Information processing device, output method, and output program

Abstract

The information processing device (100) has an acquisition unit (120) that acquires voice data of a customer, a voice recognition execution unit (130) that executes voice recognition using the voice data, a determination unit (140) that, when the content of the data acquired by the voice recognition is a question, determines whether the content of the data is a frequently asked question, and an output unit (150). When the content of the data is a frequently asked question, the acquisition unit (120) acquires an answer corresponding to the question that is the content of the data. The output unit (150) outputs the question and the answer to the display device (200).

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an output method, and an output program. [Background technology]

[0002] At stations and other places, ticket counters are installed. When a customer comes to the ticket counter, a staff member provides guidance, etc. Here, a technique for analyzing the tendency of customer inquiries has been proposed (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2009 / 107211 Summary of the Invention [Problem to be solved by the invention]

[0004] Various customers come to the counter. Various customers may ask the clerk similar questions. It is a burden for the clerk to answer the similar questions every time.

[0005] An object of the present disclosure is to reduce the burden on staff. [Means for solving the problem]

[0006] According to one aspect of the present disclosure, there is provided an information processing device. The information processing device is a device capable of outputting information to a display device. The information processing device includes: The combined data is data that combines multiple voice data of a customer and also combines data that has a related meaning. The acquisition unit to acquire ,before Note join The data acquisition unit includes a determination unit that determines whether the content of the data is a frequently asked question, and an output unit. join If the data is about frequently asked questions, join The output unit outputs the question and the answer to the display device. Effect of the Invention

[0007] According to the present disclosure, the burden on staff can be reduced. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 illustrates a provision system according to a first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating hardware included in an information processing device according to the first embodiment. [Diagram 3] 1 is a block diagram showing functions of an information processing device according to a first embodiment; [Figure 4] 4 is a flowchart showing an example of processing executed by the information processing device according to the first embodiment. [Diagram 5] FIG. 11 is a block diagram showing the functions of an information processing device according to a second embodiment. [Figure 6] 13 is a flowchart showing an example of processing executed by an information processing device according to the second embodiment. [Figure 7] FIG. 11 is a diagram illustrating an example of a management table according to the second embodiment. [Figure 8] FIG. 11 is a block diagram showing the functions of an information processing device according to a third embodiment. [Figure 9] 13 is a flowchart showing an example of processing executed by an information processing device according to a third embodiment. [Figure 10] FIG. 13 is a diagram illustrating an example of a management table according to the third embodiment. [Figure 11] FIG. 13 is a block diagram showing the functions of an information processing device according to a fourth embodiment. [Figure 12] 13 is a flowchart showing an example (part 1) of a process executed by an information processing device according to the fourth embodiment. [Figure 13] 13 is a flowchart showing a second example of the process executed by the information processing device according to the fourth embodiment. [Figure 14] 13 is a flowchart showing an example (part 1) of a process executed by an information processing device according to the first modification of the fourth embodiment. [Figure 15]13 is a flowchart showing a second example of the process executed by the information processing device of the first modification of the fourth embodiment. [Figure 16] 13 is a flowchart showing an example (part 1) of a process executed by an information processing device according to Modification 2 of the fourth embodiment. [Figure 17] 13 is a flowchart showing a second example of the process executed by the information processing device of the second modification of the fourth embodiment. [Figure 18] FIG. 13 is a diagram showing a provision system according to a fifth embodiment. [Figure 19] 13 is a flowchart showing an example of processing executed by an information processing device according to a fifth embodiment. [Figure 20] 13 is a flowchart showing an example of processing executed by an information processing device according to Modification 1 of Embodiment 5. [Figure 21] FIG. 23 is a block diagram showing the functions of an information processing device according to a sixth embodiment. [Figure 22] 23 is a flowchart showing an example of processing executed by an information processing device according to a sixth embodiment. [Diagram 23] FIG. 23 is a diagram illustrating an example of a management table according to the sixth embodiment. [Figure 24] 23 is a flowchart showing an example of processing executed by an information processing device according to the first modification of the sixth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment will be described with reference to the drawings. The following embodiment is merely an example, and various modifications are possible within the scope of the present disclosure.

[0010] Embodiment 1 1 is a diagram showing a provision system according to the first embodiment. The provision system includes an information processing device 100, a display device 200, and a microphone 300. The information processing device 100, the display device 200, and the microphone 300 are connected via a network. The network may be a wired network or a wireless network.

[0011] The information processing device 100 is a device that executes an output method and is capable of outputting information to the display device 200. The display device 200 is a device that displays information. For example, the display device 200 is a signage, a projector, etc. The display device 200 is installed in stations, tourist spots, commercial facilities, etc.

[0012] For example, microphone 300 is installed at a counter at a station, a tourist spot, a commercial facility, etc. A customer's voice is input to microphone 300. Also, the voice of an attendant may be input to microphone 300. When the attendant's voice is input to microphone 300, information processing device 100 has a function of distinguishing between the attendant's voice data and the customer's voice data. Note that the attendant is an attendant present at a station, a tourist spot, a commercial facility, etc.

[0013] Next, the hardware of the information processing device 100 will be described. 2 is a diagram showing hardware included in the information processing device of embodiment 1. The information processing device 100 is a computer. The information processing device 100 includes a processor 101, a volatile storage device 102, and a non-volatile storage device 103.

[0014] The processor 101 controls the entire information processing device 100. For example, the processor 101 is a central processing unit (CPU) or a field programmable gate array (FPGA). The processor 101 may be a multiprocessor. The information processing device 100 may also include a processing circuit.

[0015] The volatile storage device 102 is a main storage device of the information processing device 100. For example, the volatile storage device 102 is a random access memory (RAM). The non-volatile storage device 103 is an auxiliary storage device of the information processing device 100. For example, the non-volatile storage device 103 is a hard disk drive (HDD) or a solid state drive (SSD).

[0016] Next, functions of the information processing device 100 will be described. 3 is a block diagram showing functions of the information processing device of embodiment 1. The information processing device 100 includes a storage unit 110, an acquisition unit 120, a voice recognition execution unit 130, a determination unit 140, and an output unit 150.

[0017] The storage unit 110 may be realized as a storage area secured in the volatile storage device 102 or the non-volatile storage device 103 . Some or all of the acquisition unit 120, the voice recognition execution unit 130, the determination unit 140, and the output unit 150 may be realized by a processing circuit. Also, some or all of the acquisition unit 120, the voice recognition execution unit 130, the determination unit 140, and the output unit 150 may be realized as modules of a program executed by the processor 101. For example, the program executed by the processor 101 is also called an output program. For example, the output program is recorded on a recording medium.

[0018] Various information is stored in the storage unit 110. The functions of the acquisition unit 120, the voice recognition execution unit 130, the determination unit 140, and the output unit 150 will be described in detail later.

[0019] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. FIG. 4 is a flowchart illustrating an example of processing executed by the information processing device according to the first embodiment. (Step S11) The acquisition unit 120 acquires voice data of a customer. For example, the acquisition unit 120 acquires the voice data from the microphone 300. The acquisition unit 120 may also acquire the voice data from the microphone 300 via an external device. The external device is a device that exists outside the information processing device 100. For example, the external device is a cloud server. Note that a diagram of the external device is omitted. The voice data may also be called a voice signal.

