A data processing method, device and electronic equipment

Abstract

The present disclosure provides a data processing method and device and electronic equipment, wherein the method comprises: obtaining voice data sent by an electronic device; determining an association relationship between a plurality of voice data or between the voice data and the electronic device based on the working mode of each electronic device; and processing at least one voice data based on the association relationship between a plurality of voice data or between the voice data and the electronic device to obtain a target processing result.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a data processing method, apparatus, and electronic device. Background Technology

[0002] In modern enterprise operations, employees' work scenarios are becoming increasingly fragmented and diversified. For example, in fieldwork or dispatching scenarios, high-frequency, short-duration instant communication is required; in meetings or office scenarios, long-duration, high-quality recording and documentation are needed. Existing solutions usually require users to carry multiple devices to complete these tasks separately, which is not only inconvenient to carry but also cumbersome to operate, affecting work efficiency. Summary of the Invention

[0003] This disclosure provides a data processing method, apparatus, and electronic device to at least solve the above-mentioned technical problems existing in the prior art.

[0004] According to a first aspect of this disclosure, a data processing method is provided, comprising: Acquire voice data sent by electronic devices; Based on the operating modes of each of the electronic devices, the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, is determined; Based on the correlation between multiple voice data, or the correlation between the voice data and the electronic device, at least one of the voice data is processed to obtain the target processing result.

[0005] In one possible implementation, the operating modes among the various electronic devices include a first mode; wherein, in the first mode, the various electronic devices are in the same session environment; Determining the correlation between multiple voice data based on the operating modes of each of the electronic devices includes: If the operating mode of each of the electronic devices is the first mode, the association relationship between each voice data is determined based on the session information between the electronic devices or the semantic information between each voice data as defined by the first mode.

[0006] In one possible implementation, based on the correlation between multiple voice data, at least one of the voice data is processed to obtain a target processing result, including: The speech data belonging to the same association are detected to obtain the speech quality detection result; Based on the speech quality detection results, target speech sub-data that meet the target quality conditions are determined in each speech data set; The target speech sub-data is processed to obtain the target processing result.

[0007] In one possible implementation, based on the correlation between multiple voice data, at least one of the voice data is processed to obtain a target processing result, including: All electronic devices are divided into multiple groups, and the target processing sub-results corresponding to each group are generated based on the voice data collected by the electronic devices in each group. The target processing sub-results corresponding to all groups are merged to generate the target processing result.

[0008] In one possible implementation, the operating mode between the electronic devices includes a second mode; wherein, in the second mode, each of the electronic devices sends target data to the target electronic device; Based on the operating modes of each of the electronic devices, the association between the voice data and the electronic devices is determined, including: If the electronic device is operating in the second mode, determine the target electronic device associated with the voice data.

[0009] In one possible implementation, processing at least one of the voice data based on the association between the voice data and the electronic device to obtain a target processing result includes: The voice data collected by the electronic device is processed into target data, and the target data is sent to the target electronic device; the modality of the target data is matched with the target state of the target electronic device.

[0010] In one possible implementation, the method further includes: When the operating mode of each electronic device is the first mode, the target processing result is sent to each electronic device. Obtain feedback data sent by any electronic device; Based on the feedback data, the target processing result is updated to obtain the target update result.

[0011] In one possible implementation, determining the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, based on the operating modes of each of the electronic devices, includes: Receive user operations, including a first operation and a second operation; In response to the user's operation being a first operation, the operating mode of each of the electronic devices is determined to be a first mode; based on the operating mode of each of the electronic devices being the first mode, the association relationship between the multiple voice data is determined; In response to the user's operation being a second operation, the operating mode of each of the electronic devices is determined to be a second mode; based on the operating mode of each of the electronic devices being the second mode, the association between the voice data and the electronic devices is determined.

[0012] According to a second aspect of this disclosure, a data processing apparatus is provided, comprising: Acquisition unit, used to acquire voice data sent by electronic device; The determining unit is configured to determine the association relationship between multiple voice data, or the association relationship between the voice data and the electronic device, based on the operating modes of each of the electronic devices; The processing unit is configured to process at least one of the voice data based on the correlation between multiple voice data or the correlation between the voice data and the electronic device, so as to obtain a target processing result.

[0013] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and a memory communicatively connected to said at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the following method: acquiring voice data sent by an electronic device; Based on the operating modes of each of the electronic devices, the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, is determined; Based on the correlation between multiple voice data, or the correlation between the voice data and the electronic device, at least one of the voice data is processed to obtain the target processing result.

