Order data processing method and device, storage medium and computer program product

Abstract

Embodiments of the present application provide an order data processing method and device, a storage medium and a computer program product. The method applied to a target platform comprises: receiving an order data processing request, the order data comprising order payment completed outside the target platform; obtaining supplementary data in the order completion process according to the order data; and determining that the order payment is completed outside the target platform according to an identification result of the supplementary data. Therefore, the embodiments of the present application can know whether the user completes the order payment outside the platform without manual customer service processing, and improve the processing efficiency of feedback.

Description

Technical Field

[0001] This application relates to the field of electronic information technology, and in particular to an order data processing method, device, storage medium, and computer program product. Background Technology

[0002] With the development of the internet, users obtain various services on target platforms and pay for the corresponding services through those platforms. However, some users may choose to complete the payment outside the target platform, making it impossible for the target platform to know the payment results. This affects users' ability to continue enjoying the platform's services, reduces user engagement, and results in a poor user experience. Summary of the Invention

[0003] In view of the above, embodiments of this application provide an identification method, device, storage medium, and computer program product to at least partially solve the above problems.

[0004] According to a first aspect of the embodiments of this application, an order data processing method is provided, applied to a target platform, comprising: receiving an order data processing request, wherein the order data includes order payment completed outside the target platform; obtaining supplementary data during the order completion process based on the order data; and determining, based on the identification result of the supplementary data, that the order payment was completed outside the target platform.

[0005] According to a second aspect of the embodiments of this application, an order data processing method is provided, applied to a user terminal, comprising: sending an order data processing request, wherein the order data includes order payment completed outside a target platform; and obtaining an order data processing result, wherein the order processing result includes: obtaining supplementary data in the order completion process based on the order data, and determining, based on the identification result of the supplementary data, that the payment for the order was completed outside the target platform.

[0006] According to a third aspect of the embodiments of this application, an order data processing method is provided, applied to a driver's end, comprising: obtaining an order data processing result, wherein the order processing result includes: obtaining supplementary data in the order completion process based on the order data, and determining, based on the identification result of the supplementary data, that the payment for the order was completed outside the target platform, wherein the order data includes the order payment completed outside the target platform.

[0007] According to a fourth aspect of the present application, an electronic device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; the memory is used to store at least one executable instruction, which causes the processor to perform an operation corresponding to the order data processing of the first aspect.

[0008] According to a fifth aspect of the embodiments of this application, a storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements an order data processing method as described in the first, second, or third aspect.

[0009] According to a sixth aspect of the embodiments of this application, a computer program product is provided, which, when executed by a processor, implements an order data processing method as described in the first, second, or third aspect.

[0010] The order data processing scheme provided in this application embodiment receives an order data processing request, wherein the order data includes order payments completed outside the target platform; obtains supplementary data during the order completion process based on the order data; and determines, based on the identification result of the supplementary data, that the order payment was completed outside the target platform. Therefore, this application embodiment eliminates the need for manual customer service to determine whether a user has completed order payment outside the platform, thus improving feedback processing efficiency. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0012] Figure 1 A schematic diagram illustrating a scenario of an order data processing method provided in an embodiment of this application;

[0013] Figure 2 A flowchart illustrating an order data processing method provided in one embodiment of this application;

[0014] Figure 3 A flowchart of step 203 of an order data processing method provided in an embodiment of this application;

[0015] Figure 4 A schematic diagram of a speech recognition model provided in an embodiment of this application;

[0016] Figure 5 A flowchart of step 203 of an order data processing method provided in an embodiment of this application;

[0017] Figure 6 A flowchart of step 2034 of an order data processing method provided in an embodiment of this application;

[0018] Figure 7This is a schematic diagram of a payment voucher template provided in one embodiment of this application;

[0019] Figure 8 A flowchart of step 20342 of an order data processing method provided in an embodiment of this application;

[0020] Figure 9 A flowchart of step 203 of an order data processing method provided in an embodiment of this application;

[0021] Figure 10 A flowchart illustrating an order data processing method provided in one embodiment of this application;

[0022] Figure 11 This is a structural diagram of an electronic device used in an order data processing method provided in an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in the embodiments of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of this application.