[0020] (Step S12) The voice recognition execution unit 130 executes voice recognition using the voice data, thereby allowing the information processing device 100 to obtain data that is a character string.

[0021] (Step S13) The determination unit 140 determines whether the content of the data obtained by the voice recognition is a question. For example, the determination unit 140 uses a rule base to determine whether the content of the data is a question. For example, a method using a rule base is a method using a dictionary, a method using regular expressions, etc. Also, for example, the determination unit 140 uses a trained model to determine whether the content of the data is a question. The trained model can be created by machine learning such as a deep neural network (DNN). For example, in machine learning, a large amount of character strings are prepared as input data. Training data is prepared in which the character string of the input data is a question and the correct answer label is set. Then, the trained model is created by performing machine learning using the input data and the training data so that the determination result, which is output data of the trained model, matches the correct answer label. If the content of the data is a question, the process proceeds to step S14. If the content of the data is not a question, the process ends.

[0022] (Step S14) The determination unit 140 determines whether the content of the data is a frequently asked question. For example, the determination unit 140 makes the determination as follows. The memory unit 110 stores the number of times that the information processing device 100 has acquired a question that is the same as or similar to the data. In other words, the memory unit 110 stores the number of times that the information processing device 100 has acquired a similar question. The determination unit 140 increments the number of times. If the number of times is equal to or greater than a predetermined threshold, the determination unit 140 determines that the content of the data is a frequently asked question. If the condition is met, the process proceeds to step S15, otherwise the process ends.

[0023] (Step S15) The acquiring unit 120 acquires an answer corresponding to the content of the data (that is, the question) from the storage unit 110 or an external device. (Step S16) Output unit 150 outputs the question and answer to display device 200. Output unit 150 may also output the question and answer to display device 200 via an external device. As a result, display device 200 displays the question and answer. That is, display device 200 displays frequently asked questions and the answers to those questions. Then, customers visually check the content displayed on display device 200. As a result, the number of customers who ask questions to staff members is reduced.

[0024] Therefore, according to the first embodiment, the information processing device 100 can reduce the burden on staff.

[0025] Embodiment 2 Next, a description will be given of embodiment 2. In embodiment 2, differences from embodiment 1 will be mainly described. In embodiment 2, descriptions of matters common to embodiment 1 will be omitted.

[0026] 5 is a block diagram showing functions of an information processing device according to the second embodiment. The information processing device 100 further includes an estimation unit 160. A part or all of the estimation unit 160 may be realized by a processing circuit. Also, a part or all of the estimation unit 160 may be realized as a program module executed by the processor 101. The functions of the estimation unit 160 will be described in detail later.

[0027] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. FIG. 6 is a flowchart illustrating an example of processing executed by the information processing device according to the second embodiment. (Step S21) The acquisition unit 120 acquires voice data of a customer. (Step S22) The voice recognition execution unit 130 executes voice recognition using the voice data, thereby allowing the information processing device 100 to obtain data that is a character string. (Step S23) The determination unit 140 determines whether the content of the data obtained by the voice recognition is a question. If the content of the data is a question, the process proceeds to step S24. If the content of the data is not a question, the process ends.

[0028] (Step S24) The estimation unit 160 uses the data obtained by speech recognition to estimate a category corresponding to the content of the data. For example, the estimation unit 160 estimates the category using a rule base. For example, a method using a rule base is a method using a dictionary, a method using regular expressions, etc. Also, for example, the estimation unit 160 estimates the category using a trained model. In detail, when the estimation unit 160 inputs the data into the trained model, the trained model outputs a category. For example, the categories are transfer transportation, lost property, etc. The trained model can be created by machine learning such as DNN. For example, in machine learning, a large amount of character strings are prepared as input data. Training data is prepared in which a category corresponding to the character string of the input data is a correct answer label. Then, the trained model is created by performing machine learning using the input data and the training data so that a category, which is output data of the trained model, matches the correct answer label.

[0029] (Step S25) The determination unit 140 determines whether a predetermined time has elapsed since the voice data corresponding to the estimated category was first acquired. For example, the determination unit 140 determines whether the time has elapsed since the voice data corresponding to the category "transfer transportation" was first acquired. If the time has elapsed, the process ends. If the time has not elapsed, the process proceeds to step S26.

[0030] (Step S26) The determination unit 140 determines whether or not the number of times that voice data corresponding to the estimated category has been acquired is equal to or greater than a predetermined threshold. Specifically, the determination unit 140 makes the determination as follows. The storage unit 110 stores the number of times that speech data has been acquired. The determination unit 140 increments the number of times that speech data has been acquired. The determination unit 140 determines whether or not the number of times that speech data has been acquired is equal to or greater than the threshold. If the number of times that speech data has been acquired is equal to or greater than the threshold, this means that questions of the estimated category are frequently asked. Note that the number of times that speech data has been acquired may be an increase rate of the number of times that speech data has been acquired. If the number of acquisitions is equal to or greater than the threshold, the process proceeds to step S27. If the number of acquisitions is less than the threshold, the process ends.

[0031] (Step S27) The acquiring unit 120 acquires a question corresponding to the estimated category and an answer to the question. In detail, the acquiring unit 120 acquires the question and the answer from a management table. An example of the management table is shown below.

[0032] FIG. 7 is a diagram showing an example of a management table in the second embodiment. The management table 111 is also called management information. The management table 111 shows the correspondence between questions and answers. Specifically, the management table 111 has items of item number, category, question, and answer. When the estimated category is transfer transportation, the acquisition unit 120 acquires the question and answer corresponding to the category "transfer transportation". That is, the acquisition unit 120 acquires the information of the frame 11.

[0033] The management table 111 is stored in the storage unit 110 or an external device. If the management table 111 is stored in an external device, the acquisition unit 120 accesses the external device to acquire the question and the answer.

[0034] In this way, when the number of times that voice data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold, the acquisition unit 120 acquires a question corresponding to the estimated category and an answer to the question.

[0035] (Step S28) Output unit 150 outputs the question and answer to display device 200. As a result, display device 200 displays the question and answer. Then, the customer visually confirms the content displayed on display device 200. This reduces the number of customers who ask questions to the staff.

[0036] Therefore, according to the second embodiment, the information processing device 100 can reduce the burden on staff.

[0037] Embodiment 3 Next, a description will be given of embodiment 3. In embodiment 3, differences from embodiment 1 will be mainly described. In embodiment 3, descriptions of matters common to embodiment 1 will be omitted.

[0038] 8 is a block diagram showing functions of an information processing device according to the third embodiment. The information processing device 100 further includes a search unit 170. A part or all of the search unit 170 may be realized by a processing circuit. Also, a part or all of the search unit 170 may be realized as a module of a program executed by the processor 101. The functions of the search unit 170 will be described in detail later.