[0014] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0015] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which: In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0016] Figure 1 A flowchart of a data processing method provided in an embodiment of this disclosure; Figure 2 This is a grouping and fusion logic diagram in the data processing method provided in the embodiments of this disclosure; Figure 3 This is a schematic diagram of the structure of the data processing apparatus provided in the embodiments of this disclosure; Figure 4 A schematic diagram of the composition structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0017] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0018] Based on this, embodiments of this disclosure provide a data processing method applied to a cloud / server. The electronic device can be a bimodal voice interaction device supporting intelligent intercom and conference assistant functions, capable of establishing a communication connection with the cloud / server; therefore, the processing power of the electronic device can be relatively weak. In some embodiments, if the electronic device possesses higher processing power, this method can also be applied to the electronic device.

[0019] Figure 1 A flowchart of the data processing method provided in the embodiments of this disclosure, such as Figure 1 As shown, the method includes: Step 101: Obtain the voice data sent by the electronic device; Step 102: Based on the working mode of each electronic device, determine the correlation between multiple voice data, or the correlation between voice data and electronic devices; Step 103: Based on the correlation between multiple voice data or the correlation between voice data and electronic devices, process at least one voice data to obtain the target processing result.

[0020] The data processing method will be described in detail below with reference to specific embodiments.

[0021] The electronic device disclosed herein includes multiple microphones, preferably including five omnidirectional microphones (for 360° sound pickup) and one bone conduction microphone (for noise reduction or VAD (Voice Activity Detection) detection).

[0022] Electronic devices acquire voice data input by users through microphones, and then the cloud retrieves and processes the voice data sent by the electronic devices.

[0023] In one embodiment, the operating modes of the electronic devices include a first mode and a second mode, wherein in the first mode, each electronic device is in the same session environment; and in the second mode, each electronic device sends target data to a target electronic device.

[0024] Specifically, the first mode is the conference mode, in which each electronic device can record the content of the same conference; the second mode is the intercom mode, in which each electronic device can send voice data to the target electronic device, and can also receive voice data sent by the target electronic device.

[0025] In one embodiment, determining the association between multiple voice data sets, or the association between voice data sets and electronic devices, based on the operating modes of each electronic device, includes: Receive user operations, including a first operation and a second operation; If the user's operation is the first operation, then the operating mode of each electronic device is determined as the first mode; based on the operating mode of each electronic device as the first mode, the correlation between multiple voice data is determined. If the user's operation is a second operation, then the operating mode of each electronic device is determined to be the second mode; based on the operating mode of each electronic device being the second mode, the association between voice data and electronic devices is determined.

[0026] The first operation includes touching a first button and / or inputting a first voice command; the second operation includes touching a second button and / or inputting a second voice command.

[0027] Specifically, the electronic device includes a first button and a second button. The first button can be a multi-function button, and the second button can be a PTT (Push To Talk) button. Activating the first button switches the electronic device to its first operating mode, and activating the second button switches it to its second operating mode. Independently triggering the corresponding operating mode via physical buttons simplifies operation and prevents accidental mode switching.

[0028] Meanwhile, electronic devices can also switch between first and second modes via voice commands. By inputting the first voice command (e.g., "Start a meeting" or "Record this idea"), the electronic device enters first mode and activates the recording function; by inputting the second voice command (e.g., "Send a message to Manager Wang"), the electronic device enters second mode and activates the intercom function. The electronic device automatically routes to the corresponding operating mode based on the given command, eliminating the need for manual mode switching, thus allowing for mode switching even in situations where manual operation is inconvenient.

[0029] In one embodiment, determining the correlation between multiple voice data based on the operating modes of each electronic device includes: If each electronic device operates in the first mode, the association between each voice data is determined based on the session information between electronic devices or the semantic information between each voice data as specified in the first mode.

[0030] Each electronic device is bound to the identity information of each user. Therefore, after knowing which users are participating in the same meeting, it can be determined that the session information of the electronic devices corresponding to these users is the same, thereby determining that the voice data collected by these electronic devices are related to the same session environment.

[0031] Alternatively, after collecting voice data, the electronic devices can detect the semantic information corresponding to each voice data. If the content similarity of the semantic information corresponding to each voice data is greater than a preset threshold, it indicates that the voice data collected by these electronic devices is a recording of the same meeting. In this case, it can be determined that the relationship between the voice data collected by these electronic devices is that they are in the same conversation environment.