[0024] The specific implementation of the embodiments of this application will be further described below with reference to the accompanying drawings.

[0025] This application's embodiments are applied to a system consisting of a user terminal, a driver terminal, and a target platform. For ease of understanding, the application scenario of this application's embodiments is described below, with reference to... Figure 1 As shown, Figure 1 This is a schematic diagram illustrating a scenario for order data processing provided in an embodiment of this application. Figure 1 The scenario shown includes user terminal 11, driver terminal 12, and target platform 13.

[0026] User terminal 11 and driver terminal 12 can be terminal devices such as smartphones, tablets, laptops, and in-vehicle terminals, and the target platform 13 can be a ride-hailing platform. This is only an illustrative example and does not mean that this application is limited thereto.

[0027] Combination Figure 1 The scenario shown illustrates the method provided in Embodiment 1 of this application. It should be noted that... Figure 1 This is merely one application scenario of the method provided in Embodiment 1 of this application, and does not imply that the method must be applied to... Figure 1 The scene shown is for reference. Figure 2 As shown, Figure 2A flowchart of an order data processing method provided in Embodiment 1 of this application is included, the method comprising the following steps:

[0028] Step 201: Receive order data processing request. Order data includes order payments completed outside the target platform.

[0029] In this embodiment, the order data includes order payments completed outside the target platform, and the order data processing requests include: an order termination request sent by the user terminal 11, which is based on the completion of order payment outside the target platform; an order termination request sent by the target platform 13, which is based on the order not being terminated after exceeding a preset time threshold, the specific time threshold of which can be set by the target platform as needed; and an order termination request sent by the driver terminal 12, which is based on the completion of order payment outside the target platform.

[0030] In the embodiments of this application, see Figure 1 User terminal 11, driver terminal 12 and target platform 13 can all generate order data processing requests, and target platform 13 receives order data processing requests.

[0031] Order completion can include: closing the order, canceling / revoking the order, etc.

[0032] Step 202: Obtain supplementary data during the order completion process based on the order data.

[0033] Step 203: Based on the identification results of the supplementary data, determine that the order payment was completed outside the target platform.

[0034] The order data processing solution provided in this application receives an order data processing request, whereby the order data includes order payments completed outside the target platform; it obtains supplementary data during the order completion process based on the order data; and based on the identification results of the supplementary data, it determines that the order payment was completed outside the target platform. Therefore, this application embodiment eliminates the need for manual customer service to determine whether a user has completed order payment outside the platform, thus improving feedback processing efficiency.

[0035] In some specific implementations of the embodiments of this application, the supplementary data includes: audio recording data during the order completion process.

[0036] It should be noted that the acquisition of audio recording data in this application embodiment is carried out with the user's permission.

[0037] Specifically, the order completion process includes the time from when the user boards the vehicle to when the user leaves.

[0038] To obtain audio recording data related to order completion more quickly, this application embodiment extracts audio recording data from the order completion time to the user's departure time. This embodiment extracts audio recording data from the order completion time to the user's departure time, eliminating the need to recognize audio recording data throughout the entire order completion process, thus improving the efficiency of speech recognition and avoiding interference from useless information.

[0039] The order completion time can be determined based on order completion information sent by the user, the driver, or information obtained from the target platform regarding the driver's arrival at the destination address. In this embodiment, the order completion information can be obtained from the user, the driver, or the target platform, thus ensuring the accuracy and reliability of the order completion information.

[0040] Since users and drivers usually pay for the order before it is completed, in order to obtain more accurate audio data during the order completion process, the order end time is usually adjusted forward by a preset time period. The length of the specific preset time period is set by the target platform as needed.

