A language interaction processing method based on AIGC

Abstract

The present invention provides a language interaction processing method based on AIGC, which belongs to the field of data processing technology, and specifically includes: dividing interaction data with consistent operation targets into the same interaction data group, determining the number of identification processing times and usage occasions through identification processing data of interaction data of different interaction data groups, and determining the necessity of processing different interaction data in combination with identification deviation data and identification failure data of different interaction data, determining the necessity of comprehensive processing of different interaction data groups according to the necessity of processing different interaction data of different interaction data groups, determining the generation processing strategy of local identification processing libraries of different interaction data groups by using the comprehensive processing necessity and network connection stability, and processing the local identification processing libraries of different interaction data groups based on the generation processing strategy and the AIGC model, thereby ensuring the accuracy of local interaction processing recognition.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a language interaction processing method based on AIGC. Background Art

[0002] With the rapid development of artificial intelligence technology and AIGC (generative artificial intelligence), more and more smart vehicles are integrated with intelligent language interaction assistants, which has gradually transformed the control of vehicle functions from manual to voice interaction, greatly improving user convenience. However, at the same time, how to improve the recognition accuracy and interaction authenticity in the language interaction process has also become a technical problem that needs to be solved urgently.

[0003] In order to solve the above technical problems, the existing technical solution in the invention patent application CN202311517376.5 "Virtual Reality Human-Computer Interaction Method and System Based on Artificial Intelligence" converts the voice control signal into voice control text at the back end, and introduces semantic understanding and processing technology to perform semantic recognition of the voice control text. However, it is not difficult to find through analysis that there are the following technical problems:

[0004] In certain situations, such as changing the navigation destination while driving, operations such as changing the navigation destination during driving require extremely high real-time and accuracy in recognition processing. Therefore, if the local recognition model library cannot be updated according to the usage of different operation instructions, once there is a problem with the network, the accuracy and real-time processing of operation instructions in certain special situations cannot be guaranteed.

[0005] In view of the above technical problems, the present invention provides a language interaction processing method based on AIGC. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a language interaction processing method based on AIGC is provided.

[0008] A language interaction processing method based on AIGC, characterized by comprising:

[0009] S1: when it is determined based on the driving data of different historical driving routes and the network connection data that the network connection stability of the vehicle does not meet the requirements, proceed to the next step;

[0010] S2 divides the interaction data with the same operation target into the same interaction data group, determines the number of identification processing times and usage occasions through the identification processing data of the interaction data of different interaction data groups, and determines the necessity of processing different interaction data in combination with the identification deviation data and the identification failure data of different interaction data. When there is no interaction data in the interaction data group whose processing necessity does not meet the requirements, proceed to the next step;

[0011] S3: determining the comprehensive processing necessity of different interactive data groups according to the processing necessity of different interactive data of different interactive data groups, and when it is determined based on the comprehensive processing necessity that the interactive data group belongs to the local processing group, proceeding to the next step;

[0012] S4 utilizes the comprehensive processing necessity and the network connection stability to determine the generation processing strategy of the local recognition processing library for different interaction data groups, and processes the local recognition processing library for different interaction data groups based on the generation processing strategy and the AIGC model.

[0013] The beneficial effects of the present invention are:

[0014] 1. The necessity of processing different interactive data is determined by using the recognition deviation data and recognition failure data of the interactive data of different interactive data groups. This not only takes into account the emergence of technical problems such as the recognition deviation of the interactive data of the interactive data group, which causes the recognition processing error to be difficult to meet the requirements, but also further combines the differences in the requirements for real-time use processing of the interactive data of the interactive data group due to differences in the number of interactive recognitions and usage scenarios, thereby achieving accurate evaluation of the necessity of processing interactive data from multiple angles.

[0015] 2. The generation and processing strategies of the local recognition processing libraries for different interaction data groups are determined by utilizing the comprehensive processing necessity and the stability of the network connection. This enables accurate evaluation of the generation and processing strategies of the local recognition processing libraries for interaction data groups from multiple angles, which not only ensures the reliability requirements of local recognition processing for different interaction data groups, but also avoids the technical problem of wasting storage space due to the large amount of data in this recognition processing library.

