Method, device and equipment for processing audio file based on large model and storage medium

Abstract

The invention provides a method, a device and equipment for processing an audio file based on a large model, and a storage medium, and relates to the technical field of artificial intelligence such as voice technology and natural language processing. The specific implementation scheme is as follows: acquiring an input audio file in an interactive interface based on a large model; based on the large model, identifying the audio file, and obtaining and displaying identification information in the interactive interface; and based on the large model, analyzing the identification information, and obtaining and displaying an analysis result in the interactive interface. According to the technology disclosed by the invention, the functions of the AI product can be effectively enriched; the accuracy and the effectiveness of processing the audio file by the AI product can be improved; and the operation complexity of the user in the interaction process based on the large model can be effectively reduced, and the user experience is further effectively improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, specifically to artificial intelligence technologies such as audio processing technology and natural language processing, and particularly to a method, apparatus, device, and storage medium for processing audio files based on a large model. Background Art

[0002] In recent years, with the rapid development of artificial intelligence (AI) technology, more and more AI Q&A products have emerged, which can greatly facilitate people's learning and life.

[0003] Currently, the AI Q&A products on the market mainly support text or real-time voice conversations. Users input questions in text or voice format to the AI Q&A products, and the AI Q&A products can reply to users with answers in text or voice format, which is very convenient to use. Summary of the Invention

[0004] The present disclosure provides a method, apparatus, electronic device, and storage medium for processing audio files based on a large model.

[0005] According to one aspect of the present disclosure, there is provided a method for processing an audio file based on a large model, including:

[0006] Obtaining an input audio file in an interaction interface based on the large model;

[0007] Based on the large model, identifying the audio file, obtaining and displaying identification information in the interaction interface;

[0008] Based on the large model, analyzing the identification information, obtaining and displaying an analysis result in the interaction interface.

[0009] According to another aspect of the present disclosure, there is provided an apparatus for processing an audio file based on a large model, including:

[0010] A first obtaining module, configured to obtain an input audio file in an interaction interface based on the large model;

[0011] A first interaction module, configured to identify the audio file based on the large model, obtain and display identification information in the interaction interface;

[0012] A second interaction module, configured to analyze the identification information based on the large model, obtain and display an analysis result in the interaction interface. According to still another aspect of the present disclosure, there is provided an electronic device, including:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the methods of the aspects and any possible implementations described above.

[0016] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the methods of the aspects and any possible implementations described above.

[0017] According to still another aspect of the present disclosure, there is provided a computer program product including a computer program which, when executed by a processor, implements the methods of the aspects and any possible implementations described above.

[0018] According to the technology of the present disclosure, it is possible to effectively enrich the functions of AI products; moreover, it can also improve the accuracy and effectiveness of AI products in processing audio files; it can also effectively reduce the operation complexity of users during the interaction process based on large models, and further effectively enhance the user experience.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0021] Figure 1 is a schematic diagram according to the first embodiment of the present disclosure;

[0022] Figure 2 is a schematic diagram according to the second embodiment of the present disclosure;

[0023] Figure 3 is a schematic diagram of an interaction interface provided by the present disclosure;

[0024] Figure 4 is another schematic diagram of an interaction interface provided by the present disclosure;

[0025] Figure 5 is a schematic diagram according to the third embodiment of the present disclosure;

[0026] Figure 6 is a schematic diagram according to the fourth embodiment of the present disclosure;

[0027] Figure 7 is a schematic diagram according to the fifth embodiment of the present disclosure;

[0028] Figure 8 is a schematic diagram according to the sixth embodiment of the present disclosure;

[0029] Figure 9 is a block diagram of an exemplary electronic device for implementing the embodiments of the present disclosure. Detailed implementation manners

[0030] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well-known functions and structures are omitted in the following description for clarity and conciseness.

[0031] Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts belong to the scope of protection of the present disclosure.

[0032] It should be noted that the terminal devices involved in the embodiments of the present disclosure may include, but are not limited to, intelligent devices such as mobile phones, personal digital assistants (PDAs), wireless handheld devices, and tablet computers; the display devices may include, but are not limited to, devices with display functions such as personal computers and televisions.

[0033] In addition, the term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0034] Figure 1 is a schematic diagram according to the first embodiment of the present disclosure; as Figure 1 shown, this embodiment provides a method for processing an audio file based on a large model, which may specifically include the following steps:

[0035] S101. Obtain the input audio file in the interaction interface based on the large model;

[0036] S102. Based on the large model, identify the audio file, and obtain and display the identification information in the interaction interface;

[0037] S103. Analyze the recognition information based on the large model, and obtain and display the analysis result in the interaction interface.