[0041] See Figure 3 Step 203 includes:

[0042] Step 2031: Perform payment recognition on the recorded data to obtain the first payment recognition result;

[0043] Step 2032: Based on the first payment recognition result, determine that the order payment was completed outside the target platform.

[0044] Specifically, it is determined whether payment information exists in the recorded data. Payment information includes at least one of the following: payment amount, payment method, payment confirmation, and payment result.

[0045] Since a user's payment behavior inevitably includes at least one of the following: payment amount, payment method, payment confirmation, and payment result, this application embodiment can quickly determine whether a user has made an order payment outside the target platform by identifying payment information and using audio recording data.

[0046] For example, if a user asks, "Can I pay in cash?", the payment method in the recording will be identified to obtain the payment information.

[0047] If payment information is present in the audio recording, it indicates that the user has made an order payment outside the target platform, and the first payment identification result is obtained.

[0048] In some specific implementations of the embodiments of this application, a first speech recognition model is pre-trained to recognize the recorded data.

[0049] The first speech recognition model is obtained through pre-training. It is usually trained using training samples related to payments outside the platform. The training samples related to payments outside the platform can include speech related to cash payments, other payment methods, etc.

[0050] Specifically, if the audio recording during the order completion process involves adjusting the order end time forward by a preset time period until the user leaves, then a speech recognition model is used to perform speech recognition on the audio recording data to obtain the corresponding text data, including:

[0051] The spectral features are obtained by processing the recorded data using a speech recognition model.

[0052] The spectral features are compressed and encoded, and the compressed and encoded feature data is used to calculate the text probability of each audio unit contained in the recording data using a classifier in the speech recognition model.

[0053] Based on the text probability of each audio unit, the text data corresponding to the recording data is obtained.

[0054] The audio recording data can contain at least one audio unit. Each audio unit can have its corresponding text probability calculated, and the text with the higher probability is selected as the text data corresponding to that audio unit. For example, the top ten most probable texts can be selected as the text data corresponding to that audio unit.

[0055] Further, optionally, spectral feature processing of the recording data may include performing spectral processing on the recording data to obtain Mel-scale Frequency Cepstral Coefficients (MFCC) features, which is only an example here.

[0056] Based on the above implementation method, such as Figure 4 As shown, the recording data is divided into multiple audio units, where x represents the spectral features of an audio unit. x is compressed and encoded by an encoder to obtain compressed feature data h, where h can be a latent variable. A classifier is then used to classify h, determining the probability distribution of the text probability corresponding to each audio unit. Optionally, the softmax() function can be used to calculate the probability distribution. , Where W is the weight. For example, the number of words (also known as the vocabulary) is V, that is, the total number of words is V. For the feature data h of each audio unit, the probability of h being each word can be calculated, resulting in V probabilities. In addition, there is a possibility of no speech information, resulting in a total of V+1 probabilities. The word with the higher probability is taken as the word corresponding to the audio unit.

[0057] Optionally, a specific example is provided here to illustrate the implementation of step 2031, which includes:

[0058] A first speech recognition model is used to obtain text data corresponding to the recorded data; the text data is matched with keywords in a preset database, the preset database including at least one keyword indicating payment outside the platform; based on whether the text data matches the keywords contained in the preset database, it is determined whether there is payment information in the recorded data, and the first payment recognition result is obtained.

[0059] For example, keywords in the preset database may include at least one of the following: payment amount, payment method, payment confirmation, and payment result. For instance, payment method may include the name of a certain payment application, payment confirmation may include whether the driver agrees to the payment, and payment result may include whether the user or driver confirms receipt of payment.

[0060] Optionally, since keywords for off-platform payments usually need to be verified by multiple sources, regular expressions can be used to match these keywords. Regular expressions can compile multiple keywords into a formula, and using regular expression matching can improve the accuracy of keyword matching.