[0039] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. FIG. 9 is a flowchart illustrating an example of processing executed by the information processing device according to the third embodiment. (Step S31) The acquisition unit 120 acquires voice data of a customer. (Step S32) The voice recognition execution unit 130 executes voice recognition using the voice data, thereby allowing the information processing device 100 to obtain data that is a character string. (Step S33) The determination unit 140 determines whether the content of the data obtained by the voice recognition is a question. If the content of the data is a question, the process proceeds to step S34. If the content of the data is not a question, the process ends. (Step S34) The acquiring unit 120 acquires the management table 111 from the storage unit 110 or an external device.

[0040] (Step S35) The search unit 170 uses the management table 111 to search for questions that are identical or similar to the content of the data obtained by voice recognition (i.e., the question). For example, the search unit 170 uses the data as a query to search the management table 111. Also, for example, the search unit 170 extracts a keyword from the data, and uses the keyword as a query to search the management table 111. Also, for example, the search unit 170 vectorizes the data and a question registered in the management table 111, and compares the two vectorized data to search for questions that are identical or similar. As a result, for example, the search unit 170 identifies the question with item number "1".

[0041] (Step S36) The determination unit 140 determines whether or not a predetermined time has elapsed since the voice data identical to or similar to the searched question was first acquired. If the time has elapsed, the process ends. If the time has not elapsed, the process proceeds to step S37.

[0042] (Step S37) The determination unit 140 determines whether or not the number of times that voice data identical or similar to the searched question has been acquired is equal to or greater than a predetermined threshold. Specifically, the determination unit 140 makes the determination as follows. The storage unit 110 stores the number of times that it has been acquired. The determination unit 140 increments the number of times that it has been acquired. The determination unit 140 determines whether or not the number of times that it has been acquired is equal to or greater than the threshold. If the number of times that it has been acquired is equal to or greater than the threshold, this means that the searched question is frequently asked. If the number of acquisitions is equal to or greater than the threshold, the process proceeds to step S38. If the number of acquisitions is less than the threshold, the process ends.

[0043] (Step S38) The acquiring unit 120 acquires the searched question and the answer to the question from the management table 111. For example, the acquiring unit 120 acquires the question and answer of item number "1". (Step S39) Output unit 150 outputs the question and answer to display device 200. As a result, display device 200 displays the question and answer. Then, the customer visually confirms the content displayed on display device 200. This reduces the number of customers who ask questions to the staff.

[0044] An example of the management table 111 is shown here. FIG. 10 is a diagram showing an example of a management table in the third embodiment. In the second embodiment, a question and an answer corresponding to a category are output. For example, the information in box 11 is output. On the other hand, in the third embodiment, a searched question and an answer to the question are output. For example, the information in box 12 is output. In this way, narrowed-down information is output. Therefore, according to the third embodiment, the information processing device 100 can output a question and an answer that is more suited to the situation.

[0045] Embodiment 4 Next, a fourth embodiment will be described. In the fourth embodiment, differences from the first embodiment will be mainly described. In the fourth embodiment, descriptions of the same matters as the first embodiment will be omitted.

[0046] A speaker may give a speech that is meaningfully connected over multiple episodes. Therefore, if a judgment is made based on the voice data of one episode, the information processing device 100 may not be able to perform appropriate processing. Therefore, the information processing device 100 has the following functions.

[0047] 11 is a block diagram showing functions of an information processing device according to the fourth embodiment. The information processing device 100 further includes a combining unit 180. A part or all of the combining unit 180 may be realized by a processing circuit. Also, a part or all of the combining unit 180 may be realized as a module of a program executed by the processor 101. The function of coupling portion 180 will be explained later.

[0048] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. Fig. 12 is a flowchart showing an example (part 1) of the process executed by the information processing device of the fourth embodiment. Fig. 13 is a flowchart showing an example (part 2) of the process executed by the information processing device of the fourth embodiment. The process in Figs. 12 and 13 differs from the process in Fig. 4 in that steps S11a, 13a to 13d, 14a, and 15a are executed. Therefore, in Figs. 12 and 13, steps S11a, 13a to 13d, 14a, and 15a will be described. Descriptions of the process other than steps S11a, 13a to 13d, 14a, and 15a will be omitted.

[0049] (Step S11a) The acquisition unit 120 acquires audio data for one episode. (Step S13a) The determination unit 140 determines whether or not the voice data acquired in step S11a is the first voice data of the same person. If the acquired voice data is the first voice data, the determination unit 140 stores the data obtained by voice recognition in the storage unit 110. Then, the process proceeds to step S11a. If the acquired voice data is voice data of the same person, the process proceeds to step S13b. Note that the determination unit 140 can determine whether or not the acquired voice data is voice data of the same person by analysis.

[0050] (Step S13b) The determination unit 140 determines whether there is a semantic connection between the data obtained by the speech recognition and the data stored in the storage unit 110. For example, the determination unit 140 determines whether there is a semantic connection by using a rule base. For example, a method using a rule base is a method using a dictionary or a method using regular expressions. In addition, for example, the determination unit 140 vectorizes the data obtained by the speech recognition and the data stored in the storage unit 110, and compares the two vectorized data to determine whether there is a semantic connection. If there is a semantic connection, the process proceeds to step S13c If there is no semantic connection, the process proceeds to step S13d.

[0051] (Step S13c) The combining unit 180 combines the data obtained by the voice recognition with the data stored in the storage unit 110. The combining unit 180 stores the combined data in the storage unit 110. Then, the process proceeds to step S11a. (Step S13d) The acquiring unit 120 acquires the combined data from the storage unit 110. The combined data is data in which a plurality of pieces of voice data of a customer are combined, and is data in which contents having a semantic connection are combined. If the combined data is not stored in the storage unit 110, the determination unit 140 performs the following process using the voice data for one episode.

[0052] (Step S14a) The determination unit 140 determines whether the content of the combined data is a frequently asked question. For example, the determination unit 140 makes the determination as follows. The memory unit 110 stores the number of times that the information processing device 100 has acquired a question that is the same as or similar to the combined data. In other words, the memory unit 110 stores the number of times that the information processing device 100 has acquired a similar question. The determination unit 140 increments the number of times. If the number of times is equal to or greater than a predetermined threshold, the determination unit 140 determines that the content of the combined data is a frequently asked question. If the condition is met, the process proceeds to step S15, otherwise the process ends.

[0053] (Step S15a) Acquiring unit 120 acquires an answer corresponding to the content of the combined data (that is, a question) from storage unit 110 or an external device.

[0054] According to the fourth embodiment, the information processing device 100 determines whether a question is frequently asked based on a plurality of utterances that are related in meaning, and thus the information processing device 100 can make a more appropriate determination.

[0055] Furthermore, there are cases where a speaker inverts a sentence and utters multiple utterances that are connected in meaning. Even when a speaker speaks in this way, the fourth embodiment is effective.

[0056] Here, the external device may execute steps S11a, 12, 13, and 13a to 13c. When the external device executes the processes, in step S13d, the acquiring section 120 acquires the combined data from the external device.

[0057] Variation 1 of embodiment 4 The fourth embodiment can be combined with the second embodiment. The process when the second embodiment and the fourth embodiment are combined will be described with reference to a flowchart.