[0038] The execution subject of this embodiment is a device for processing audio files based on a large model, and this device can be set in various AI products such as AI assistants or AI Q&A products.

[0039] In the scenario of this embodiment, when the user is using it, they can upload an audio file in the interaction interface to achieve the input of the audio file. Then, based on the large model, the audio file can be recognized to obtain the corresponding recognition information, and the recognized recognition information is displayed in the interaction interface. In this embodiment, the large model can further analyze the recognition information to obtain the analysis result, and at the same time, the analysis result is also displayed in the interaction interface.

[0040] The method for processing audio files based on a large model in this embodiment, by adopting the above technical solution, can provide the processing of audio files in various AI products such as AI Q&A products or AI assistants. It can not only automatically and intelligently recognize and display the recognition information of the audio file based on the large model, but also intelligently analyze the recognition information based on the large model and display the analysis result, which can effectively enrich the functions of AI products; moreover, it can also improve the accuracy and effectiveness of AI products in processing audio files. Furthermore, the technical solution of this embodiment can also effectively reduce the operation complexity of users in obtaining information such as audio analysis, and further effectively improve the user experience.

[0041] Figure 2 It is a schematic diagram according to the second embodiment of the present disclosure; the method for processing audio files based on a large model in this embodiment further introduces the technical solution of the present disclosure in more detail on the basis of the technical solution of the above Figure 1 shown embodiment. As Figure 2 shown, the method for processing audio files based on a large model in this embodiment can specifically include the following steps:

[0042] S201. In the interaction interface based on the large model, obtain the input audio file;

[0043] S202. Based on the large model, recognize the audio file, and obtain and display at least one first speech message in the interaction interface. Each first speech message includes: a speaker identification, a first start timestamp of the speaker's speech, and a first text of the speaker's speech;

[0044] The technical solution of this embodiment can be applied to various scenarios such as meeting records, education and training, and interview arrangement. The audio file can include one, two, or multiple speakers. The speakers in this embodiment can be people, or other cartoon animals in anime that can imitate human voices.

[0045] In this embodiment, the large model can intelligently identify the voices of each speaker, and then identify the speakers. The audio file in this embodiment may include one, two or more speakers, and each speaker may speak once, twice or more times. Correspondingly, the audio file may include one, two or more first speech messages. When the large model is identifying the audio file, it can sequentially identify each first speech message in the order from front to back. Each first speech message may include: a speaker identification, a first start timestamp of the speaker's speech, and a first text of the speaker's speech.

[0046] For each first speech message, the identification of the speaker therein is an identification that can uniquely identify the speaker marked by the large model based on the speaker's voice. For example, it can be identified in the order of speaker 1, speaker 2, speaker 3, etc.

[0047] The first start timestamp of the speaker in the first speech message is the starting speech moment of the speaker in this first speech message.

[0048] The first text in the first speech message is the text content corresponding to the speaker's speech in this first speech message.

[0049] In this embodiment, taking at least one first speech message in the identification information obtained by the large model for intelligent information identification as an example. In practical applications, the identification information can also adopt other formats, which are not limited herein.

[0050] Preferably, in an embodiment of the present disclosure, multiple first speech messages may be displayed in the interaction interface in the order of the first start timestamps in the audio file to implement the display of the identification information.

[0051] S203. Display an audio player in the interaction interface, and the audio player is used to play the audio file;

[0052] To facilitate the user to listen to the audio file subsequently, in this embodiment, an audio player may also be set in the interaction interface, and the user can directly play the uploaded audio file by clicking on the player.

[0053] S204. Based on each first speech message, use the large model to mine the summary of the audio file; and display the summary of the audio file in the interaction interface;

[0054] S205. Based on each first speech message, use the large model to mine at least one first speech topic and the second start timestamp of each first speech topic; and display each first speech topic and the corresponding second start timestamp in the interaction interface;

[0055] S206. Establish the mapping relationship between each first speaking topic and the corresponding first speaking information.

[0056] In this embodiment, usually, one first speaking information may include one first speaking topic, and different first speaking information may correspond to the same first speaking topic. Therefore, in the mapping relationship, one first speaking topic may correspond to at least one first speaking information.