[0061] Alternatively, confidence levels can be pre-set for keywords in the database related to off-platform payments. A keyword's confidence level indicates the likelihood that the keyword represents a payment made outside the platform. For example, text data is matched against keywords in a pre-defined database to identify at least one keyword contained in the text data. The average confidence level for each keyword is calculated. If the average confidence level is greater than or equal to a pre-defined threshold, a successful match is determined, indicating the presence of payment information in the recording data. If the average confidence level is less than the pre-defined threshold, a failed match is determined, indicating the absence of payment information in the recording data. Using keyword confidence levels for calculation can improve the accuracy of the judgment.

[0062] In some specific implementations of the embodiments of this application, the method further includes: pre-training a second speech recognition model.

[0063] When the audio recording data during the order completion process is the user's audio recording data throughout the entire order service process, the second speech recognition model is used for speech recognition to directly identify keywords related to external payment from the audio recording data.

[0064] Optionally, a specific example is provided here to illustrate the implementation of step 2031, which includes:

[0065] A second speech recognition model is used to determine whether the recorded data contains keywords from a preset database, which includes at least one keyword indicating off-platform payment. Based on the presence or absence of the keyword, it is determined whether payment information exists in the recorded data, thus obtaining the first payment recognition result.

[0066] In this embodiment, the keywords indicating payment outside the platform are directly identified using the audio recording data of the user throughout the order service process, without the need to truncate the audio data, thus improving the accuracy of the identification.

[0067] In some specific implementations of this application, the target platform 13 sends the first payment recognition result to the user terminal 11 or the driver terminal 12, and either the user terminal 11 or the driver terminal 12 can choose whether to confirm the first payment recognition result.

[0068] Specifically, the target platform 13 sends the first payment recognition result to the user terminal 11, and the user terminal 11 can choose to send "Confirm payment outside the target platform" or "No payment outside the target platform was made".

[0069] Specifically, the target platform 13 sends the first payment recognition result to the driver terminal 12, and the driver terminal 12 can choose to send "Confirm payment outside the target platform" or "No payment outside the target platform was made".

[0070] This application embodiment avoids incorrect order termination due to misidentification of recorded data, thus preventing negative impacts on user experience, through the interaction between the target platform and the user or driver's end.

[0071] In some specific implementations of the embodiments of this application, the supplementary data includes: a payment voucher image during the order completion process.

[0072] Optionally, the payment voucher image can be uploaded to the target platform by either the user's or the driver's end.

[0073] In some specific implementations of the embodiments of this application, see [link to relevant documentation]. Figure 5 Step 203 includes:

[0074] Step 2033: Perform payment recognition on the payment voucher image to obtain the second payment recognition result.

[0075] Step 2034: Based on the second payment identification result, determine that the order payment was completed outside the target platform.

[0076] See Figure 6 It also includes step 204, which involves pre-setting multiple payment voucher templates and corresponding payment recognition methods, with at least some payment voucher templates corresponding to different payment platforms.

[0077] Step 2034 includes:

[0078] Step 20341: Determine the payment voucher template that matches the payment voucher image.

[0079] Step 20342: Perform payment recognition on the payment voucher image according to the payment recognition method corresponding to the matched payment voucher to obtain the second payment recognition result.

[0080] like Figure 7 As shown, Figure 7 The diagrams 7a and 7b are two payment voucher templates provided in Embodiment 1 of this application. Based on the payment voucher templates, payment recognition can be performed more accurately and quickly in the payment voucher image, thus improving processing efficiency.

[0081] Specifically, see Figure 8 Step 20342 includes:

[0082] Step 20342a: Determine the location of the payment amount and payment time in the payment voucher according to the payment identification method corresponding to the matched payment voucher.

[0083] Step 20342b: Extract the payment amount and payment time from the payment voucher based on their positions in the voucher.

[0084] Step 20342c: Obtain the second payment recognition result based on whether the payment amount and payment time correspond to the order.

