Information processing device and program

Abstract

To provide an information processing device and program, which allow for providing conversational sentences tailored to circumstances of each user.SOLUTION: An information processing device provided herein is configured to acquire event identification information for identifying a user event associated with date / time information, and generate associated conversational sentence related to the event identification information in speech generating processing at date and time after the date and time indicated by the date / time information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device and a program. [Background technology]

[0002] In recent years, various tools for managing users' schedules have been developed. Among these tools, a technique for registering and managing schedules based on predetermined keywords included in a user's conversation is known (see, for example, Non-Patent Document 1, etc.). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] "iPhone User Guide", [online], Apple Computer, [searched December 16, 2019], Internet<URL: https: / / support.apple.com / ja-jp / guide / iphone / iph3d110f84 / ios> Summary of the Invention [Problem to be solved by the invention]

[0004] However, while the above-mentioned conventional tools communicate with users in conversational sentences, they are only capable of managing future plans and are not capable of providing conversational sentences related to those plans, and therefore do not provide sufficient information tailored to the circumstances of each user.

[0005] The present invention has been made in view of the above-mentioned circumstances, and one of its objects is to provide an information processing device and a program that enable provision of conversational text that is suited to the circumstances of each user. [Means for solving the problem]

[0006] One aspect of the present invention that solves the problems of the above-mentioned conventional examples is an information processing device that includes an acquisition means for acquiring event-specific information that identifies a user's event associated with date and time information, and a conversation sentence generation means for generating a related conversation sentence related to the event-specific information in a process of speaking at a date and time after the date and time represented by the date and time information. Effect of the Invention

[0007] According to the present invention, it is possible to provide conversational text that is tailored to the circumstances of each user. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram illustrating an example of the configuration of an information processing system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram illustrating a configuration example of a terminal device according to an embodiment of the present invention. [Diagram 3] FIG. 2 is a functional block diagram illustrating an example of a server according to an embodiment of the present invention. [Figure 4] FIG. 2 is an explanatory diagram illustrating an example of a conversation sentence queue used in the information processing system according to the embodiment of the present invention. [Diagram 5] 1 is an explanatory diagram illustrating an example of the contents of an action database used in an information processing system according to an embodiment of the present invention. FIG. [Figure 6] FIG. 2 is a functional block diagram illustrating an example of a terminal device according to an embodiment of the present invention. [Figure 7] FIG. 2 is an explanatory diagram illustrating an example of setting information used in the information processing system according to the embodiment of the present invention. [Figure 8] 4 is a flowchart illustrating an example of the operation of the information processing system according to the embodiment of the present invention. [Figure 9] 6 is another flowchart illustrating an example of the operation of the information processing system according to the embodiment of the present invention. [Figure 10] FIG. 11 is a flowchart illustrating an example of a conversation sentence selection process of the information processing system according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment of the present invention will be described with reference to the drawings. As shown in Fig. 1, an information processing system 1 according to the embodiment of the present invention includes a server 10 as an information processing device, and a terminal device 20 communicatively connected to the server 10 via a communication means such as a network.

[0010] Here, the server 10 includes a control unit 11, a storage unit 12, and a communication unit 13, as shown in Fig. 1. The terminal device 20 is a robot, and includes at least a leg unit 21 and a main body unit 22, as shown in Fig. 2, in which a control unit 31, a storage unit 32, a sensor unit 33, a display unit 34, an audio output unit 35, a communication unit 36, and a drive unit 37 are housed. The leg unit 21 and the main body unit 22 are connected via an actuator that can rotate around at least one axis, and the orientation of the main body unit 22 can be rotated relative to the leg unit 21.

[0011] The control unit 11 of the server 10 is a program-controlled device such as a CPU, and operates according to a program stored in the storage unit 12. In this embodiment, the control unit 11 accepts request information from the terminal device 20. The control unit 11 also executes processing based on the accepted request information. For example, as one of the processes, the control unit 11 transmits action information including an action instruction for instructing an action to be executed by the terminal device 20 and character string information representing the content of the voice uttered by the terminal device 20 to the terminal device 20 that is the sender of the request information.

[0012] In addition, in one example of the present embodiment, the control unit 11 acquires information representing an event such as a "date" of the user associated with date and time information representing a date and time (hereinafter referred to as event specifying information), and generates a related conversation sentence related to the acquired event specifying information in the process of executing a process of sending a voice uttered by the terminal device 20 on a date and time after the date and time represented by the date and time information to the terminal device 20. The detailed contents of the process of the control unit 11 will be described later.