[0057] When specifically implemented, the large model may analyze the first text in each first speaking information corresponding to the audio file in the order from front to back to obtain the corresponding speaking topic. The speaking topic of each first text may be a paragraph of text or multiple keywords. And it is detected whether the speaking topic of the current first text is the same as the speaking topic of the first text in the nearest previous first speaking information; if they are the same, they are classified into the same speaking topic, if not, the current first text is classified into another speaking topic; at this time, based on multiple first texts belonging to the same speaking topic before the current first text, the final speaking topic may be generated. And continue to analyze each subsequent first text until the detection is completed. Finally, it can be realized that multiple first speaking information are divided into at least one first speaking topic, and the text content of each first speaking topic can be generated, that is, the content of the speaking topic is obtained.

[0058] Of course, optionally, in some scenarios, one first speaking information may also correspond to more than two first speaking topics. At this time, the analysis granularity may be for each sentence in the first text of each first speaking information, and the analysis principle is the same and will not be elaborated here.

[0059] In this embodiment, taking the analysis result including not only the summary of the audio file but also the speaking topic of the audio file as an example. Further, the analysis result of this embodiment may also include the mapping relationship between the first speaking topic and the corresponding first speaking information, but this analysis result is convenient for subsequent retrieval of speaking information based on the speaking topic and does not need to be displayed on the interaction interface.

[0060] It should be noted that the interaction interface of this embodiment may include: a file information area for displaying at least one of the recognition information and the analysis information, and a question and answer area for interacting based on the large model. For example, Figure 3 is a schematic diagram of an interaction interface provided by the present disclosure. As Figure 3 shown, the left side of the interaction interface may be a file information area for displaying the recognition information, such as Figure 3As shown, taking the display of three first speech messages as an example, the first first speech message includes the speaker object 1, the first start timestamp XX:XX, and the corresponding first text. The second first speech message includes the speaker object 2, the first start timestamp YY:YY, and the corresponding first text. The third first speech message includes the speaker object 3, the first start timestamp ZZ:ZZ, and the corresponding first text, and so on. The right side of the interaction interface can be a Q&A area. For example, the upload of the above audio file and the display of the summary of the audio file can also be in the Q&A area.

[0061] For example, in this embodiment, the recognition information and analysis information displayed in the file information area can be presented using different interfaces. For example Figure 3 As shown, the page to be displayed can be selected in the upper left corner. When the recognition information is selected, the display interface is as Figure 3 shown. Specifically, multiple first speech messages included in the audio file can be displayed. Each first speech message can include a speaker object identifier, the first start timestamp of the speaker's speech, and the first text of the speaker's speech. As Figure 4 shown, when the analysis information such as the speech topic is selected in the upper left corner, the display interface at this time is as Figure 4 shown, displaying at least one first speech topic of the audio file, and the second start timestamp of each first speech topic. As Figure 4 shown, taking the display of two first speech topics as an example.

[0062] In addition, optionally, as Figure 3 and 4 shown, an audio player can be specifically set and displayed below the file information area. The audio player is used to play the audio file.

[0063] The method for processing an audio file based on a large model in this embodiment, by adopting the above technical solution, can intelligently identify the first speech messages in the audio file and display them. It can also intelligently analyze the summary of the audio file and the first speech topics and display them, effectively improving the processing ability of the large model product for the audio file.

[0064] Moreover, a mapping relationship between each first speech topic and the corresponding first speech message can be established, providing effective support for retrieval based on the first speech topic, and further effectively enhancing the performance of the large model product in processing audio files.

[0065] Figure 5 is a schematic diagram according to the third embodiment of the present disclosure; the method for processing an audio file based on a large model in this embodiment further describes the technical solution of the present disclosure in more detail on the basis of the technical solution of the above Figure 2 shown embodiment. As Figure 5As shown in the figure, in this embodiment, the following steps may further be included:

[0066] S501. In response to detecting a processing request for a second speech topic in the first speech topic, based on a pre-established mapping relationship, obtain second speech information corresponding to the second speech topic;

[0067] S502. In the interaction interface, prominently display the second speech information;

[0068] The technical solution of this embodiment can be an application scenario based on the technical solution of the above Figure 2 shown embodiment.