[0058] Fig. 14 is a flowchart showing an example (part 1) of the process executed by the information processing device of the first modified example of the fourth embodiment. Fig. 15 is a flowchart showing an example (part 2) of the process executed by the information processing device of the first modified example of the fourth embodiment. The process in Figs. 14 and 15 differs from the process in Fig. 6 in that steps S21a, 23a to 23d, 24a, 25a, and 26a are executed. Therefore, in Figs. 14 and 15, steps S21a, 23a to 23d, 24a, 25a, and 26a will be described. Descriptions of the process other than steps S21a, 23a to 23d, 24a, 25a, and 26a will be omitted.

[0059] (Step S21a) The acquisition unit 120 acquires audio data for one episode. (Step S23a) The determination unit 140 determines whether the voice data acquired in step S21a is the first voice data of the same person. If the acquired voice data is the first voice data, the determination unit 140 stores the data obtained by voice recognition in the storage unit 110. Then, the process proceeds to step S21a. If the acquired voice data is the voice data of the same person, the process proceeds to step S23b.

[0060] (Step S23b) The determination unit 140 determines whether or not there is a connection in meaning between the data obtained by the voice recognition and the data stored in the storage unit 110. If there is a semantic connection, the process proceeds to step S23c, otherwise the process proceeds to step S23d.

[0061] (Step S23c) The combining unit 180 combines the data obtained by the voice recognition with the data stored in the storage unit 110. The combining unit 180 stores the combined data in the storage unit 110. Then, the process proceeds to step S21a. (Step S23d) The acquiring unit 120 acquires the combined data from the storage unit 110. (Step S24a) The estimation unit 160 uses the combined data to estimate a category corresponding to the content of the combined data. For example, the estimation unit 160 estimates the category using a rule base. For example, a method using a rule base is a method using a dictionary, a method using regular expressions, or the like. Also, for example, the estimation unit 160 estimates the category using a trained model. The trained model can be created by machine learning such as DNN. For example, in machine learning, a large amount of combined data is prepared as input data. Training data is prepared in which a category corresponding to the combined data of the input data is a correct answer label. Then, the trained model is created by performing machine learning using the input data and the training data so that a category, which is output data of the trained model, matches the correct answer label.

[0062] (Step S25a) The determination unit 140 determines whether a predetermined time has elapsed since the combined data corresponding to the estimated category was first acquired. If the time has elapsed, the process ends. If the time has not elapsed, the process proceeds to step S26a.

[0063] (Step S26a) The determination unit 140 determines whether or not the number of times that combined data corresponding to the estimated category has been acquired is equal to or greater than a predetermined threshold. Specifically, the determination unit 140 makes the determination as follows. The storage unit 110 stores the number of times of acquisition. The determination unit 140 increments the number of times of acquisition. The determination unit 140 determines whether or not the number of times of acquisition is equal to or greater than the threshold. If the number of acquisitions is equal to or greater than the threshold, the process proceeds to step S27. If the number of acquisitions is less than the threshold, the determination unit 140 increments the number of acquisitions. For example, the number of acquisitions is managed by the storage unit 110. Then, the process ends.

[0064] According to the first modification of the fourth embodiment, the information processing device 100 determines whether or not a question is frequently asked based on a plurality of utterances that are related in meaning, so that the information processing device 100 can make a more appropriate determination.

[0065] Here, the external device may execute steps S21a, S22, S23, and S23a to S23c. When the external device executes the processes, in step S23d, the acquiring section 120 acquires the combined data from the external device.

[0066] Variation 2 of embodiment 4 The fourth embodiment can be combined with the third embodiment. The process when the third embodiment and the fourth embodiment are combined will be described with reference to a flowchart.

[0067] Fig. 16 is a flowchart showing an example (part 1) of the process executed by the information processing device of Modification 2 of the fourth embodiment. Fig. 17 is a flowchart showing an example (part 2) of the process executed by the information processing device of Modification 2 of the fourth embodiment. The process in Figs. 16 and 17 differs from the process in Fig. 9 in that steps S31a, 33a to 33d, 35a, 36a, and 37a are executed. Therefore, in Figs. 16 and 17, steps S31a, 33a to 33d, 35a, 36a, and 37a will be described. Descriptions of the process other than steps S31a, 33a to 33d, 35a, 36a, and 37a will be omitted.

[0068] (Step S31a) The acquisition unit 120 acquires audio data for one episode. (Step S33a) The determination unit 140 determines whether the voice data acquired in step S31a is the first voice data of the same person. If the acquired voice data is the first voice data, the determination unit 140 stores the data obtained by voice recognition in the storage unit 110. Then, the process proceeds to step S31a. If the acquired voice data is the voice data of the same person, the process proceeds to step S33b.

[0069] (Step S33b) The determination unit 140 determines whether or not there is a connection in meaning between the data obtained by the voice recognition and the data stored in the storage unit 110. If there is a semantic connection, the process proceeds to step S33c If there is no semantic connection, the process proceeds to step S33d.

[0070] (Step S33c) The combining unit 180 combines the data obtained by the voice recognition with the data stored in the storage unit 110. The combining unit 180 stores the combined data in the storage unit 110. Then, the process proceeds to step S31a. (Step S33d) The acquiring unit 120 acquires the combined data from the storage unit 110.

[0071] (Step S35a) The search unit 170 searches for questions that are identical or similar to the contents of the combined data (i.e., the question) using the management table 111. For example, the search unit 170 uses the combined data as a query to search the management table 111. Also, for example, the search unit 170 extracts a keyword from the combined data, and uses the keyword as a query to search the management table 111. Also, for example, the search unit 170 vectorizes the combined data and the question registered in the management table 111, and compares the two vectorized data to search for questions that are identical or similar.

[0072] (Step S36a) The determination unit 140 determines whether or not a predetermined time has elapsed since the combined data that is the same as or similar to the searched query was first obtained. If the time has elapsed, the process ends. If the time has not elapsed, the process proceeds to step S37a.

[0073] (Step S37a) The determination unit 140 determines whether the number of times combined data identical or similar to the searched question has been acquired is equal to or greater than a predetermined threshold. Specifically, the determination unit 140 makes the determination as follows. The storage unit 110 stores the number of times of acquisition. The determination unit 140 increments the number of times of acquisition. The determination unit 140 determines whether the number of times of acquisition is equal to or greater than the threshold. If the number of acquisitions is equal to or greater than the threshold, the process proceeds to step S38. If the number of acquisitions is less than the threshold, the process ends.

[0074] According to the second modification of the fourth embodiment, the information processing device 100 determines whether a question is frequently asked based on a plurality of utterances that have a semantic connection, and thus the information processing device 100 can make a more appropriate determination.

[0075] Here, the external device may execute steps S31a, S32, S33, and S33a to S33c. When the external device executes the processes, in step S33d, the acquiring section 120 acquires the combined data from the external device.

[0076] Embodiment 5. Next, a fifth embodiment will be described. In the fifth embodiment and the modified example of the fifth embodiment, differences from the second to fourth embodiments will be mainly described. In the fifth embodiment and the modified example of the fifth embodiment, descriptions of commonalities with the second to fourth embodiments will be omitted.