[0016] A further technical solution is that the travel data of the historical travel route includes the number of times the historical travel route was traveled and the travel duration.

[0017] A further technical solution is that the network connection data of the historical driving route includes the number of locations with suspected abnormalities in the network of the historical driving route and the number of identification failures of interaction data of different locations with suspected abnormalities in the network.

[0018] A further technical solution is that, when there are identification failures at the location, the location is determined to be a location where there is a suspected abnormality in the network.

[0019] A further technical solution is that when the network connection stability of the vehicle meets the requirements, there is no need to generate a local recognition processing library.

[0020] A further technical solution is that the preset processing strategy is to determine the amount of generated processing data of the local recognition processing library without data amount restriction.

[0021] A further technical solution is to process the local recognition processing library of different interaction data groups based on the generation processing strategy and the AIGC model, specifically including:

[0022] Determine the limited data amount of the local recognition processing library of the interactive data group based on the generation processing strategy;

[0023] Taking the limited data amount as a constraint condition, the AIGC model is used to generate similar interaction data of the interaction data group, and the local recognition processing library of the interaction data group is processed through the similar interaction data.

[0024] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0027] Figure 1 It is a flow chart of a language interaction processing method based on AIGC;

[0028] Figure 2 is a flow chart of a method for determining that the network connection stability of the vehicle does not meet the requirements;

[0029] Figure 3 is a flow chart of a method for determining the necessity of processing interaction data;

[0030] Figure 4 is a flow chart of a method for determining the necessity of comprehensive processing of an interactive data group;

[0031] Figure 5The present invention is a flowchart of a method for determining a generation processing strategy of a local recognition processing library for an interaction data group. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0033] The following will further elaborate from two perspectives: method-based embodiments and system-based embodiments.

[0034] Method Example

[0035] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a language interaction processing method based on AIGC is provided, which is characterized by specifically including:

[0036] S1: when it is determined based on the driving data of different historical driving routes and the network connection data that the network connection stability of the vehicle does not meet the requirements, proceed to the next step;

[0037] Furthermore, the travel data of the historical travel route includes the number of times the historical travel route was traveled and the travel duration.

[0038] Specifically, the network connection data of the historical driving route includes the number of locations where the network of the historical driving route is suspected to be abnormal and the number of identification failures of interaction data of different locations where the network is suspected to be abnormal.

[0039] Furthermore, when there are identification failures at the location, it is determined that the location is a location where a suspected abnormality exists in the network.

[0040] It should be noted that if Figure 2 As shown, determining that the network connection stability of the vehicle does not meet the requirements specifically includes:

[0041] The number of locations with suspected anomalies in the network of different historical driving routes is determined by using the network connection data of different historical driving routes, and the network anomaly values ​​of different historical driving routes are determined by combining the number of identification failures of the interaction data of different locations with suspected anomalies in the network;

[0042] Determine the number of times and the driving duration of different historical driving routes based on the driving data of different historical driving routes, and determine the weight values ​​of different historical driving routes according to the number of times and the driving duration of different historical driving routes;

[0043] The network connection stability of the vehicle is determined by using weight values ​​of different historical driving routes and network anomaly values, and is determined in combination with a preset stability threshold to determine whether the network connection stability of the vehicle meets the requirements.

[0044] Further, determining whether the network connection stability of the vehicle meets the requirement in combination with a preset stability threshold specifically includes:

[0045] When the network connection stability of the vehicle is less than the preset stability threshold, it is determined that the network connection stability of the vehicle does not meet the requirement.

[0046] It is understandable that when the network connection stability of the vehicle meets the requirements, there is no need to generate a local recognition processing library.