[0013] The storage unit 12 is a disk device or a memory device, and holds a program executed by the control unit 11. The storage unit 12 also operates as a work memory for the control unit 11. In one example of the present embodiment, the storage unit 12 may store information for generating instructions to the terminal device 20. For example, the storage unit 12 holds a conversation sentence queue that accumulates conversation sentence candidates to be spoken by the terminal device 20. The contents of the conversation sentence queue will be described later.

[0014] The communication unit 13 is a network interface or the like, and sends various information to the terminal device 20 via the network in accordance with instructions input from the control unit 11. The communication unit 13 also outputs information received via the network to the control unit 11.

[0015] The control unit 31 of the terminal device 20 is a program-controlled device such as a CPU, and operates according to a program stored in the storage unit 32. In this embodiment, the control unit 31 transmits request information to the server 10 at a predetermined timing together with device identification information specific to the terminal device 20, which will be described later.

[0016] In one example of this embodiment, when a sensor unit 33 described later receives a voice input of a user, the control unit 31 of the terminal device 20 converts the input voice into character string information. This process can use a widely known voice recognition process, and the control unit 31 may execute this process by, for example, sending information of the input voice to a voice recognition server that executes the voice recognition process and receiving the recognized character string information.

[0017] Furthermore, the control unit 31, triggered by the user's voice input, sends request information to the server 10. This request information includes information for identifying the trigger (e.g., information indicating that the user has input voice) and information required for processing in the server 10, for example, character string information which is the recognition result of the voice input by the user.

[0018] That is, when the control unit 31 determines that a predetermined trigger has occurred, it collects information necessary for processing in the server 10 and sends request information including the collected information together with information specifying the trigger to the server 10. This trigger can be any trigger, such as voice input by the user as in the previous example, or the arrival of a predetermined time. The detailed operation of the control unit 31 will be described later.

[0019] The storage unit 32 is a memory device or the like, and holds programs executed by the control unit 31. The storage unit 32 also operates as a work memory for the control unit 31.

[0020] In this embodiment, the storage unit 32 may store setting information that associates the trigger with information that specifies information to be sent to the server 10. This setting information will be described later with a specific example. The storage unit 32 also stores device identification information that is uniquely set for the terminal device 20.

[0021] Furthermore, in one example of this embodiment, the storage unit 32 stores image data of an animation to be displayed on the display unit 34. Specifically, the storage unit 32 may store a plurality of image data of parts expressing the facial expressions of a character, such as image data of eye animation, such as image data of smiling eyes, image data of animated eyes with tears flowing, etc., and image data of animated mouths, such as image data of a closed mouth in a smiling state, image data of a closed mouth in a crying state, image data of an animated mouth during speech, etc.

[0022] The sensor unit 33 includes at least a microphone that is an audio sensor. The sensor unit 33 may also include a touch sensor, an acceleration sensor, etc. The sensor unit 33 outputs to the control unit 31 audio signals detected by each sensor, information indicating the position touched by the user, acceleration information, etc.

[0023] The display unit 34 is a liquid crystal display or the like, and displays image data according to instructions input from the control unit 31. In one example of the present embodiment, the display unit 34 displays the character's facial expression using image data of the eyes and mouth. The audio output unit 35 is a speaker or the like, and produces sound according to an audio signal input from the control unit 31.

[0024] The communication unit 36 ​​includes a network interface. The communication unit 36 ​​transmits and receives information to and from the server 10 via a network, wirelessly or via a wired connection. Specifically, the communication unit 36 ​​transmits request information and the like to the server 10 in accordance with instructions input from the control unit 31. The communication unit 36 ​​also outputs information received from the server 10 to the control unit 31.

[0025] The drive unit 37 drives the actuator to rotate the main body unit 22 relative to the leg units 21 in accordance with an instruction input from the control unit 31 .

[0026] Next, the operation of the control unit 11 of the server 10 of this embodiment will be described. In this embodiment, the control unit 11 of the server 10 includes a receiving unit 41, an event management unit 42, an event information acquisition unit 43, a conversation sentence generation unit 44, a conversation history management unit 45, an action information generation unit 46, and an instruction transmission unit 47, as shown in FIG.