[0077] 18 is a diagram showing a provision system according to the fifth embodiment. The provision system further includes a server 400. The information processing device 100 and the server 400 communicate with each other via a network. The network may be a wired network or a wireless network.

[0078] The server 400 stores supplementary information for estimating a category corresponding to a question or for searching for a question. The supplementary information is useful information. For example, the supplementary information may include a character string indicating the content of the useful information. For example, information on a social networking service (SNS) is stored in the server 400. The server 400 performs filtering and extracts useful information from the information on the SNS. This allows the server 400 to store the supplementary information, which is useful information. The server 400 periodically updates the supplementary information. Furthermore, the server 400 may periodically transmit the supplementary information to the information processing device 100. When the acquisition unit 120 of the information processing device 100 acquires the supplementary information, the acquisition unit 120 stores the supplementary information in the storage unit 110.

[0079] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. Fig. 19 is a flowchart showing an example of a process executed by the information processing device of embodiment 5. The process in Fig. 19 differs from the process in Fig. 6 in that steps S23e and 24b are executed. Therefore, steps S23e and 24b will be described in Fig. 19. Descriptions of the processes other than steps S23e and 24b will be omitted.

[0080] (Step S23e) The acquisition unit 120 acquires supplementary information related to the data obtained by speech recognition from the storage unit 110 or the server 400. This sentence may be expressed as follows: The acquisition unit 120 acquires supplementary information related to words included in the data obtained by speech recognition from the storage unit 110 or the server 400. For example, if the data includes a line name, the acquisition unit 120 acquires supplementary information related to the line name.

[0081] (Step S24b) The estimation unit 160 estimates a category corresponding to the content of the data using the data obtained by speech recognition and the supplementary information. For example, the estimation unit 160 estimates the category using a rule base. For example, a method using a rule base is a method using a dictionary or a method using regular expressions. Also, for example, the estimation unit 160 estimates the category using a trained model. In detail, when the estimation unit 160 inputs the data and the supplementary information to the trained model, the trained model outputs a category. The trained model can be created by machine learning such as DNN. For example, in machine learning, a large amount of character strings and supplementary information are prepared as input data. Training data is prepared in which a category corresponding to the character string of the input data is a correct answer label. Then, the trained model is created by performing machine learning using the input data and the training data so that the category, which is the output data of the trained model, matches the correct answer label.

[0082] Here, for example, the content of the utterance may lack some information due to a speech recognition error of the voice announcement, an erroneous utterance, etc. Also, for example, the content of the utterance may lack a prerequisite due to an omission of the utterance, etc. In such a case, the accuracy of the category estimated based only on the content of the utterance may be low. Therefore, the information processing device 100 uses the supplementary information to supplement the content that is missing from the content of the utterance. This allows a more accurate category to be estimated.

[0083] According to the fifth embodiment, the information processing device 100 can estimate a more accurate category.

[0084] Variation 1 of embodiment 5 Fig. 20 is a flowchart showing an example of processing executed by the information processing device of Variation 1 of Embodiment 5. The processing in Fig. 20 differs from the processing in Fig. 9 in that steps S34a and 35b are executed. Therefore, steps S34a and 35b will be described in Fig. 20. Descriptions of the processing other than steps S34a and 35b will be omitted.

[0085] (Step S34a) The acquisition unit 120 acquires, from the storage unit 110 or the server 400, supplemental information related to the data obtained by the voice recognition. (Step S35b) The search unit 170 uses the management table 111 to search for a question that is the same as or similar to the question based on the data and the supplemental information obtained by voice recognition. For example, the search unit 170 uses the data and the supplemental information as a query to search the management table 111. Also, for example, the search unit 170 extracts a keyword from the data, and uses the keyword and the supplemental information as a query to search the management table 111. Also, for example, the search unit 170 vectorizes the question based on the data and the supplemental information and the question registered in the management table 111, and compares the two vectorized data to search for the same or similar question.

[0086] According to the first modification of the fifth embodiment, the information processing device 100 can search for a more accurate question.

[0087] Variation 2 of embodiment 5 In the second modification of the fifth embodiment, a case where supplemental information is used will be described, which is applied to the first modification of the fourth embodiment.

[0088] The process of step S24a is changed as follows. The acquisition unit 120 acquires supplementary information related to the combined data from the storage unit 110 or the server 400. The estimation unit 160 estimates a category corresponding to the content of the combined data using the combined data and the supplementary information. For example, the estimation unit 160 estimates a category using a rule base. For example, a method using a rule base is a method using a dictionary, a method using a regular expression, or the like. Also, for example, the estimation unit 160 estimates a category using a trained model. In detail, when the estimation unit 160 inputs the combined data and the supplementary information to the trained model, the trained model outputs a category. The process from step S25a onwards is the same as the process of FIG. 15. The trained model can be created by machine learning such as DNN. For example, in machine learning, a large amount of combined data and supplementary information are prepared as input data. Training data is prepared in which a category corresponding to the combined data of the input data is a correct answer label. Then, the trained model is created by performing machine learning using the input data and the training data so that the category, which is the output data of the trained model, matches the correct answer label.

[0089] According to the second modification of the fifth embodiment, the information processing device 100 can achieve the effects of the first modification of the fourth embodiment and the effects of the fifth embodiment.

[0090] Variation 3 of embodiment 5 In the third modification of the fifth embodiment, a case where supplemental information is used will be described, which is applied to the second modification of the fourth embodiment.

[0091] The process of step S35a is changed as follows. The acquisition unit 120 acquires supplementary information related to the data obtained by the voice recognition from the storage unit 110 or the server 400. The search unit 170 searches the management table 111 for a question that is the same as or similar to a question based on the combined data and the supplementary information. For example, the search unit 170 searches the management table 111 using the combined data and the supplementary information as a query. Also, for example, the search unit 170 extracts a keyword from the combined data, and searches the management table 111 using the combined keyword and the supplementary information as a query. Also, for example, the search unit 170 vectorizes a question based on the combined data and the supplementary information and a question registered in the management table 111, and compares the two vectorized data to search for a question that is the same as or similar to the question. The process from step S35a onwards is the same as the process of FIG. 17.

[0092] According to the third modification of the fifth embodiment, the information processing device 100 can achieve the effects of the second modification of the fourth embodiment and the effects of the first modification of the fifth embodiment.

[0093] Embodiment 6 Next, a sixth embodiment will be described. In the sixth embodiment and the modified example of the sixth embodiment, differences from the second to fourth embodiments will be mainly described. In the sixth embodiment and the modified example of the sixth embodiment, descriptions of commonalities with the second to fourth embodiments will be omitted.

[0094] 21 is a block diagram showing functions of an information processing device according to the sixth embodiment. The information processing device 100 further includes an analysis unit 190 and a change unit 191. A part or all of the analysis unit 190 and the change unit 191 may be realized by a processing circuit. Also, a part or all of the analysis unit 190 and the change unit 191 may be realized as a program module executed by the processor 101. The functions of the analysis unit 190 and the change unit 191 will be described later.

[0095] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. Fig. 22 is a flowchart showing an example of processing executed by the information processing device of embodiment 6. The processing in Fig. 22 differs from the processing in Fig. 6 in that steps S23f and 27a are executed. Therefore, steps S23f and 27a will be described in Fig. 22. Descriptions of the processing other than steps S23f and 27a will be omitted.