[0069] For example, when the user can select a second speech topic from at least one first speech topic in the Figure 4 shown interaction interface and request to view relevant content, at this time, the device for processing the audio file based on the large model can, based on the mapping relationship established in step S206 of the above Figure 2 shown embodiment, obtain the second speech information corresponding to the second speech topic. Specifically, the number of second speech information corresponding to the second speech topic can also be one, two, or multiple.

[0070] Alternatively, optionally, the user can also input an operation to view relevant content for the second speech topic in the first speech topic in the Q&A area. At this time, the implementation principle is similar.

[0071] In this embodiment, after the audio file is recognized, that is, after step S202 of the above Figure 2 shown embodiment, at least one first speech information has been displayed in the interaction interface. At this time, in order to clearly display the second speech information corresponding to the second speech topic to the user, at this time, the second speech information can be prominently displayed in the interaction interface.

[0072] To avoid multiple prominent displays of multiple processing requests interfering with each other, in this embodiment, a preset duration can be set for each prominent display corresponding to a processing request, and the length of the preset duration can be set according to actual experience or requirements. For example, it can be highlighted for a duration of 1s, 2s, etc.

[0073] For example, in Figure 4In the displayed file information area and the speech topic interface, the user can see the titles of multiple first speech topics shown, the topic content of each first speech topic, etc. If the user wants to view the relevant content of the second speech topic among the multiple first speech topics, the user can click on the second speech topic in this interface. At this time, a menu can pop up, and the menu can include functions such as copy and view speech information. At this time, the user can choose to view the speech information. At this time, the device for processing audio files based on a large model can, according to the processing request selected by the user and based on the pre-established mapping relationship, in Figure 3 the interface of the identification information in the displayed file information area, determine the second speech information corresponding to the second speech topic, and highlight the second speech information in a pre-set manner. For example, the background color block of the second speech information can be faded in for 0.3 seconds and faded out for 0.3 seconds to achieve highlighting through a flashing animation effect, so as to remind the user to focus their sight on this position, so that the user can see the second speech information corresponding to the second speech topic.

[0074] In the above example, the highlighting is achieved through a flashing animation effect. In actual application scenarios, other highlighting methods can also be used, which are not limited here.

[0075] S503. Obtain the audio segment corresponding to the second speech information in the audio file according to the processing request;

[0076] S504. Perform the response operation corresponding to the processing request on the audio segment.

[0077] For example, the response operations in this embodiment can include the following two methods:

[0078] The first method is to obtain the starting playback moment of the audio segment. Based on the starting playback moment of the audio segment, control the playback progress of the audio player for the audio file, so that when the user clicks to play, the audio player just starts to play this audio segment, effectively enhancing the practicality.

[0079] In this implementation method, if the second speech topic corresponds to more than two pieces of second speech information, the audio segments obtained from the audio file should be two or more audio segments corresponding to two or more pieces of second speech information. At this time, the playback of the audio player can be controlled based on the starting playback moments of each audio segment in sequence.

[0080] The second method is to push the audio segment on the interaction interface. At this time, the user can directly click on the audio segment to also listen to the corresponding audio content.

[0081] In this implementation manner, when there are more than two pieces of second speech information corresponding to the second speech topic, when pushing on the interaction interface, two or more audio segments can be pushed in sequence; or two or more audio segments can be merged together for pushing. By adopting the above two methods, both can accurately and effectively respond to the processing request.

[0082] The method for processing an audio file based on a large model in this embodiment can effectively reduce the operation complexity of the user and improve the user experience by highlighting the second speech information corresponding to the second speech topic in the first speech topic in response to the processing request based on the pre-established mapping relationship.

[0083] Furthermore, in this embodiment, it is also possible to timely and accurately respond to the processing request related to the speech topic by using audio segments, so that the user can timely and accurately understand the content of the original audio corresponding to the processing request, and at the same time, while improving the interaction diversity, it reduces the operation complexity of the user and improves the user experience.

[0084] Figure 6 It is a schematic diagram according to the fourth embodiment of the present disclosure; the method for processing an audio file based on a large model in this embodiment further describes the technical solution of the present disclosure in more detail on the basis of the technical solution of the above Figure 2 shown embodiment. As Figure 6 shown, in this embodiment, the following steps may further be included:

[0085] S601. In response to detecting a processing request for the second text in the first text, use a large model to obtain the start playback moment of the second text in the audio file;

[0086] S602. Based on the start playback moment, control the audio player to play the playback progress of the audio file.

[0087] The technical solution of this embodiment can be an application scenario based on the technical solution of the above Figure 2 shown embodiment.

