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JP-7857339-B2 - Processing apparatus, processing method, and processing program

JP7857339B2JP 7857339 B2JP7857339 B2JP 7857339B2JP-7857339-B2

Inventors

  • 岩本　優
  • 吉田 徳太郎
  • 張 維烝
  • 川崎 啓介
  • 山田 雄基
  • 早田 孝
  • 森下 智之
  • 山下 祐貴

Assignees

  • ＮＴＴドコモビジネス株式会社

Dates

Publication Date
20260512
Application Date
20240522

Claims (9)

  1. An input control unit receives audio or text data from a user terminal and inputs it to a generation model for translation, which is configured with prompts that instruct the model to translate incoming audio or text data into a specified language in a natural context. A storage unit stores in a memory unit information related to business knowledge, which is extracted based on the translated audio data or text data output from the translation generation model in response to the input from the input control unit, The system includes an inquiry response unit which inputs an inquiry into an inquiry response generation model that has been set to prompt the generation model to generate an answer to a predetermined inquiry input by the user based on information about the business knowledge stored in the memory unit, translates the answer to the user's inquiry generated by the inquiry response generation model according to the language used by the user, and outputs it to the user. The aforementioned storage unit is Information relating to business knowledge, such as inquiries and corresponding answers concerning at least one of the following: business objectives, business procedures, instructions for using tools and systems, and troubleshooting, or information relating to business training that is the content of individual explanations, is stored in the memory unit . A processing apparatus characterized by the following:
  2. The aforementioned storage unit is The user-specific translation data is input to a generative model for extraction, which is configured with prompts that instruct the model to extract questions and corresponding answers from the voice data or text data, which are the user's natural language dialogue data. The questions extracted by the aforementioned generation model for extraction and the corresponding answers are associated and stored in the storage unit as information relating to the knowledge of the business. The apparatus according to claim 1.
  3. The aforementioned storage unit is The following steps are performed: A generative model for extraction, which is configured with prompts that instruct the model to extract information related to job training from the voice data or text data, which are natural language dialogue data of the user, is input with the translation data for each user. The information regarding the training of the business extracted by the aforementioned generation model is stored in the memory unit as information regarding the knowledge of the business. The apparatus according to claim 1.
  4. The aforementioned storage unit is The following steps are performed: A generative model for extraction, which is configured with prompts that instruct the model to extract information identifying the user who made the utterance from the voice data or text data, which are natural language dialogue data of the user, and information relating to the user's business knowledge, is input with the translation data for each user. The information identifying the user extracted by the extraction generation model is associated with the information relating to the user's business knowledge and stored in the storage unit. The apparatus according to claim 1.
  5. The system further includes a display unit that displays information relating to the knowledge of the business stored in the storage unit, associating questions with answers to those questions. The apparatus according to any one of claims 1 to 3.
  6. Based on pre-meeting information about meetings that pre-configured users will participate in, it is determined whether the meeting is in a specific field or a meeting where accuracy is paramount. Based on the determined results, select either the first generative model, which is a natural language processing model finely tuned for a specific field, or the second generative model, which is a large-scale natural language processing model. The selected generation model further includes a creation unit that creates prompts that instruct the model to translate the input audio data or text data into the language used by each user. The apparatus according to any one of claims 1 to 3.
  7. The aforementioned processing apparatus is The user terminal and each server device equipped with the generation model communicate via a communication network related to IOWN (Innovative Optical and Wireless Network). The apparatus according to any one of claims 1 to 3.
  8. A method of processing that a computer will execute, An input control step involves inputting audio or text data received from a user terminal to a generative translation model that has been configured with prompts instructing it to translate incoming audio or text data into a specified language in a natural context. A storage step involves storing information relating to business knowledge, extracted based on the translated audio data or text data output from the translation generation model in response to the input from the input control step, in a storage unit. A processing method comprising: an inquiry response step, in which an inquiry is input to an inquiry response generation model, which is set to have a prompt that instructs the generation model to generate an answer to a predetermined inquiry input by the user based on information regarding the business knowledge stored in the memory unit; and an inquiry is input to the user, the answer to the user's inquiry generated by the inquiry response generation model is translated according to the language used by the user and output to the user; The aforementioned storage process is, Information relating to business knowledge, such as inquiries and corresponding answers concerning at least one of the following: business objectives, business procedures, instructions for using tools and systems, and troubleshooting, or information relating to business training that is the content of individual explanations, is stored in the memory unit . Processing method.
  9. An input control step involves inputting audio or text data received from a user terminal into a generative translation model that has been configured with prompts instructing it to translate incoming audio or text data into a specified language in a natural context. A storage step involves storing information relating to business knowledge, extracted based on the translated audio data or text data output from the translation generation model in response to the input from the input control step, in a storage unit. A processing program that causes a computer to execute an inquiry response process, which includes: inputting an inquiry from the user into an inquiry response generation model that has been set with prompts instructing it to generate an answer to a predetermined inquiry input by the user based on information about the business knowledge stored in the memory unit; translating the answer to the user's inquiry generated by the inquiry response generation model according to the language used by the user; and outputting it to the user. The storage step is, Information relating to business knowledge, such as inquiries and corresponding answers concerning at least one of the following: business objectives, business procedures, instructions for using tools and systems, and troubleshooting, or information relating to business training that is the content of individual explanations, is stored in the memory unit . Processing program.