[0096] (Step S23f) The analysis unit 190 uses the data obtained by the voice recognition to analyze whether the content of the data is of high urgency. For example, the analysis unit 190 performs the analysis using a rule base. For example, a method using a rule base is a method using a dictionary, a method using regular expressions, etc. Also, for example, the analysis unit 190 performs the analysis using a trained model. The information processing device 100 obtains information indicating whether the urgency is high or not through the analysis. For example, the content of high urgency is content indicating that an accident, fire, disaster, etc. has occurred. For example, when the content of the data is content indicating that an accident, fire, disaster, etc. has occurred, the analysis unit 190 outputs information indicating that the urgency is high. The trained model can be created by machine learning such as DNN. For example, in machine learning, a large amount of keywords are prepared as input data. Training data is prepared in which the level of urgency corresponding to the keyword of the input data is used as a correct answer label. Then, the trained model is created by performing machine learning using the input data and the training data so that the level of urgency, which is output data of the trained model, matches the correct answer label.

[0097] Furthermore, the analysis unit 190 may use data obtained by speech recognition to analyze the urgency corresponding to the content of the data. For example, if the content of the data includes "earthquake" or "disaster", the urgency is "highest". For example, if the content of the data includes "accident" or "breakdown", the urgency is "high". For example, if the content of the data includes "congestion" or "delay", the urgency is "medium". The urgency may be expressed as a numerical value instead of a degree such as "high".

[0098] (Step S27a) The acquiring unit 120 acquires a question corresponding to the estimated category and an answer to the question based on the information indicating whether the urgency is high or not and the management table. Here, two management tables are prepared. The two management tables are shown below.

[0099] FIG. 23 is a diagram showing an example of a management table according to the sixth embodiment. Management table 111a is information used when the level of urgency is high. Management table 111b is information used when the level of urgency is low. Management tables 111a and 111b show the correspondence between questions and answers. Note that management tables 111a and 111b are stored in storage unit 110 or an external device. Also, management table 111a is also referred to as first management information. Management table 111b is also referred to as second management information.

[0100] When the information indicating whether the urgency is high indicates that the urgency is high, the acquiring unit 120 acquires a question corresponding to the estimated category and an answer to the question using the management table 111a.When the information indicating whether the urgency is high indicates that the urgency is low, the acquiring unit 120 acquires a question corresponding to the estimated category and an answer to the question using the management table 111b.

[0101] Furthermore, when the urgency level is analyzed, a management table according to the urgency level is prepared. The management table is stored in the storage unit 110 or an external device. The management table is also referred to as third management information. The management table indicates the correspondence between questions and answers. The acquisition unit 120 may use the management table to acquire questions corresponding to the estimated category and answers to the questions.

[0102] The modification unit 191 may modify the answer to the question. Furthermore, the modification unit 191 may omit a part of the text of the answer to the question. For example, the omitted text is text that is unlikely to need to be conveyed to the customer. By omitting the text of the answer that is unlikely to need to be conveyed to the customer, the customer can easily recognize the answer. As a result, the time that the attendant spends dealing with the customer is reduced, and the burden on the attendant is reduced. Furthermore, the output unit 150 outputs the modified answer or the omitted answer to the display device 200.

[0103] When the management tables 111a and 111b are stored in an external device, the acquiring unit 120 accesses the external device to acquire the question and the answer.

[0104] According to the sixth embodiment, the information processing device 100 outputs a question and an answer according to the degree of urgency, so that the information processing device 100 can output a question and an answer that are more suited to the situation.

[0105] Variation 1 of the sixth embodiment Fig. 24 is a flowchart showing an example of processing executed by the information processing device of Variation 1 of Embodiment 6. The processing in Fig. 24 differs from the processing in Fig. 9 in that steps S33e, 34b, 35c, and 38a are executed. Therefore, in Fig. 24, steps S33e, 34b, 35c, and 38a will be described. And, description of the processing other than steps S33e, 34b, 35c, and 38a will be omitted.

[0106] (Step S33e) The analysis unit 190 uses the data obtained by the voice recognition to analyze whether the content of the data is of high urgency or not. The information processing device 100 obtains information indicating whether the content of the data is of high urgency or not through the analysis. Furthermore, the analysis unit 190 may use data obtained by voice recognition to analyze the urgency level corresponding to the content of the data. (Step S34b) The acquiring unit 120 acquires the management table 111a or the management table 111b based on the information indicating whether the urgency is high or not. The acquiring unit 120 may acquire a management table according to the urgency.

[0107] (Step S35c) When management table 111a is acquired, search unit 170 uses management table 111a to search for questions that are the same as or similar to the content of the data acquired by voice recognition. When management table 111b is acquired, search unit 170 uses management table 111b to search for questions that are the same as or similar to the content of the data acquired by voice recognition. Furthermore, when a management table according to the urgency level is acquired, the search unit 170 uses the management table to search for a question whose content is the same as or similar to the content of the data obtained by voice recognition.

[0108] (Step S38a) When management table 111a is acquired, acquiring unit 120 acquires the searched question and the answer to the question based on management table 111a. When management table 111b is acquired, acquiring unit 120 acquires the searched question and the answer to the question based on management table 111b. Furthermore, when a management table according to the urgency level is acquired, the acquiring section 120 may acquire the searched question and the answer to the question by using the management table according to the urgency level.

[0109] The modification unit 191 may modify the answer to the question. Furthermore, the modification unit 191 may omit a part of the text of the answer to the question. For example, the text to be omitted is text that is unlikely to need to be conveyed to the customer. By omitting the text of the answer that is unlikely to need to be conveyed to the customer, the customer can easily recognize the answer. As a result, the time that the attendant spends responding to the customer is reduced, and the burden on the attendant is reduced.

[0110] According to the first modification of the sixth embodiment, the information processing device 100 outputs a question and an answer according to the degree of urgency, so that the information processing device 100 can output a question and an answer that are more suited to the situation.

[0111] Variation 2 of the sixth embodiment In the second modification of the sixth embodiment, a case will be described in which information indicating whether the urgency is high or not is used, and the first modification of the fourth embodiment is applied.

[0112] The process of step S27 is changed as follows. The analysis unit 190 uses the combined data to analyze whether the content of the combined data is of high urgency or not. When the information indicating whether the urgency is high or not obtained by the analysis indicates that the urgency is high, the acquisition unit 120 uses the management table 111a to acquire a question corresponding to the estimated category and an answer to the question. When the information indicates that the urgency is low, the acquisition unit 120 uses the management table 111b to acquire a question corresponding to the estimated category and an answer to the question. The process other than the changed step S27 is the same as that of the first modification of the fourth embodiment. Furthermore, the analysis unit 190 may use the combined data to analyze the urgency corresponding to the content of the combined data. The acquisition unit 120 may use a management table according to the urgency to acquire a question corresponding to the estimated category and an answer to the question.