[0032] In one embodiment, based on the correlation between multiple voice data, at least one voice data is processed to obtain a target processing result, including: The speech quality detection results are obtained by detecting each speech data belonging to the same association. Based on the speech quality detection results, target speech sub-data that meet the target quality conditions are identified in each speech data set; The target speech sub-data is processed to obtain the target processing result.

[0033] Voice data belonging to the same association, meaning they correspond to recordings of the same meeting, share the same semantic information. However, for the same participant, some electronic devices, due to their distance from the participant, may capture noise or incomplete audio. Therefore, it's necessary to inspect each voice data point to determine the optimal target voice sub-data for each participant. Then, these target voice sub-data are processed to obtain the desired processing result. By performing quality checks on multiple voice data points under the same association, low-quality voice segments such as noise, distortion, disconnections, and weak reception can be eliminated, preventing invalid data from interfering with the processing results. This allows for the selection of target voice sub-data that meets the target quality criteria, improving the accuracy of speech-to-text transcription and ensuring the output is complete and semantically clear.

[0034] For example, in this disclosure, the identity information and voiceprint features of each participant can be determined first; then, a heterogeneous microphone array can be used to locate the sound source and record the physical location information of the speaker; the audio data and physical location information are uploaded synchronously, and the cloud engine combines the voiceprint features and physical location information to distinguish the speaker and determine the various voice data corresponding to each participant; each voice data is detected to determine the target voice sub-data corresponding to each participant; the target voice sub-data is transcribed to obtain the corresponding text information, and meeting minutes are generated based on the text information corresponding to each participant.

[0035] In other embodiments, processing methods that can reflect the meeting content may also be used, such as generating meeting playback records based on the target voice sub-data corresponding to each participant.

[0036] In one embodiment, based on the correlation between multiple voice data, at least one voice data is processed to obtain a target processing result, including: All electronic devices are divided into multiple groups, and the target processing sub-results corresponding to each group are generated based on the voice data collected by the electronic devices in each group. The target processing sub-results corresponding to all groups are merged to generate the target processing result.

[0037] In this embodiment, all electronic devices can be divided into multiple groups, each corresponding to a sub-conference. Electronic devices within each group collect voice data from each participant in that sub-conference and generate meeting minutes for each sub-conference based on this data. Then, the meeting minutes from all sub-conferences are merged to generate the final meeting minutes. This method solves the problem of interference caused by discussing multiple sub-conferences simultaneously in the same meeting. It allows multiple groups to discuss multiple sub-issues at different times and spaces. After the discussion, the voice data from multiple groups are logically merged through processing to form a complete discussion result, achieving concurrent processing of meeting discussions, saving meeting time, and improving work efficiency.

[0038] Figure 2 This is a grouping and fusion logic diagram in the data processing method provided in the embodiments of this disclosure. For example... Figure 2 As shown, a meeting may contain multiple sub-topics, such as sub-topic 1, sub-topic 2, ..., sub-topic K. Each sub-topic corresponds to a group, and each group has multiple electronic devices. The electronic devices in each group collect the voice data of the participants in that group, and then generate the discussion results of each group. The discussion results of each group are then processed by the fusion logic to obtain the discussion results of the entire meeting.

[0039] When processing the voice data, each group can, as described above, first determine the target voice sub-data corresponding to each participant in each group, then transcribe the target voice sub-data to obtain the corresponding text information, and generate the meeting minutes corresponding to each group based on the text information corresponding to each participant.

[0040] In this embodiment of the disclosure, if a user wants to mark important points during a meeting, they can briefly press the first button to mark them. The marked points will be highlighted when the meeting minutes are generated, thus highlighting the key points in the meeting minutes and improving the effectiveness of the meeting minutes.

[0041] In one embodiment, determining the association between voice data and electronic devices based on the operating modes of each electronic device includes: If the electronic device is operating in the second mode, identify the target electronic device associated with the voice data.

[0042] Specifically, if the electronic device is operating in the second mode, i.e., intercom mode, then it is necessary to first determine which electronic device the voice data needs to be sent to, i.e., the target electronic device. After determining the target electronic device, the corresponding voice data is sent to the target electronic device, and it can also receive voice data sent by the target electronic device. Here, determining the target electronic device associated with the voice data first can establish a correspondence between the voice data and the receiving terminal, avoid missending or missing voice messages, and ensure accurate delivery of voice data.