[0027] The receiving unit 41 receives request information and device identification information from the terminal device 20. This request information includes information for specifying the cause (trigger) of the request for the action to be executed by the terminal device 20. Although the types of triggers will be described later, for example, voice input by the user is an example thereof. The above request information based on the trigger that there has been voice input by the user may include information for specifying the trigger and information representing the content of the voice input by the user. Here, the information representing the content of the voice input by the user may be character string information that is the result of recognizing the voice.

[0028] The receiving unit 41 outputs the information for specifying the trigger, the character string information representing the content of the voice input by the user, etc. included in the request information received here to the event information acquisition unit 43 and the action information generation unit 46.

[0029] The event management unit 42 stores and manages event information for each user in the storage unit 12. Here, the event information is the user's schedule, which is associated with date and time information and event specifying information for specifying the event.

[0030] The event information acquisition unit 43 receives the input of the character string information representing the content of the voice input by the user from the receiving unit 41. Then, the event information acquisition unit 43 determines whether the received character string information is information related to an event. Specifically, the event information acquisition unit 43 in this embodiment compares the character string information with a pattern of information related to a predetermined event.

[0031] Here, the pattern includes a part that matches words (date and time related words) representing predetermined dates and times such as "tomorrow", "the day after tomorrow", "next week", etc., and a part that matches words (event related words) related to events such as "date", "work", "beauty salon", etc. This pattern can be represented by, for example, a character string of a regular expression. For example, it is set as "[tomorrow|the day after tomorrow|weekend|next week][D+ day][W+ day of the week] [day][is|has]W+[something|what]*", etc.

[0032] In the above example, "*" is a regular expression that matches any character including spaces, "+" is a regular expression that matches one or more characters of a type specified by the preceding character, and [X|Y|...] is a regular expression that matches either X, Y.... [Z] means a pattern that may or may not exist, "D" matches a number, and "W" matches a letter. Therefore, the above string matches string information such as "I have a date tomorrow" or "I have an exam next Monday." In the above pattern, the part "[tomorrow|the day after tomorrow|weekend|next week][D+day][W+week][day]" corresponds to a date-time related word, and the part of the leading "W+" (matching any character) in "W+[is][is|is]" corresponds to an event-related word.

[0033] Also, this pattern is not limited to one, and there may be multiple patterns. For example, in addition to the above patterns, patterns such as "W+[is][is|what]*[tomorrow|the day after tomorrow|weekend|next week][D+day][W+week][day]" may be set. This example matches an example that does not match the above-mentioned patterns, such as "There's a live show tomorrow," and the event information acquisition unit 43 determines that the accepted character string information is event-related information when the character string information representing the content of the voice input by the user matches a pattern of event-related information (any of the patterns if there are multiple patterns) such as the above example.

[0034] That is, when the character string information expressing the contents of the voice input by the user matches the pattern of event-related information as in the above example and determines that the information is event-related, the event information acquisition unit 43 extracts date and time information and event identification information that identifies the event from the character string information. Specifically, when the character string information is "I have a date tomorrow," the event information acquisition unit 43 obtains date and time information for the day following the date and time when the process is being executed.

[0035] The date and time information is information indicating the date and time when an event occurs, which is estimated based on the date and time related words found by the above pattern. A widely known technique can be used for the process of estimating the date and time information from the date and time related words, etc., so a detailed description thereof will be omitted here.

[0036] For example, if the process is performed on December 15th, the event information acquisition unit 43 acquires date and time information of December 16th, which is "tomorrow" from that date. In addition, the event information acquisition unit 43 extracts "date" from the character string information as event specific information for identifying the event. A widely known method can be used to extract this event specific information.

[0037] The event information acquisition unit 43 outputs the extracted date and time information and event identification information that identifies the event to the conversation text generation unit 44. Furthermore, the event information acquisition unit 43 interrupts the process if the character string information representing the content of the voice input by the user does not match any pattern of information related to the event (if there are multiple patterns, none of them).

[0038] The conversation sentence generation unit 44 generates a conversation sentence upon receiving the date and time information and the event specification information output by the event information acquisition unit 43. Specifically, the conversation sentence generation unit 44 determines a date and time (utterance period) that is later than the date and time output by the event information acquisition unit 43.

[0039] The utterance period is determined, for example, as follows: In one example of this embodiment, the server 10 stores in the storage unit 12, as the day candidate information, a day number data table in which predefined day number candidates such as "1 day", "2 days", "1 week", etc., the number of days from the first day to the last day of the utterance period (utterance period length) defined for each day number candidate, and a word specifying the date of occurrence of an event (called a date and time indicator word) are associated with each other.