[0113] The modification unit 191 may modify the answer to the question. Furthermore, the modification unit 191 may omit a part of the text of the answer to the question. For example, the text to be omitted is text that is unlikely to need to be conveyed to the customer. By omitting the text of the answer that is unlikely to need to be conveyed to the customer, the customer can easily recognize the answer. As a result, the time that the attendant spends responding to the customer is reduced, and the burden on the attendant is reduced.

[0114] According to the second modification of the sixth embodiment, the information processing device 100 outputs a question and an answer according to the degree of urgency, so that the information processing device 100 can output a question and an answer that are more suited to the situation.

[0115] Variation 3 of the sixth embodiment In the third modification of the sixth embodiment, a case will be described in which information indicating whether the urgency is high or not is used, and the second modification of the fourth embodiment is applied.

[0116] The process of step S34 is changed as follows. The analysis unit 190 uses the combined data to analyze whether the content of the combined data is of high urgency or not. The acquisition unit 120 selects a management table based on information indicating whether the urgency is high or not, obtained by the analysis. For example, when the information indicates that the urgency is high, the acquisition unit 120 acquires management table 111a. When the information indicates that the urgency is low, the acquisition unit 120 acquires management table 111b. Furthermore, the analysis unit 190 may use the combined data to analyze the urgency level corresponding to the contents of the combined data. The acquisition unit 120 acquires a management table according to the urgency level.

[0117] The process of step S35a is changed as follows. When management table 111a is acquired, search unit 170 uses management table 111a to search for questions that are the same as or similar to the content of the combined data. When management table 111b is acquired, search unit 170 uses management table 111b to search for questions that are the same as or similar to the content of the combined data. When a management table according to the urgency is acquired, search unit 170 uses the management table to search for questions that are the same as or similar to the content of the combined data.

[0118] The process of step S38 is changed as follows. When management table 111a is acquired, acquiring unit 120 acquires the searched question and the answer to the question based on management table 111a. When management table 111b is acquired, acquiring unit 120 acquires the searched question and the answer to the question based on management table 111b. When a management table according to the urgency is acquired, acquiring unit 120 acquires the searched question and the answer to the question based on the management table.

[0119] The modification unit 191 may modify the answer to the question. Furthermore, the modification unit 191 may omit a part of the text of the answer to the question. For example, the text to be omitted is text that is unlikely to need to be conveyed to the customer. By omitting the text of the answer that is unlikely to need to be conveyed to the customer, the customer can easily recognize the answer. As a result, the time that the attendant spends responding to the customer is reduced, and the burden on the attendant is reduced.

[0120] The processes other than steps S34, S35a, and S38 that are changed are the same as those in the second modification of the fourth embodiment.

[0121] According to the third modification of the sixth embodiment, the information processing device 100 outputs a question and an answer according to the degree of urgency, so that the information processing device 100 can output a question and an answer that are more suited to the situation.

[0122] The features of each of the embodiments described above can be combined with each other as appropriate.

[0123] The above embodiments describe the generation of questions and answers related to station operations by the information processing device of the present disclosure, but are merely examples. For example, the information processing device of the present disclosure may generate questions and answers related to guidance operations for tourist spots or commercial facilities. [Explanation of symbols]

[0124] 11 frame, 12 frame, 100 information processing device, 101 processor, 102 volatile storage device, 103 non-volatile storage device, 110 storage unit, 111 management table, 111a, 111b management tables, 120 acquisition unit, 130 voice recognition execution unit, 140 judgment unit, 150 output unit, 160 estimation unit, 170 search unit, 180 combination unit, 190 analysis unit, 191 change unit, 200 display device, 300 microphone, 400 server.

Claims

1. An information processing device capable of outputting information to a display device, an acquisition unit that acquires combined data, the combined data being data in which a plurality of pieces of voice data of a customer are combined and in which contents having a connection in meaning are combined; a determination unit that determines whether the content of the combined data is a frequently asked question; An output unit; having when the content of the combined data is a frequently asked question, the acquisition unit acquires an answer corresponding to the question that is the content of the combined data; The output unit outputs the question and the answer to the display device. Information processing device.

2. An information processing device capable of outputting information to a display device, An acquisition unit for acquiring voice data of a customer; a voice recognition execution unit that executes voice recognition using the voice data; a determination unit that determines whether the content of the data obtained by the voice recognition is a question; an estimation unit that estimates a category corresponding to the content of the data by using the data when the content of the data is a question; An output unit; having the acquiring unit acquires a question corresponding to the estimated category and an answer to the question when the number of times that the voice data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold value; The output unit outputs the question and the answer to the display device. Information processing device.

3. The acquisition unit acquires supplementary information related to the data acquired by speech recognition, the estimation unit estimates a category corresponding to the content of the data by using the data obtained by speech recognition and the supplemental information; The information processing device according to claim 2 .

4. An analysis unit is further provided for analyzing whether the content of the data is of high urgency or not, or the urgency corresponding to the content of the data, using the data obtained by the voice recognition, When the information obtained by the analysis indicating whether the degree of urgency is high indicates that the degree of urgency is high, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using first management information, which is information used when the degree of urgency is high and which indicates a correspondence between questions and answers; when the information indicates that the degree of urgency is low, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using second management information, which is information used when the degree of urgency is low and which indicates a correspondence between questions and answers; when the degree of urgency has been analyzed, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using third management information, which is information according to the degree of urgency and which indicates a correspondence between questions and answers. The information processing device according to claim 2 .

5. An information processing device capable of outputting information to a display device, an acquisition unit that acquires combined data, the combined data being data in which a plurality of pieces of voice data of a customer are combined and in which contents having a connection in meaning are combined; an estimation unit that estimates a category corresponding to a content of the combined data by using the combined data; An output unit; having the acquiring unit acquires a question corresponding to the estimated category and an answer to the question when the number of times the combined data corresponding to the estimated category is acquired within a predetermined time is equal to or greater than a predetermined threshold value; The output unit outputs the question and the answer to the display device. Information processing device.

6. The acquisition unit acquires supplemental information related to the binding data, the estimation unit estimates a category corresponding to a content of the combined data by using the combined data and the supplemental information; The information processing device according to claim 5 .

7. The method further includes an analysis unit that uses the combined data to determine whether the content of the combined data is of high urgency or not, or to analyze the urgency corresponding to the content of the combined data, When the information obtained by the analysis indicating whether the degree of urgency is high indicates that the degree of urgency is high, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using first management information, which is information used when the degree of urgency is high and which indicates a correspondence between questions and answers; when the information indicates that the degree of urgency is low, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using second management information, which is information used when the degree of urgency is low and which indicates a correspondence between questions and answers; when the degree of urgency has been analyzed, the acquisition unit acquires a question corresponding to the estimated category and an answer to the question using third management information, which is information according to the degree of urgency and which indicates a correspondence between questions and answers. The information processing device according to claim 5 .

8. An information processing device capable of outputting information to a display device, an acquisition unit that acquires management information indicating correspondence between customer voice data and questions and answers; a voice recognition execution unit that executes voice recognition using the voice data; a determination unit that determines whether the content of the data obtained by the voice recognition is a question; a search unit that searches for a question that is the same as or similar to the content of the data by using the management information when the content of the data is a question; An output unit; having when the number of times that voice data identical or similar to the searched question is acquired within a predetermined time period is equal to or greater than a predetermined threshold, the acquisition unit acquires the searched question and an answer to the question from the management information; The output unit outputs the question and the answer to the display device. Information processing device.