[0047] In another embodiment, determining that the network connection stability of the vehicle does not meet the requirement specifically includes:

[0048] Determine whether there is a historical driving route with a location where a network abnormality is suspected through network connection data of different historical driving routes, if so, proceed to the next step, if not, determine that the network connection stability of the vehicle meets the requirements;

[0049] Determine the network anomaly values ​​of different historical driving routes by the number of locations with suspected anomalies in the network of different historical driving routes and the number of identification failures of interaction data of different locations with suspected anomalies in the network, and judge whether there is a historical driving route whose network anomaly value does not meet the requirements. If so, proceed to the next step; if not, determine that the network connection stability of the vehicle meets the requirements;

[0050] The historical driving routes whose network anomaly values ​​do not meet the requirements are taken as problematic driving routes, and it is determined whether the number of the problematic driving routes meets the requirements. If so, the next step is entered; if not, it is determined that the network connection stability of the vehicle does not meet the requirements;

[0051] Determine the number of times and the driving duration of different historical driving routes based on the driving data of different historical driving routes, and determine the weight values ​​of different historical driving routes according to the number of times and the driving duration of different historical driving routes, and judge whether the sum of the weight values ​​of the problematic driving routes meets the requirements, if so, proceed to the next step, if not, determine that the network connection stability of the vehicle does not meet the requirements;

[0052] The network connection stability of the vehicle is determined by using weight values ​​of different historical driving routes and network anomaly values, and is determined in combination with a preset stability threshold to determine whether the network connection stability of the vehicle meets the requirements.

[0053] In another embodiment, determining that the network connection stability of the vehicle does not meet the requirement specifically includes:

[0054] Determine locations with suspected network anomalies through network connection data of different historical driving routes, and use them as network anomaly locations, and judge whether the number of network anomaly locations meets the requirement. If so, proceed to the next step; if not, determine that the network connection stability of the vehicle does not meet the requirement.

[0055] Determine the identification abnormality values ​​of different network abnormality locations according to the number of identification failures of the interaction data of different network abnormality locations, and judge whether the sum of the identification abnormality values ​​of the network abnormality locations meets the requirements, if so, proceed to the next step, if not, determine that the network connection stability of the vehicle does not meet the requirements;

[0056] Determine the network anomaly values ​​of different historical driving routes by the number of locations with suspected anomalies in the network of different historical driving routes and the number of identification failures of interaction data of different locations with suspected anomalies in the network, and judge whether there is a historical driving route whose network anomaly value does not meet the requirements. If so, proceed to the next step; if not, determine that the network connection stability of the vehicle meets the requirements;

[0057] Determine the number of times and the driving duration of different historical driving routes based on the driving data of different historical driving routes, and determine the weight values ​​of different historical driving routes according to the number of times and the driving duration of different historical driving routes;

[0058] The network connection stability of the vehicle is determined by using weight values ​​of different historical driving routes and network anomaly values, and is determined in combination with a preset stability threshold to determine whether the network connection stability of the vehicle meets the requirements.

[0059] S2 divides the interaction data with the same operation target into the same interaction data group, determines the number of identification processing times and usage occasions through the identification processing data of the interaction data of different interaction data groups, and determines the necessity of processing different interaction data in combination with the identification deviation data and the identification failure data of different interaction data. When there is no interaction data in the interaction data group whose processing necessity does not meet the requirements, proceed to the next step;

[0060] Furthermore, the usage scenarios include a vehicle stationary state and a vehicle driving state, wherein the vehicle stationary state includes a vehicle unstarted state and a vehicle started state.

[0061] Specifically, the recognition deviation data includes the number of recognition deviations and recognition results corresponding to different numbers of recognition deviations.

[0062] Furthermore, the recognition failure data includes the number of recognition failures and failure types of different recognition failure numbers.