[0085] This application embodiment only needs to extract the payment amount and payment time from the payment voucher templates 7a and 7b at those locations to determine if the payment amount and payment time correspond to the order. This allows for rapid payment recognition of the payment voucher image without needing to read the entire payment voucher image for image recognition. This application embodiment improves the efficiency and accuracy of payment voucher recognition.

[0086] In some specific implementations of the embodiments of this application, the supplementary data includes: audio recording data and payment voucher images during the order completion process.

[0087] The audio recording data and payment voucher images during the order completion process are the same as in the above embodiment, so they will not be described again here.

[0088] See Figure 9 Step 203 includes: the above steps 2031 and 2033 and the following step 2035.

[0089] Step 2025: Based on the first payment identification result, determine that the order payment was completed outside the target platform.

[0090] This application embodiment uses the first payment recognition result obtained from the recorded data payment recognition in the above embodiments and the second payment recognition result obtained from the payment voucher image recognition to determine that the order payment was completed outside the target platform. This application embodiment can more accurately determine that the order payment was completed outside the target platform.

[0091] In this embodiment of the application, it is also possible to first determine whether the first payment recognition result obtained by the payment recognition of the audio data can determine whether the payment of the order was completed outside the target platform according to steps 2021 and 2022. If it cannot be determined, then the second payment recognition result obtained by the payment voucher image recognition according to steps 2023 and 2024 can determine whether the payment of the order was completed outside the target platform.

[0092] Based on the method described in the above embodiments, see [link / reference]. Figure 10 This application provides an order data processing method, applied to... Figure 1 User client 11, the method includes:

[0093] Step 101: Send an order data processing request. The order data includes order payments completed outside the target platform.

[0094] Step 102: Obtain the order data processing results. The order processing results include: obtaining supplementary data during the order completion process based on the order data, and determining, based on the identification results of the supplementary data, that the order payment was completed outside the target platform.

[0095] In this embodiment, the user terminal 11 sends an order data processing request, and the target platform 13 executes steps 201-203 in the above embodiment, sending the obtained order data processing result back to the user terminal 11. The steps executed by the target platform in this embodiment will not be described in detail. This is to allow users to know whether orders paid outside the target platform have been closed, thereby preventing users from being unable to promptly close orders on the target platform due to payments made outside the target platform, thus affecting their ability to use the target platform again and enjoy the corresponding services.

[0096] In some specific implementations of this application, the target platform 13 sends the first payment recognition result to the user terminal 11 or the driver terminal 12, and either the user terminal 11 or the driver terminal 12 can choose whether to confirm the first payment recognition result.

[0097] Specifically, the target platform 13 sends the first payment recognition result to the user terminal 11, and the user terminal 11 can choose to send "Confirm payment outside the target platform" or "No payment outside the target platform was made".

[0098] This application embodiment avoids incorrect order termination due to misidentification of recorded data, thus preventing negative impacts on user experience, through the interaction between the target platform and the user or driver's end.

[0099] Based on the methods described in the above embodiments, this application provides an order data processing method, applied to... Figure 1 The driver terminal 12, the method includes:

[0100] Obtain the order data processing results, which include: obtaining supplementary data during the order completion process based on the order data, and determining, based on the identification results of the supplementary data, that the order payment was completed outside the target platform. The order data includes order payments completed outside the target platform.

[0101] In this embodiment, the target platform 13 executes steps 201-203 of the above embodiments, sending the obtained order data processing results to the driver terminal 12. The steps performed by the target platform in this embodiment will not be repeated here. This is to allow drivers to know whether orders paid for outside the target platform by users have been completed, thereby preventing users from using the target platform again due to orders not being completed in a timely manner because the user completed the order payment outside the target platform.

[0102] In some specific implementations of this application, the target platform 13 sends the first payment recognition result to the user terminal 11 or the driver terminal 12, and either the user terminal 11 or the driver terminal 12 can choose whether to confirm the first payment recognition result.

[0103] Specifically, the target platform 13 sends the first payment recognition result to the driver terminal 12, and the driver terminal 12 can choose to send "Confirm payment outside the target platform" or "No payment outside the target platform was made".