Description

This invention relates to a processing apparatus, a processing method, and a processing program. Traditionally, interpreting services utilizing human resources involved commissioning interpreters from specialized agencies for each type of interpreting service, with the interpreters contracted by those agencies performing the interpretation and the results being provided to the client. Furthermore, in recent years, various IT-based systems have been provided as interpretation systems, including automatic translation systems between languages, and systems that convert speech to text using speech recognition and speech synthesis technologies. Japanese Patent Publication No. 2022-003441Japanese Patent Publication No. 2019-139663 Figure 1 is a diagram showing an example of the configuration of a processing system according to the first embodiment.Figure 2 shows an overview of IOWN technology.Figure 3 illustrates an example of the use of the processing system according to the first embodiment.Figure 4 is a diagram illustrating the processing flow of the processing system.Figure 5 is a diagram illustrating the overview of the processing system.Figure 6 shows an example of pre-meeting information.Figure 7 is a diagram illustrating step S11 shown in Figure 5.Figure 8 is a diagram illustrating step S12 shown in Figure 5.Figure 9 is a diagram illustrating step S13 shown in Figure 5.Figure 10 is a diagram illustrating step S14 shown in Figure 5.Figure 11 is a diagram illustrating step S15 shown in Figure 5.Figure 12 is a diagram illustrating step S16 shown in Figure 5.Figure 13 is a diagram illustrating step S17 shown in Figure 5.Figure 14 is a diagram illustrating the processing of the processing system.Figure 15 shows another example of the prompt creation process.Figure 16 shows another example of the prompt creation process.Figure 17 shows another example of the prompt creation process.Figure 18 illustrates another example of the processing system's use.Figure 19 illustrates another example of the processing system's use.Figure 20 is a diagram illustrating the overview of the task management support process of the processing system.Figure 21 is an example of a sequence diagram showing the processing procedure of the processing method according to the first embodiment.Figure 22 is an example of a sequence diagram showing the processing procedure of another processing method according to the first embodiment.Figure 23 is a diagram comparing a conventional translation service with a simultaneous interpretation service provided by the processing system according to the first embodiment.Figure 24 is a diagram comparing a conventional translation service with a simultaneous interpretation service provided by the processing system according to the first embodiment.Figure 25 is a diagram illustrating the processing of the processing system according to the second embodiment.Figure 26 is a diagram showing the configuration of a processing system according to the second embodiment.Figure 27 is a diagram illustrating an example of processing by the processing system according to the second embodiment.Figure 28 is a diagram illustrating an example of processing by the processing system according to the second embodiment.Figure 29 is a diagram illustrating an example of processing by the processing system according to the second embodiment.Figure 30 is a sequence diagram showing the processing procedure according to the second embodiment.Figure 31 is a sequence diagram showing the processing procedure according to the second embodiment.Figure 32 is a sequence diagram showing the processing procedure according to the second embodiment.Figure 33 is a diagram illustrating the processing of the processing system according to the third embodiment.Figure 34 shows the configuration of the processing system according to the third embodiment.Figure 35 is a diagram illustrating an example of processing by the processing system according to the third embodiment.Figure 36 is a sequence diagram showing the processing procedure according to the third embodiment.Figure 37 is a diagram illustrating the processing of the processing system according to the fourth embodiment.Figure 38 shows the configuration of the processing system according to the fourth embodiment.Figure 39 is a table diagram showing an example of information relating to business knowledge that has undergone a predetermined correspondence process according to the fourth embodiment.Figure 40 is a diagram illustrating an example of processing by the processing system according to the fourth embodiment.Figure 41 is a diagram illustrating an example of processing by the processing system according to the fourth embodiment.Figure 42 is a sequence diagram showing the processing procedure according to the fourth embodiment.Figure 43 is a sequence diagram showing the processing procedure according to the fourth embodiment.Figure 44 is a diagram illustrating the processing of the proce