[0063] Specifically, Figure 3 As shown, the method for determining the necessity of processing the interaction data is:

[0064] Determining the necessity of basic processing of the interaction data according to the number of identification processing times of different usage scenarios;

[0065] Obtaining the number of recognition deviations of the interaction data and the recognition results corresponding to different numbers of recognition deviations, and determining the recognition deviation amount of the interaction data in combination with the distribution of the recognition results corresponding to different numbers of recognition deviations, determining the number of recognition failures of the interaction data and the corresponding failure types of different numbers of recognition failures based on the recognition failure data of the interaction data, and determining the recognition failure amount of the interaction data according to the number of recognition failures and the corresponding failure types of different numbers of recognition failures;

[0066] The necessity of processing the interaction data is determined by using the basic necessity of processing the interaction data, the amount of recognition deviation, and the amount of recognition failure.

[0067] In another embodiment, the method for determining the necessity of processing the interaction data is:

[0068] S21 determines the necessity of basic processing of the interaction data according to the number of identification processing times of different usage scenarios, and judges whether the necessity of basic processing of the interaction data is within a preset necessity interval. If yes, proceed to the next step; if no, proceed to step S24;

[0069] S22 determines the number of identification deviations of the interaction data through the identification deviation data of the interaction data, and judges whether the number of identification deviations of the interaction data is less than the preset number of deviations. If so, proceed to the next step; if not, determine that the necessity of processing the interaction data does not meet the requirements;

[0070] S23 determines the number of failed identification times of the interaction data according to the failed identification data of the interaction data, and judges whether the number of failed identification times of the interaction data is less than a preset number of failed identification times. If so, proceeds to the next step; if not, determines that the necessity of processing the interaction data does not meet the requirements;

[0071] S24: obtaining the number of recognition deviations of the interaction data and the recognition results corresponding to different numbers of recognition deviations, and determining the recognition deviation amount of the interaction data in combination with the distribution of the recognition results corresponding to different numbers of recognition deviations, determining the number of recognition failures of the interaction data and the corresponding failure types of different numbers of recognition failures based on the recognition failure data of the interaction data, and determining the recognition failure amount of the interaction data according to the number of recognition failures and the corresponding failure types of different numbers of recognition failures;

[0072] S25 determines the necessity of processing the interaction data by using the basic processing necessity of the interaction data, the recognition deviation amount, and the recognition failure amount.

[0073] Further, the necessity of processing the interaction data has a value range between 0 and 1, and when the necessity of processing the interaction data is not within a preset necessity interval, it is determined that the necessity of processing the interaction data does not meet the requirement.

[0074] It should be noted that when there is interaction data whose processing necessity does not meet the requirements, the local recognition processing library of different interaction data groups is processed based on the preset generation processing strategy and AIGC model.

[0075] In another embodiment, the method for determining the necessity of processing the interaction data is:

[0076] Determine the necessity of basic processing of the interaction data according to the number of identification processing times of different usage scenarios, and judge whether the necessity of basic processing of the interaction data is less than a preset necessity threshold. If so, determine the necessity of processing the interaction data based on the basic processing necessity; if not, proceed to the next step;

[0077] Determine the number of identification deviations of the interaction data through the identification deviation data of the interaction data, obtain the number of identification deviations of the interaction data and the identification results corresponding to different identification deviation numbers, and determine the identification deviation amount of the interaction data in combination with the distribution of the identification results corresponding to different identification deviation numbers, and judge whether the identification deviation amount of the interaction data meets the requirements, if yes, proceed to the next step, if not, determine that the necessity of processing the interaction data does not meet the requirements;

[0078] Based on the recognition failure data of the interaction data, the number of recognition failures of the interaction data and the corresponding failure types of different recognition failures are performed, and the recognition failure amount of the interaction data is determined according to the number of recognition failures and the corresponding failure types of different recognition failures, and it is judged whether the recognition failure amount of the interaction data meets the requirements, if so, proceeding to the next step, if not, determining that the necessity of processing the interaction data does not meet the requirements;

[0079] The necessity of processing the interaction data is determined by using the basic necessity of processing the interaction data, the amount of recognition deviation, and the amount of recognition failure.