[0104] This application embodiment avoids incorrect order termination due to misidentification of recorded data, thus preventing negative impacts on user experience, through the interaction between the target platform and the user or driver's end.

[0105] Based on the method described in Embodiment 1 above, this application provides an electronic device for implementing the method described in the above embodiments, with reference to... Figure 11 This document illustrates a schematic diagram of an electronic device according to an embodiment of this application. The specific embodiments of this application do not limit the specific implementation of the electronic device.

[0106] like Figure 11 As shown, the electronic device 110 may include: a processor 1102, a communications interface 1104, a memory 1106, and a communications bus 1108.

[0107] in:

[0108] The processor 1102, communication interface 1104, and memory 1106 communicate with each other via communication bus 1108.

[0109] Communication interface 1104 is used to communicate with other electronic devices or servers.

[0110] The processor 1102 is used to execute program 1110, which can specifically execute the relevant steps in the above-described identification method embodiment.

[0111] Specifically, program 1110 may include program code that includes computer operation instructions.

[0112] The processor 1102 may be a CPU, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The smart device may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0113] Memory 1106 is used to store program 1110. Memory 1106 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0114] Specifically, program 1110 can be used to cause processor 1102 to execute the order data processing method described in the above embodiments. The specific implementation of each step in program 1110 can be found in the corresponding descriptions of the steps and units in the above identification method embodiments, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0115] Based on the methods described in the above embodiments, this application provides a computer storage medium storing a computer program thereon, which, when executed by a processor, implements the methods described in the above embodiments.

[0116] Based on the methods described in the above embodiments, this application provides a computer program product that, when executed by a processor, implements the methods described in the above embodiments.

[0117] It should be noted that, depending on the implementation needs, the various components / steps described in the embodiments of this application can be broken down into more components / steps, or two or more components / steps or parts of the operation of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of this application.

[0118] The methods described in the embodiments of this application can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD-ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code downloaded over a network that is originally stored in a remote recording medium or a non-transitory machine-readable medium and will be stored in a local recording medium. Thus, the methods described herein can be processed by software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components (e.g., RAM, ROM, flash memory, etc.) capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods described herein. Furthermore, when a general-purpose computer accesses the code used to implement the methods shown herein, the execution of the code transforms the general-purpose computer into a dedicated computer for performing the methods shown herein.

[0119] Those skilled in the art will recognize that the units and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application.

[0120] The above embodiments are only used to illustrate the embodiments of this application, and are not intended to limit the embodiments of this application. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the embodiments of this application. Therefore, all equivalent technical solutions also fall within the scope of the embodiments of this application, and the patent protection scope of the embodiments of this application should be defined by the claims.

Claims

1. An order data processing method, applied to a target platform, comprising: Receive an order data processing request, wherein the order data includes order payments completed outside the target platform; The target platform is a platform that provides services to users, and the order is the order corresponding to the service; Supplementary data is obtained based on the order data during the order completion process; Based on the identification results of the supplementary data, it was determined that the payment for the order was completed outside the target platform; The first payment recognition result is sent to the user's and / or driver's terminals; Receive confirmation information sent by the user terminal and / or driver terminal based on the first payment identification result.

2. The method according to claim 1, wherein, The supplementary data includes: audio recordings during the order completion process; The step of determining, based on the identification results of the supplementary data and the determination that the payment for the order was completed outside the target platform, includes: The recorded data is subjected to payment recognition to obtain a first payment recognition result; Based on the first payment recognition result, it is determined that the payment for the order was completed outside the target platform.

3. The method according to claim 1, wherein, The supplementary data includes: images of payment vouchers during the order completion process; The step of determining, based on the identification results of the supplementary data and the determination that the payment for the order was completed outside the target platform, includes: The payment voucher image is subjected to payment recognition to obtain a second payment recognition result; Based on the second payment identification result, it is determined that the payment for the order was completed outside the target platform.