[0043] The electronic device includes a cellular mobile communication module (4G LTE) and a short-range wireless communication module. When the electronic device is in the second mode, it collects voice data and pushes the voice data to the cloud instant messaging group in real time through the cellular mobile communication module or the short-range wireless communication module, as well as receiving group messages and performing cross-modal playback or display of voice or text.

[0044] In one embodiment, based on the correlation between voice data and an electronic device, at least one voice data is processed to obtain a target processing result, including: The voice data collected by the electronic device is processed into target data and sent to the target electronic device; the modality of the target data is matched with the target state of the target electronic device.

[0045] Specifically, when the electronic device is in the second mode, the voice data collected by the electronic device can be converted into text data. The target data may include voice data and / or the text data corresponding to the voice data. Therefore, when sending the target data to the target electronic device, only voice data or text data may be sent, or both voice data and text data may be sent to the target electronic device together.

[0046] In one embodiment, matching the modality of the target data with the target state of the target electronic device includes: When the target electronic device is detected to be in a preset silent intercom state, the voice data sent by the electronic device is converted into text data and the text data is displayed. When the target electronic device is detected to be in a preset voice intercom state, the text data sent by the electronic device is converted into voice data and the voice data is played.

[0047] Specifically, if the target electronic device is in a preset silent intercom mode, meaning the environment in which the target electronic device is located does not allow for voice playback, and if the target electronic device receives voice data, the voice data can be converted into text data and then displayed. If the target electronic device is in a preset voice intercom mode, meaning the environment in which the target electronic device is located allows for voice playback, and if the target electronic device receives text data, the text data can be converted into voice data and then played. Of course, the target electronic device can also directly display the text data.

[0048] In this embodiment of the disclosure, text is automatically displayed in silent intercom mode and voice is automatically played in voice intercom mode. The mode of the received target data can be automatically switched according to the state of the target electronic device, thereby improving the intelligence and scene adaptability of intercom interaction, avoiding the inability to view messages due to environmental limitations, ensuring the reliability of intercom communication, and improving the user experience.

[0049] In one embodiment, the method further includes: When each electronic device is in the first operating mode, the target processing result is sent to each electronic device. Obtain feedback data sent by any electronic device; Based on the feedback data, the target processing results are updated to obtain the target update results.

[0050] If the electronic devices are in the first mode, the target processing result is to generate meeting minutes. After the meeting minutes are sent to each electronic device, participants can correct errors or add new content based on them. Specifically, participants can input their feedback data (corrections or additions) into the electronic devices via intercom. The cloud retrieves the feedback data sent by the electronic devices and then updates the meeting minutes. This expands meetings with fixed locations and times into interactive sessions across different times and spaces, breaking through the traditional limitation of meeting minutes that only record the content of the meeting process. The intercom content is integrated as a useful supplement and enhancement into the meeting minutes, ultimately forming new enhanced minutes and improving the effectiveness of the meeting minutes.

[0051] In this embodiment of the disclosure, when the Bluetooth connection of the electronic device is detected to be disconnected, it can automatically switch to the onboard 4G network to maintain the online function of the electronic device.

[0052] When an electronic device is engaged in continuous voice interaction (such as in conference mode or during long conversations), if the device's battery level is detected to be below a threshold, the sampling rate of the voice data will be automatically reduced or a low-power transmission method will be switched (such as switching from WiFi transmission to Bluetooth transmission) to prioritize the integrity of the voice data.

[0053] In this disclosure, voice can be processed differently according to the actual working state of the electronic device, so as to meet the different working modes of the same electronic device. This makes it convenient for users to use the same electronic device to complete multiple tasks in different scenarios, which is simple to operate and improves work efficiency.

[0054] This disclosure also provides a data processing apparatus. Figure 3 This is a schematic diagram of the structure of the data processing apparatus provided in the embodiments of this disclosure, such as... Figure 3 As shown, the device includes: Acquisition unit 301 is used to acquire voice data sent by electronic device; The determining unit 302 is used to determine the correlation between multiple voice data or the correlation between voice data and electronic devices based on the working modes of each electronic device; The processing unit 303 is used to process at least one voice data based on the correlation between multiple voice data or the correlation between voice data and electronic devices to obtain a target processing result.