[0040] The conversation sentence generation unit 44 determines the first day of the utterance period by randomly selecting one of the number of days candidates included in the number of days data table and adding it to the date and time output by the event information acquisition unit 43. The conversation sentence generation unit 44 also determines the last day of the utterance period by adding the utterance period length associated with the selected number of days candidate to the first day of the utterance period.

[0041] As an example, when the date and time output by the event information acquisition unit 43 is "December 15th," if "2 days" is selected from the candidate days (with the associated speech period length being "0 days"), the conversation sentence generation unit 44 will set the first day of the speech period to "December 17th" and the last day to "December 17th."

[0042] The conversation sentence generating unit 44 also generates a conversation sentence using a date and time indicator associated with the selected number of days candidate and the event specifying information output by the event information acquiring unit 43. For example, the conversation sentence generating unit 44 randomly selects one of predetermined conversation sentence pattern candidates such as "By the way, how was the <event specifying information> of the <date and time indicator>?", "Ah, the <date and time indicator> was the <event specifying information>, right?", etc., and inserts the date and time indicator and the event specifying information into the selected conversation sentence pattern.

[0043] As a result, the conversation sentence generating unit 44 generates a conversation sentence such as "By the way, how was your date the day before yesterday?".

[0044] The conversation sentence generating unit 44 associates the conversation sentence thus generated with the determined speech period as a speech condition, and accumulates the associated conversation sentence in a conversation sentence queue stored in the storage unit 12. That is, in this example, the conversation sentence queue stored in the storage unit 12 of the server 10 is stored in the following manner: (C) is stored in association with the conversation text (D).

[0045] In addition to the above-mentioned speech period, the speech conditions may include conditions related to the time of speech, conditions such as the temperature at the time of speech, etc. Furthermore, the speech conditions are not necessarily required and may not be defined. If no speech conditions are defined (if there are no speech conditions), the conversation sentence without the defined speech conditions becomes a conversation sentence that can be spoken at any time.

[0046] In this embodiment, conversation sentences may be preregistered in the conversation sentence queue in addition to the conversation sentences generated by the conversation sentence generating unit 44. In this way, examples of conversation sentences preregistered may include, for example, "It was hot today," associated with the speech conditions that the maximum temperature was 35 degrees or higher and the time was after 6 p.m., and "Aren't you going to bed soon?" associated with the speech condition that the time was between 2 a.m. and 4 a.m.

[0047] The conversation history management unit 45 sequentially records, for each user, the contents of the voice input by the user that is accepted by the receiving unit 41 and the contents of the conversation sentences that are spoken by the terminal device 20 of the user that are instructed by the action information generation unit 46 that will be described later. In other words, the conversation history management unit 45 records the history of the conversation between the user and the terminal device 20.

[0048] Based on the information input from the receiving unit 41, the action information generating unit 46 determines the action to be executed by the terminal device 20 that sent the request, generates action information including information instructing the action (action instruction) and information required to execute the action (hereinafter referred to as parameter information), and outputs the action information to the instruction transmitting unit 47.

[0049] In one example of this embodiment, the memory unit 12 of the server 10 stores an action database including at least one record (R) that associates, as information for generating instructions to the terminal device 20, information (T) that identifies a trigger, information (V) to be compared with information representing the content of the voice input by the user (hereinafter referred to as comparison string information, although this comparison string information may not be necessary depending on the type of trigger), and information (S) representing the process to be executed by the server 10 to generate action information, as illustrated in FIG. 5.

[0050] The action information generation unit 46 obtains comparison string information (V, if any) associated with information (T) identifying a trigger input from the receiving unit 41 and information representing the processing to be performed by the server 10 to generate action information.

[0051] Then, when the comparison string information is acquired (when the comparison string information is associated with the information identifying the trigger), the action information generating unit 46 compares the comparison string information with the string information output by the receiving unit 41. Then, when the action information generating unit 46 determines that the string information output by the receiving unit 41 matches the comparison string information, it executes the process represented by the acquired information and generates action information.

[0052] Moreover, if the comparison character string information has not been acquired, the action information generating unit 46 executes the process indicated by the acquired information to generate action information.