[0080] S3: determining the comprehensive processing necessity of different interactive data groups according to the processing necessity of different interactive data of different interactive data groups, and when it is determined based on the comprehensive processing necessity that the interactive data group belongs to the local processing group, proceeding to the next step;

[0081] Specifically, Figure 4 As shown, the method for determining the necessity of comprehensive processing of the interactive data group is:

[0082] Determining the complexity of the identification and processing of the interaction data group according to the amount of interaction data in the interaction data group and the number of identification and processing times of different interaction data;

[0083] Determining a necessity evaluation amount of the interaction data group based on the necessity of processing different interaction data of the interaction data group;

[0084] The comprehensive processing necessity of the interaction data group is determined according to the recognition processing complexity and the necessity evaluation amount of the interaction data group.

[0085] Furthermore, when the comprehensive processing necessity of the interaction data group is greater than a set necessity threshold, the interaction group is determined to be a local processing group.

[0086] In another embodiment, the method for determining the necessity of comprehensive processing of the interaction data group is:

[0087] S31: obtaining the amount of interaction data of the interaction data group, and determining whether the amount of interaction data of the interaction data group is greater than a preset interaction amount range; if so, proceeding to the next step; if not, determining that the interaction data group does not belong to a local processing group;

[0088] S32 determines the total number of identification and processing times of the interaction data group by using the identification and processing times of different interaction data, and judges whether the total number of identification and processing times of the interaction data group is greater than a preset processing number threshold, if so, proceeds to the next step, if not, determines that the interaction data group does not belong to the local processing group;

[0089] S33 determines the recognition processing complexity of the interaction data group according to the amount of interaction data in the interaction data group and the number of recognition processing times of different interaction data, and judges whether the recognition processing complexity of the interaction data group is greater than a preset complexity threshold. If so, proceed to step S35; if not, proceed to the next step;

[0090] S34: determining the processing weight values ​​of different interaction data of the interaction data group based on the processing necessity of different interaction data of the interaction data group, and judging whether the sum of the processing weight values ​​of different interaction data of the interaction data group is within a preset weight interval; if so, proceeding to the next step; if not, determining that the interaction data group does not belong to the local processing group;

[0091] S35 determines the necessity evaluation amount of the interaction data group based on the necessity of processing different interaction data of the interaction data group, and determines the comprehensive processing necessity of the interaction data group according to the recognition processing complexity and the necessity evaluation amount of the interaction data group.

[0092] S4 utilizes the comprehensive processing necessity and the network connection stability to determine the generation processing strategy of the local recognition processing library for different interaction data groups, and processes the local recognition processing library for different interaction data groups based on the generation processing strategy and the AIGC model.

[0093] Specifically, Figure 5 As shown, the method for determining the generation processing strategy of the local recognition processing library of the interaction data group is:

[0094] Determining the comprehensive weight of the interactive data group according to the network connection stability and the weight of the comprehensive processing necessity;

[0095] The generation processing strategy of the local recognition processing library of the interaction data group is determined according to the preset weight interval in which the comprehensive weight of the interaction data group is located.

[0096] Furthermore, the generation and processing strategies of the local recognition and processing library include no data volume limitation and using different preset data volume thresholds to determine the generation and processing data volume of the local recognition and processing library.

[0097] In another embodiment, the method for determining the generation processing strategy of the local recognition processing library of the interaction data group is:

[0098] When determining whether the network connection stability is less than a preset stability threshold, if so, determining the generation processing strategy of the local recognition processing library of the interaction data group based on the preset processing strategy, if not, proceeding to the next step;

[0099] Obtaining the comprehensive processing necessity of the interactive data group, determining whether the comprehensive processing necessity of the interactive data group is greater than a preset processing necessity threshold, if so, determining a generation processing strategy of a local recognition processing library of the interactive data group based on a preset processing strategy, if not, proceeding to the next step;

[0100] Determining the comprehensive weight of the interactive data group according to the network connection stability and the weight of the comprehensive processing necessity;

[0101] The generation processing strategy of the local recognition processing library of the interaction data group is determined according to the preset weight interval in which the comprehensive weight of the interaction data group is located.