[0088] For example, after recognizing the audio file, that is, the above Figure 2After step S202 of the illustrated embodiment, at least one first speech message has been displayed on the interaction interface. When using it, the user can select and click to play the second text in the first text of any first speech message. The second text can be a segment of any length in the first text. At this time, by using a large model, the starting playback moment of the second text in the audio file can be obtained. For example, the large model can obtain the first start timestamp corresponding to the first text to which the second text belongs, the first start timestamp of the next first text after the first text to which the second text belongs, the total length of the first text to which the second text belongs, and the position of the second text in the first text, etc., and accurately determine the starting playback moment of the second text in the audio file. Then, based on the starting playback moment, the playback progress of the audio file is controlled to play the audio content corresponding to the second text when the user clicks the player.

[0089] The method for processing an audio file based on a large model in this embodiment can also, for a text-related processing request, obtain the starting playback moment of the text in the audio file, and accurately and effectively control the playback progress of the audio player to play the audio file, enabling the user to timely and accurately understand the content of the original audio corresponding to the text processing request. It can also, while enhancing the interaction diversity, reduce the operation complexity of the user and improve the user experience.

[0090] Figure 7 is a schematic diagram according to the fifth embodiment of the present disclosure; as Figure 5 As shown, the apparatus 700 for processing an audio file based on a large model in this embodiment includes:

[0091] An acquisition module 701, configured to acquire an input audio file in an interaction interface based on a large model;

[0092] An interaction module 702, configured to identify the audio file based on the large model, and acquire and display identification information in the interaction interface;

[0093] The interaction module 702 is further configured to analyze the identification information based on the large model, and obtain and display an analysis result in the interaction interface.

[0094] The apparatus 700 for processing an audio file based on a large model in this embodiment realizes the principle and technical effects of processing an audio file based on a large model by using the above modules, which is the same as the implementation of the above related method embodiments. For details, reference can be made to the records of the above related method embodiments, and details will not be repeated here.

[0095] Figure 8 is a schematic diagram according to the sixth embodiment of the present disclosure; as Figure 8As shown, the apparatus 800 for processing an audio file based on a large model in this embodiment further introduces the technical solution of the present disclosure in more detail on the basis of the technical solution of the above Figure 7 shown embodiment. As Figure 8 shown, the apparatus 800 for processing an audio file based on a large model in this embodiment includes the same-name and same-function modules as those in the above Figure 7 shown: an acquisition module 801 and an interaction module 802.

[0096] In this embodiment, the recognition information includes at least one piece of first speech information, and each piece of the first speech information includes: a speaker object identifier, a first start timestamp of the speaker object's speech, and a first text of the speaker object's speech.

[0097] The interaction module 802 is configured to:

[0098] Display the recognition information in the interaction interface in the order of the first start timestamps in the audio file.

[0099] Further optionally, as Figure 8 shown, in an embodiment of the present disclosure, the apparatus 800 for processing an audio file based on a large model further includes:

[0100] The interaction module 802 is further configured to display an audio player in the interaction interface, and the audio player is used to play the audio file.

[0101] Further optionally, as Figure 8 shown, in an embodiment of the present disclosure, the apparatus 800 for processing an audio file based on a large model further includes a control module 803;

[0102] The interaction module 802 is further configured to, in response to detecting a processing request for a second text in the first text, use the large model to obtain a start playback moment of the second text in the audio file;

[0103] The control module 803 is configured to control the playback progress of the audio file played by the audio player based on the start playback moment.

[0104] Further optionally, in an embodiment of the present disclosure, the analysis result includes: a first speech topic and a second start timestamp of the first speech topic;

[0105] The established mapping relationship between the first speech topic and the corresponding first speech information.

[0106] Further optionally, as Figure 8 shown, in an embodiment of the present disclosure, the apparatus 800 for processing an audio file based on a large model further includes:

[0107] An acquisition module 801, configured to, in response to detecting a processing request for a second speech topic in the first speech topic, acquire second speech information corresponding to the second speech topic based on the pre-established mapping relationship;

[0108] An interaction module 802 is further configured to prominently display the second speech information in the interaction interface.

[0109] Further optionally, as Figure 8 shown, in an embodiment of the present disclosure, the apparatus 800 for processing an audio file based on a large model further includes a response module 804:

[0110] An acquisition module 801, configured to acquire an audio segment corresponding to the second speech information in the audio file according to the processing request;

[0111] A response module 804, configured to perform a response operation corresponding to the processing request on the audio segment by a user.