[0053] As a specific example, the action database here contains records that associate information identifying a trigger that "there has been voice input by the user" with string information such as "*News [for|is]* [not|tell|read it out]*" as comparison string information to be compared with information expressing the content of the voice input by the user, with the information "obtain the news string information from a specified web server on the Internet, and instruct the string information to be read out."

[0054] This comparison string information is also expressed as a regular expression. Therefore, the above string will match string information such as "Tell me about today's news" and "Is there any news?"

[0055] For example, when the action information generation unit 46 receives input from the receiving unit 41 of information identifying a trigger, such as "there has been voice input by the user," and character string information, such as "Is there any news?", representing the content of the voice input by the user, the action information generation unit 46 searches the action database for a record including the information identifying the trigger.

[0056] Here, the action information generating unit 46 finds the above record from the action database, and compares the comparison string information contained in the record with the accepted string information. In the above example, the accepted string information "Is there any news?" is determined to match the comparison string information "*News [to|is]* [not|tell|read it out]*", so the action information generating unit 46 searches for information that indicates the process to be executed by the server 10, which is contained in the above record found by the search, for example, "(Step 1) Obtain news string information from a specified web server on the Internet, (Step 2) Generate instructions to read the string information (Step 3) "Generate instructions to display animation information to be played during reading" is obtained, and processing is performed according to this information.

[0057] That is, the action information generating unit 46 obtains news character string information from a predetermined web server on the Internet according to the read information. The action information generating unit 46 also generates a display instruction for animation information including information (which may be a file name for each image data) specifying image data of an animation to be displayed at the start of execution of action processes performed in parallel, image data of an animation to be displayed during the execution, and image data of an animation to be displayed at the end of the execution.

[0058] In this example, the action information generating unit 46 generates action information including an action instruction and parameter information, and outputs the action information to the instruction transmitting unit 47. The action instruction includes an instruction to read out character string information and an instruction to display animation information. The parameter information includes the acquired character string information and information for identifying image data of the animation.

[0059] Here, the information representing the process to be executed by the server 10 may include an instruction to "select a conversation sentence." When such an instruction is included, the action information generating unit 46 selects a conversation sentence in accordance with the instruction, for example, in the following manner.

[0060] The action information generating unit 46 extracts a conversation sentence that satisfies the speech condition associated with the conversation sentence from among the conversation sentences stored in the conversation sentence queue. Various information required to determine whether the speech condition is satisfied or not, such as the current date and time (date and time when the process is being executed) and weather information, may be obtained from an NTP (Network Time Protocol) server or a predetermined web server via a network.

[0061] The action information generating unit 46 randomly selects one of the conversation sentences extracted as satisfying the utterance conditions. The action information generating unit 46 also reads out the conversation history related to the user of the terminal device 20 that sent the request, which is recorded by the conversation history managing unit 45. The action information generating unit 46 then judges whether the selected conversation sentence will result in a natural conversation when uttered following the currently recorded conversation history.

[0062] This determination can be realized, for example, by using a neural network that has machine-learned the text of a conversation between humans to determine whether or not the sentence is valid as a sentence following the currently recorded conversation history, that is, whether or not there is continuity in the conversation. This type of processing is known as Next Sentence Prediction (NSP). As a neural network for performing next sentence prediction, for example, a model known as BERT (https: / / arxiv.org / pdf / 1706.03762.pdf) can be used. As training data for machine learning for such next sentence prediction, widely known training data and a machine learning processing method using the same can be adopted, such as a method using a pair of conversation sentences (a first conversation sentence and a second conversation sentence) and information indicating the continuity of the first and second conversation sentences associated with each other.

[0063] In this way, when the neural network is used to determine whether the selected conversational sentence is appropriate as a sentence following the currently recorded conversation history, that is, whether the conversation is continuous, the output of the neural network represents the appropriateness as a numerical value. The action information generating unit 46 determines that the conversation is natural (determines that there is continuity) when the numerical value exceeds a predetermined threshold value.

[0064] When the action information generating unit 46 determines that there is continuity as described above, it generates an action instruction including an instruction to read out the character string information and an instruction to display animation information. The action information generating unit 46 also generates parameter information including the character string information of the selected conversational text and information specifying image data of the animation, and instructs the instruction transmitting unit 47 to transmit the generated action instruction and parameter information as action information to the terminal device 20.

[0065] The instruction transmitting unit 47 transmits the action information generated by the action information generating unit 46 to the terminal device 20 which is the source of the request information received by the receiving unit 41 .