[0102] It should be noted that the preset processing strategy is to determine the amount of data generated by the local recognition processing library without any data amount restriction.

[0103] Furthermore, based on the generation processing strategy and the AIGC model, the local recognition processing library processes different interaction data groups, specifically including:

[0104] Determine the limited data amount of the local recognition processing library of the interactive data group based on the generation processing strategy;

[0105] Taking the limited data amount as a constraint condition, the AIGC model is used to generate similar interaction data of the interaction data group, and the local recognition processing library of the interaction data group is processed through the similar interaction data.

[0106] Through the above embodiments, the present invention achieves the following beneficial effects:

[0107] 1. The necessity of processing different interactive data is determined by using the recognition deviation data and recognition failure data of the interactive data of different interactive data groups. This not only takes into account the emergence of technical problems such as the recognition deviation of the interactive data of the interactive data group, which causes the recognition processing error to be difficult to meet the requirements, but also further combines the differences in the requirements for real-time use processing of the interactive data of the interactive data group due to differences in the number of interactive recognitions and usage scenarios, thereby achieving accurate evaluation of the necessity of processing interactive data from multiple angles.

[0108] 2. The generation and processing strategies of the local recognition processing libraries for different interaction data groups are determined by utilizing the comprehensive processing necessity and the stability of the network connection. This enables accurate evaluation of the generation and processing strategies of the local recognition processing libraries for interaction data groups from multiple angles, which not only ensures the reliability requirements of local recognition processing for different interaction data groups, but also avoids the technical problem of wasting storage space due to the large amount of data in this recognition processing library.

[0109] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0110] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0111] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A language interaction processing method based on AIGC, characterized in that: Specifically include: When it is determined based on the driving data of different historical driving routes and the network connection data that the network connection stability of the vehicle does not meet the requirements, proceed to the next step; The interactive data with the same operation target are divided into the same interactive data group, and the identification processing times and usage occasions are determined by the identification processing data of the interactive data of different interactive data groups, and the necessity of processing different interactive data is determined by combining the identification deviation data and the identification failure data of different interactive data. When there is no interactive data in the interactive data group whose processing necessity does not meet the requirements, the next step is entered; Determining the comprehensive processing necessity of different interactive data groups according to the processing necessity of different interactive data of different interactive data groups, and when it is determined based on the comprehensive processing necessity that the interactive data group belongs to the local processing group, proceeding to the next step; Determine generation processing strategies of local recognition processing libraries of different interaction data groups by using the comprehensive processing necessity and the network connection stability, and process the local recognition processing libraries of different interaction data groups based on the generation processing strategies and the AIGC model; The network connection data of the historical driving route includes the number of locations where the network of the historical driving route is suspected to be abnormal and the number of identification failures of interaction data of different locations where the network is suspected to be abnormal; Determining that the network connection stability of the vehicle does not meet the requirements, specifically including: The number of locations with suspected anomalies in the network of different historical driving routes is determined by using the network connection data of different historical driving routes, and the network anomaly values ​​of different historical driving routes are determined by combining the number of identification failures of the interaction data of different locations with suspected anomalies in the network; Determine the number of times and the driving duration of different historical driving routes based on the driving data of different historical driving routes, and determine the weight values ​​of different historical driving routes according to the number of times and the driving duration of different historical driving routes; Determining the network connection stability of the vehicle by using weight values ​​of different historical driving routes and network anomaly values, and determining whether the network connection stability of the vehicle meets the requirements in combination with a preset stability threshold; The method for determining the generation processing strategy of the local recognition processing library of the interaction data group is: When determining whether the network connection stability is less than a preset stability threshold, if so, determining the generation processing strategy of the local recognition processing library of the interaction data group based on the preset processing strategy, if not, proceeding to the next step; Obtaining the comprehensive processing necessity of the interactive data group, determining whether the comprehensive processing necessity of the interactive data group is greater than a preset processing necessity threshold, if so, determining a generation processing strategy of a local recognition processing library of the interactive data group based on a preset processing strategy, if not, proceeding to the next step; Determining the comprehensive weight of the interactive data group according to the network connection stability and the weight of the comprehensive processing necessity; Determining a generation processing strategy of a local recognition processing library of the interaction data group according to a preset weight interval in which the comprehensive weight of the interaction data group is located; The local recognition processing library processes different interaction data groups based on the generation processing strategy and the AIGC model, specifically including: Determine the limited data amount of the local recognition processing library of the interactive data group based on the generation processing strategy; Taking the limited data amount as a constraint condition, the AIGC model is used to generate similar interaction data of the interaction data group, and the local recognition processing library of the interaction data group is processed through the similar interaction data.

