia tone corresponding to the aphasia type; The target text information corresponding to the aphonic tone is extracted from the original text information.

5. The method according to claim 1, characterized in that Generating a rehabilitation plan corresponding to the aphasia patient according to the language features and the speech features includes: generating a corresponding oral practice plan for the aphasia patient according to the language features; generating a listening practice plan corresponding to the aphasia patient according to the speech features; The rehabilitation plan is generated according to the oral practice plan and the listening practice plan, so as to perform rehabilitation training on the aphasia patient according to the oral practice plan and the listening practice plan.

6. The method according to claim 1, characterized in that After generating a rehabilitation plan corresponding to the aphasia patient according to the language features and the speech features, the method further includes: performing rehabilitation training on the aphasia patient according to the rehabilitation plan; Obtain the rehabilitation progress of the aphasia patient, and optimize the rehabilitation plan according to the rehabilitation progress; the rehabilitation progress at least includes the duration, frequency and effect of the rehabilitation training.

7. The method according to claim 1, characterized in that The extracting features of the target text information and the voice information respectively comprises: Inputting the target text information and the voice information into a preset natural language processing module respectively, and the natural language processing module recognizes and outputs the text feature vector and the voice feature vector; The language feature is formed according to the text feature vector, and the voice feature is formed according to the voice feature vector.

8. A rehabilitation plan generating device, characterized in that: include: A signal acquisition module, used to acquire the original speech signal of the aphasia patient; A speech recognition module, used to recognize the original speech signal and obtain original text information corresponding to the original speech signal; A target acquisition module, used for acquiring a rehabilitation target corresponding to the aphasia patient, extracting target text information from the original text information according to the rehabilitation target, and converting the target text information into voice information; A feature extraction module, used to extract features from the target text information and the voice information respectively, to obtain language features corresponding to the target text information and voice features corresponding to the voice information; A plan generating module is used to generate a rehabilitation plan corresponding to the aphasia patient according to the language features and the speech features.

9. A computer device, characterized in that: The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is used to execute the computer program and implement the method for generating a rehabilitation plan for an aphasia patient as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the method for generating a rehabilitation plan for an aphasic patient according to any one of claims 1 to 7.

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