[0112] Further optionally, in an embodiment of the present disclosure, the analysis result further includes: a summary of the audio file mined based on each piece of the first speech information.

[0113] Further optionally, as Figure 8 shown, in an embodiment of the present disclosure, the interaction interface includes: a file information area for displaying at least one of the recognition information and the analysis information, and a question-and-answer area for interaction based on a large model.

[0114] The apparatus 800 for processing an audio file based on a large model in this embodiment realizes the implementation principle and technical effects of processing an audio file based on a large model by using the above modules, which is the same as the implementation of the above related method embodiments. For details, reference can be made to the records of the above related method embodiments, and details will not be repeated here.

[0115] In the technical solution of the present disclosure, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0116] According to the embodiments of the present disclosure, the present disclosure further provides an electronic device, a readable storage medium, and a computer program product.

[0117] Figure 9FIG. 0 shows a schematic block diagram of an exemplary electronic device 900 that can be used to implement embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0118] As Figure 9 shown, the device 900 includes a computing unit 901 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0119] A plurality of components in the device 900 are connected to the I / O interface 905, including: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; a storage unit 908, such as a magnetic disk, an optical disk, etc.; and a communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 909 allows the device 900 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0120] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated 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 901 executes the various methods and processes described above, such as the above methods of the present disclosure. For example, in some embodiments, the above methods of the present disclosure can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the above methods of the present disclosure described above can be executed. Alternatively, in other embodiments, the computing unit 901 can be configured to execute the above methods of the present disclosure by any other suitable means (e.g., by means of firmware).

[0121] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-a-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0122] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0123] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, 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 a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0124] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, speech input, or tactile input).

[0125] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0126] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, can also be a server of a distributed system, or a server incorporating a blockchain.

[0127] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution disclosed in the present disclosure can be achieved, and no limitation is imposed herein.

[0128] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A method for processing an audio file based on a large model, comprising: In an interaction interface based on a large model, obtaining an input audio file; Based on the large model, identifying the audio file, obtaining and displaying identification information in the interaction interface; Based on the large model, analyzing the identification information, obtaining and displaying an analysis result in the interaction interface.

2. The method according to claim 1, wherein The identification information includes at least one first speech message, and each first speech message includes: a speaker identification, a first start timestamp of the speaker's speech, and a first text of the speaker's speech. The step of, based on the large model, identifying the audio file, obtaining and displaying identification information in the interaction interface, includes: Displaying the identification information in the interaction interface in the order of the first start timestamps in the audio file.

3. The method according to claim 2, wherein After obtaining the input audio file in the interaction interface based on the large model, the method further includes: Displaying an audio player in the interaction interface, where the audio player is used to play the audio file.

4. The method according to claim 3, wherein The method further includes: In response to detecting a processing request for a second text in the first text, using the large model to obtain a start playback moment of the second text in the audio file; Based on the start playback moment, controlling the audio player to play the playback progress of the audio file.

5. The method according to claim 4, wherein, The analysis result includes: a first speech topic and a second start timestamp of the first speech topic; The established mapping relationship between the first speech topic and the corresponding first speech message.

6. The method according to claim 5, wherein The method further includes: In response to detecting a processing request for a second speech topic in the first speech topic, based on the pre-established mapping relationship, obtaining the second speech message corresponding to the second speech topic; In the interaction interface, prominently displaying the second speech message.

7. The method according to claim 6, wherein, The method further includes: According to the processing request, obtaining an audio segment corresponding to the second speech message in the audio file; Performing a response operation corresponding to the processing request on the audio segment.

8. The method according to any one of claims 2-7, wherein, The analysis result further includes: a summary of the audio file mined based on each first speech message.

9. According to the method as claimed in any one of claims 1-7, wherein, The interaction interface includes: a file information area for displaying at least one of the identification information and the analysis information, and a question-and-answer area for interaction based on the large model.

10. An apparatus for processing an audio file based on a large model, comprising: A first acquisition module for obtaining an input audio file in an interaction interface based on a large model; A first interaction module for identifying the audio file based on the large model, obtaining and displaying identification information in the interaction interface; A second interaction module for analyzing the identification information based on the large model, obtaining and displaying an analysis result in the interaction interface.

11. An electronic device, comprising: 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, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-9.

12. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-9.

13. A computer program product, comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-9.

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