[0055] In this embodiment of the disclosure, the electronic device can be a dual-modal voice interaction device that supports intelligent intercom and conference assistant, including an audio acquisition module and a transmission module. The audio acquisition module is used to acquire the user's voice data, and the transmission module is used to transmit the acquired voice data to the cloud or server.

[0056] In one embodiment, when various electronic devices join the same local area network or the same GPS fence, the electronic device with the best location is elected as the "master node". The master node determines in real time which electronic device has the best acquisition effect and then allows that device to upload the acquired audio data to the cloud or server.

[0057] In one embodiment, the electronic device further includes a display screen for displaying received voice data or text data converted from voice data in intercom mode; or for displaying the last generated meeting minutes in conference mode.

[0058] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0059] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0060] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0061] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 402 or a computer program loaded from storage unit 408 into random access memory (RAM) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0062] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0063] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as data processing methods. For example, in some embodiments, the data processing method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform data processing methods by any other suitable means (e.g., by means of firmware).

[0064] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0065] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0066] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0067] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0068] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0069] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0070] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0071] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0072] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A data processing method, comprising: Acquire voice data sent by electronic devices; Based on the operating modes of each of the electronic devices, the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, is determined; Based on the correlation between multiple voice data, or the correlation between the voice data and the electronic device, at least one of the voice data is processed to obtain the target processing result.

2. The method according to claim 1, The operating modes among the various electronic devices include a first mode; wherein, In the first mode, all the electronic devices are in the same session environment; Determining the correlation between multiple voice data based on the operating modes of each of the electronic devices includes: If the operating mode of each of the electronic devices is the first mode, the association relationship between each voice data is determined based on the session information between the electronic devices or the semantic information between each voice data as defined by the first mode.

3. The method according to claim 2, Based on the correlation between multiple voice data, at least one of the voice data is processed to obtain a target processing result, including: The speech data belonging to the same association are detected to obtain the speech quality detection result; Based on the speech quality detection results, target speech sub-data that meet the target quality conditions are determined in each speech data set; The target speech sub-data is processed to obtain the target processing result.

4. The method according to claim 2, Based on the correlation between multiple voice data, at least one of the voice data is processed to obtain a target processing result, including: All electronic devices are divided into multiple groups, and the target processing sub-results corresponding to each group are generated based on the voice data collected by the electronic devices in each group. The target processing sub-results corresponding to all groups are merged to generate the target processing result.

5. The method according to claim 1, The operating modes between the electronic devices include a second mode; wherein... In the second mode, each of the electronic devices sends target data to the target electronic device; Based on the operating modes of each of the electronic devices, the association between the voice data and the electronic devices is determined, including: If the electronic device is operating in the second mode, determine the target electronic device associated with the voice data.

6. The method according to claim 5, The step of processing at least one of the voice data based on the association between the voice data and the electronic device to obtain a target processing result includes: The voice data collected by the electronic device is processed into target data, and the target data is sent to the target electronic device; The modality of the target data matches the target state of the target electronic device.

7. The method according to claim 2, further comprising: When the operating mode of each electronic device is the first mode, the target processing result is sent to each electronic device. Obtain feedback data sent by any electronic device; Based on the feedback data, the target processing result is updated to obtain the target update result.

8. The method according to claim 1, Determining the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, based on the operating modes of each of the electronic devices, includes: Receive user operations, including a first operation and a second operation; In response to the user's operation being a first operation, the operating mode of each of the electronic devices is determined to be a first mode; based on the operating mode of each of the electronic devices being the first mode, the association relationship between the multiple voice data is determined; In response to the user's operation being a second operation, the operating mode of each of the electronic devices is determined to be a second mode; based on the operating mode of each of the electronic devices being the second mode, the association between the voice data and the electronic devices is determined.

9. A data processing apparatus, comprising: Acquisition unit, used to acquire voice data sent by electronic device; The determining unit is configured to determine the association relationship between multiple voice data, or the association relationship between the voice data and the electronic device, based on the operating modes of each of the electronic devices; The processing unit is configured to process at least one of the voice data based on the correlation between multiple voice data or the correlation between the voice data and the electronic device, so as to obtain a target processing result.

10. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the following method: Acquire voice data sent by electronic devices; Based on the operating modes of each of the electronic devices, the association between multiple voice data sets, or the association between the voice data sets and the electronic devices, is determined; Based on the correlation between multiple voice data, or the correlation between the voice data and the electronic device, at least one of the voice data is processed to obtain the target processing result.

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