4. The method according to claim 1, wherein, The supplementary data includes: audio recordings and payment voucher images during the order completion process; The step of determining, based on the identification results of the supplementary data and the determination that the payment for the order was completed outside the target platform, includes: The recorded data is subjected to payment recognition to obtain a first payment recognition result; The payment voucher image is subjected to payment recognition to obtain a second payment recognition result; Based on the first payment identification result and the first payment identification result, it is determined that the payment for the order was completed outside the target platform.

5. The method of claim 2 or 4, wherein, The method further includes: Pre-train the first speech recognition model; The step of performing payment recognition on the recorded data to obtain a first payment recognition result includes: The first speech recognition model is used to obtain the text data corresponding to the recorded data; The text data is matched for keywords in a preset database, which includes at least one keyword indicating payment outside the platform. Based on whether the text data matches keywords contained in the preset database, it is determined whether payment information exists in the recording data, and the first payment recognition result is obtained.

6. The method of claim 5, wherein, The step of using a first speech recognition model to obtain the text data corresponding to the recorded data includes: The spectral features are obtained by performing spectral feature processing on the recorded data; The spectral features are compressed and encoded, and a classifier is used to calculate the text probability of each audio unit contained in the recording data. Based on the text probability of each audio unit, the text data corresponding to the recording data is obtained.

7. The method of claim 2 or 4, wherein, The method further includes: Pre-train a second speech recognition model; The step of performing payment recognition on the recorded data to obtain a first payment recognition result includes: A second speech recognition model is used to determine whether the recorded data contains keywords in a preset database, the preset database including at least one keyword indicating payment outside the platform; Based on the presence or absence of the keyword, it is determined whether payment information exists in the recording data, thus obtaining the first payment recognition result.

8. The method according to claim 3 or 4, wherein, The method further includes: Multiple payment voucher templates and corresponding payment recognition methods are pre-defined, and at least some of the payment voucher templates correspond to different payment platforms; The step of performing payment recognition on the payment voucher image to obtain a second payment recognition result includes: Determine the payment voucher template that matches the payment voucher image; Based on the payment recognition method corresponding to the matched payment voucher, the payment voucher image is used for payment recognition to obtain the second payment recognition result.

9. The method of claim 8, wherein, The step of performing payment recognition on the payment voucher image according to the payment recognition method corresponding to the matched payment voucher includes: Based on the payment identification method corresponding to the matched payment voucher, determine the location of the payment amount and payment time in the payment voucher; Extract the payment amount and payment time from the payment voucher based on their positions in the payment voucher. The second payment identification result is obtained based on whether the payment amount and payment time correspond to the order.

10. An order data processing method, applied to a user terminal, comprising: Send an order data processing request, wherein the order data includes order payments completed outside the target platform; The target platform is a platform that provides services to users, and the order is the order corresponding to the service; Obtain the order data processing result, which includes: obtaining supplementary data during the order completion process based on the order data, and determining, based on the identification result of the supplementary data, that the payment for the order was completed outside the target platform; Receive the first payment recognition result sent by the target platform, and send confirmation information of the first payment recognition result to the target platform.

11. An order data processing method, applied to the driver's end, comprising: Obtaining order data processing results, the order processing results include: obtaining supplementary data during the order completion process based on the order data, and determining, based on the identification results of the supplementary data, that the payment for the order was completed outside the target platform, the order data including order payments completed outside the target platform; The system receives a first payment recognition result sent by the target platform and sends confirmation information of the first payment recognition result to the target platform, wherein the target platform is a platform that provides services to the user, and the order is the order corresponding to the service.

12. An electronic device comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the order data processing method as described in any one of claims 1-11.

13. A storage medium storing a computer program, which, when executed by a processor, implements the order data processing method as described in any one of claims 1-11.

14. A computer program product, which, when executed by a processor, implements the order data processing method as described in any one of claims 1-11.

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