9. The acquisition unit acquires supplementary information related to the data acquired by speech recognition, the search unit uses the management information to search for a question that is the same as or similar to a question based on the data obtained by speech recognition and the supplemental information. The information processing device according to claim 8.

10. An analysis unit is further provided for analyzing whether the content of the data is of high urgency or not, or the urgency corresponding to the content of the data, using the data obtained by the voice recognition, the search unit, when the information obtained by the analysis indicating whether the level of urgency is high indicates a high level of urgency, searches for questions that are identical or similar to the content of the data using first management information, which is information used when the level of urgency is high and which indicates a correspondence between questions and answers; when the information indicates a low level of urgency, searches for questions that are identical or similar to the content of the data using second management information, which is information used when the level of urgency is low and which indicates a correspondence between questions and answers; when the level of urgency has been analyzed, searches for questions that are identical or similar to the content of the data using third management information, which is information according to the level of urgency and which indicates a correspondence between questions and answers; the acquiring unit acquires the searched question and the answer thereto based on the first management information when the information indicates a high level of urgency, acquires the searched question and the answer thereto based on the second management information when the information indicates a low level of urgency, and acquires the searched question and the answer thereto based on the third management information when the level of urgency has been analyzed. The information processing device according to claim 8.

11. The acquisition unit acquires combined data, which is data in which a plurality of pieces of voice data of the customer are combined and in which contents having a semantic connection are combined; the search unit searches for a question that is the same as or similar to the content of the combined data by using the management information; when the number of times that the combined data that is identical or similar to the searched question is acquired within the time period is equal to or greater than the threshold, the acquisition unit acquires the searched question and an answer to the question from the management information. The information processing device according to claim 8.

12. The acquisition unit acquires supplemental information related to the binding data, the search unit searches for a question that is the same as or similar to a question based on the combined data and the supplemental information, using the management information. The information processing device according to claim 11.

13. The method further includes an analysis unit that uses the combined data to determine whether the content of the combined data is of high urgency or not, or to analyze the urgency corresponding to the content of the combined data, the acquisition unit acquires first management information which is information used when the level of urgency is high and which indicates a correspondence between questions and answers, when the information indicating whether the level of urgency is high obtained by the analysis indicates that the level of urgency is high; acquires second management information which is information used when the level of urgency is low and which indicates a correspondence between questions and answers, when the information indicates that the level of urgency is low; and acquires third management information which is information according to the level of urgency and which indicates a correspondence between questions and answers, when the level of urgency has been analyzed; the search unit, when the first management information is acquired, uses the first management information to search for questions that are identical or similar to the content of the combined data, when the second management information is acquired, uses the second management information to search for questions that are identical or similar to the content of the combined data, and when the third management information is acquired, uses the third management information to search for questions that are identical or similar to the content of the combined data, the acquisition unit, when the number of times that the combined data identical or similar to the searched question is acquired within the time period is equal to or greater than the threshold value and the first management information is acquired, acquires the searched question and an answer to the question based on the first management information; when the number of times that the combined data identical or similar to the searched question is acquired within the time period is equal to or greater than the threshold value and the second management information is acquired, acquires the searched question and an answer to the question based on the second management information; and when the number of times that the combined data identical or similar to the searched question is acquired within the time period is equal to or greater than the threshold value and the third management information is acquired, acquires the searched question and the answer to the question based on the third management information. The information processing device according to claim 11.

14. A modification unit is further provided for modifying the answer to the question or omitting a part of the sentence of the answer to the question, The output unit outputs the modified answer or the omitted answer to the display device.

9. The information processing device according to claim 1, 2, 5, or 8.

15. An information processing device capable of outputting information to a display device, Acquire combined data, which is data in which multiple voice data of the customer are combined and in which contents having a common meaning are combined; determining whether the content of the combined data is a frequently asked question; If the content of the combined data is a frequently asked question, obtaining an answer corresponding to the question that is the content of the combined data; outputting the question and the answer to the display device; Output method.

16. An information processing device capable of outputting information to a display device, Acquire customer voice data, performing speech recognition using said speech data; determining whether the content of the data obtained by the speech recognition is a question; if the content of the data is a question, using the data to infer a category corresponding to the content of the data; If the number of times that the voice data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold, a question corresponding to the estimated category and an answer to the question are acquired; outputting the question and the answer to the display device; Output method.

17. An information processing device capable of outputting information to a display device, Acquire combined data, which is data in which multiple voice data of the customer are combined and in which contents having a common meaning are combined; using the combined data to infer a category corresponding to the content of the combined data; if the number of times the combined data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold, acquiring a question corresponding to the estimated category and an answer to the question; outputting the question and the answer to the display device; Output method.

18. An information processing device capable of outputting information to a display device, acquires customer voice data and management information indicating a correspondence between questions and answers, executes voice recognition using the voice data, determines whether the content of the data obtained by the voice recognition is a question, and if the content of the data is a question, searches for questions that are the same as or similar to the content of the data using the management information; if the number of times that voice data identical or similar to the searched question is acquired within a predetermined time period is equal to or exceeds a predetermined threshold, the searched question and an answer to the question are acquired from the management information; outputting the question and the answer to the display device; Output method.

19. A computer capable of outputting information to a display device, Acquire combined data, which is data in which multiple voice data of the customer are combined and in which contents having a common meaning are combined; determining whether the content of the combined data is a frequently asked question; If the content of the combined data is a frequently asked question, obtaining an answer corresponding to the question that is the content of the combined data; outputting the question and the answer to the display device; The output program that causes the processing to occur.

20. A computer capable of outputting information to a display device, Acquire customer voice data, performing speech recognition using said speech data; determining whether the content of the data obtained by the speech recognition is a question; if the content of the data is a question, using the data to infer a category corresponding to the content of the data; If the number of times that the voice data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold, a question corresponding to the estimated category and an answer to the question are acquired; outputting the question and the answer to the display device; The output program that causes the processing to occur.

21. A computer capable of outputting information to a display device, Acquire combined data, which is data in which multiple voice data of the customer are combined and in which contents having a common meaning are combined; using the combined data to infer a category corresponding to the content of the combined data; if the number of times the combined data corresponding to the estimated category is acquired within a predetermined time period is equal to or greater than a predetermined threshold, acquiring a question corresponding to the estimated category and an answer to the question; outputting the question and the answer to the display device; The output program that causes the processing to occur.

22. A computer capable of outputting information to a display device, acquires customer voice data and management information indicating a correspondence between questions and answers, executes voice recognition using the voice data, determines whether the content of the data obtained by the voice recognition is a question, and if the content of the data is a question, searches for questions that are the same as or similar to the content of the data using the management information; if the number of times that voice data identical or similar to the searched question is acquired within a predetermined time period is equal to or exceeds a predetermined threshold, the searched question and an answer to the question are acquired from the management information; outputting the question and the answer to the display device; The output program that causes the processing to occur.

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