2. The AIGC-based language interaction processing method according to claim 1, characterized in that: The travel data of the historical travel route includes the number of times the historical travel route was traveled and the travel duration.

3. The AIGC-based language interaction processing method according to claim 1, characterized in that: The network connection data of the historical driving route includes the number of locations where the network of the historical driving route is suspected to be abnormal and the number of identification failures of interaction data of different locations where the network is suspected to be abnormal.

4. The AIGC-based language interaction processing method according to claim 3, characterized in that: When the location has failed identification times, the location is determined to be a location where a suspected abnormality exists in the network.

5. The AIGC-based language interaction processing method according to claim 1, characterized in that: When the network connection stability of the vehicle meets the requirements, there is no need to generate a local recognition processing library.

6. The AIGC-based language interaction processing method according to claim 1, characterized in that: The use scenarios include a vehicle stationary state and a vehicle driving state, wherein the vehicle stationary state includes a vehicle unstarted state and a vehicle started state.

7. The AIGC-based language interaction processing method according to claim 1, characterized in that: The method for determining the necessity of processing the interaction data is: Determining the necessity of basic processing of the interaction data according to the number of identification processing times of different usage scenarios; Obtaining the number of recognition deviations of the interaction data and the recognition results corresponding to different numbers of recognition deviations, and determining the recognition deviation amount of the interaction data in combination with the distribution of the recognition results corresponding to different numbers of recognition deviations, determining the number of recognition failures of the interaction data and the corresponding failure types of different numbers of recognition failures based on the recognition failure data of the interaction data, and determining the recognition failure amount of the interaction data according to the number of recognition failures and the corresponding failure types of different numbers of recognition failures; The necessity of processing the interaction data is determined by using the basic necessity of processing the interaction data, the amount of recognition deviation, and the amount of recognition failure.

8. The AIGC-based language interaction processing method according to claim 1, characterized in that: The method for determining the necessity of processing the interaction data is: Determine the necessity of basic processing of the interaction data according to the number of identification processing times of different usage scenarios, and judge whether the necessity of basic processing of the interaction data is less than a preset necessity threshold. If so, determine the necessity of processing the interaction data based on the basic processing necessity; if not, proceed to the next step; Determine the number of identification deviations of the interaction data through the identification deviation data of the interaction data, obtain the number of identification deviations of the interaction data and the identification results corresponding to different identification deviation numbers, and determine the identification deviation amount of the interaction data in combination with the distribution of the identification results corresponding to different identification deviation numbers, and judge whether the identification deviation amount of the interaction data meets the requirements, if yes, proceed to the next step, if not, determine that the necessity of processing the interaction data does not meet the requirements; Based on the recognition failure data of the interaction data, the number of recognition failures of the interaction data and the corresponding failure types of different recognition failures are performed, and the recognition failure amount of the interaction data is determined according to the number of recognition failures and the corresponding failure types of different recognition failures, and it is judged whether the recognition failure amount of the interaction data meets the requirements, if so, proceeding to the next step, if not, determining that the necessity of processing the interaction data does not meet the requirements; The necessity of processing the interaction data is determined by using the basic necessity of processing the interaction data, the amount of recognition deviation, and the amount of recognition failure.

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