[0066] Next, a description will be given of the operation of the control unit 31 of the terminal device 20. In this embodiment, the control unit 31 is configured to functionally include a request sending unit 51, an action information receiving unit 52, a voice synthesis unit 53, and an action processing execution unit 54, as exemplified in Fig. 6.

[0067] When the request sending unit 51 determines that a predetermined trigger has occurred, it collects information necessary for processing in the server 10 and sends request information including the collected information together with information specifying the trigger to the server 10. Specifically, triggers such as a voice input by the user or a predetermined time being reached are listed in advance, included in the setting information, and stored in the storage unit 32.

[0068] As an example, the setting information, as illustrated in FIG. 7, lists and records, for each trigger, its name (trigger name: N), in association with information related to the processing of the trigger, such as occurrence conditions (C), information (P) that identifies information related to the trigger that is necessary for processing on the server 10, and interval time (T).

[0069] When the request sending unit 51 determines that the occurrence condition is satisfied by referring to this setting information, it assumes that a trigger has occurred in which the occurrence condition is satisfied, and refers to information (P) related to that trigger that is necessary for processing on the server 10.

[0070] The request sending unit 51 then collects information necessary for processing in the server 10, which is identified by the referenced information, and sends request information including the collected information and information identifying the trigger that has occurred (which may be the trigger name), to the server 10.

[0071] The action information receiving unit 52 receives action information from the server 10, and outputs the received action information to the action processing executing unit .

[0072] The voice synthesis unit 53 synthesizes voice data based on character string information input from the action processing execution unit 54, which will be described later. The voice synthesis unit 53 outputs the voice data obtained by synthesis to the action processing execution unit 54.

[0073] The action processing execution unit 54 extracts the action instruction and the parameter information from the action information sent by the server 10, and executes processing according to the action instruction. Specifically, as in the above example, a case will be described where the action information receiving unit 52 receives an action instruction including an instruction to read out the acquired character string information and an instruction to display the animation information, and action information including the acquired character string information and the parameter information including image data of the animation.

[0074] In this example, the action processing execution unit 54 outputs the acquired character string information to the voice synthesis unit 53 to acquire voice data. The action processing execution unit 54 also reads out image data of an animation specified by information included in the action information from the storage unit 22. The action processing execution unit 54 then outputs the voice data output by the voice synthesis unit 53 to the voice output unit 35 to produce a sound, and outputs the image data of the read animation to the display unit 34 to play the image data of the animation.

[0075] [Operation] The information processing system 1 of this embodiment has the above configuration and operates as in the following example. In the following example, it is assumed that the storage unit 12 of the server 10 stores, as an action database, information representing the process executed by the server 10 to generate action information for each trigger that is the cause of an action request, in association with the trigger.

[0076] In the following example, the action database contains the following information: · Information identifying the trigger (T): the user is having a conversation · Action to be performed: (Step 1) Select the text information of the conversation (Step 2) Generate instructions to read the string information (Step 3) The information to be included is 0 which generates an instruction to display animation information to be played during reading.

[0077] In addition, the memory unit 32 of the terminal device 20 stores, as setting information, for each trigger, information (C) that identifies the occurrence condition and information (P) that is related to the trigger and is necessary for processing on the server 10, as illustrated in FIG. 7.

[0078] In the following example, the setting information includes the following information: information identifying the trigger (trigger name N): there was a voice input by the user; occurrence condition (C): the user uttered a specific wake word; information identifying information required for processing in the server 10 (P): character string information of the content uttered by the user. Here, a wake word is a word such as "Hey, listen to me" or "Wake up," which should be recognized as the start of voice input when uttered by the user, and is determined in advance. The terminal device 20 may remove the character string portion corresponding to the wake word from the character string information of the content uttered by the user that is required for processing in the server 10.

[0079] Hereinafter, the operations of the server 10 that holds such setting information and the terminal device 20 will be described with reference to FIGS.

[0080] When a user speaks to the terminal device 20, such as "Hey, listen to me. I have a date tomorrow..." (S11 in FIG. 8), the terminal device 20 executes a process of recognizing the user's voice (S12) and acquires character string information corresponding to the voice spoken by the user. As already mentioned, the voice recognition process does not have to be performed by the terminal device 20 itself, and may be performed by accessing a voice recognition process service via a network.

[0081] The terminal device 20 refers to the setting information to check whether any of the trigger occurrence conditions is satisfied (S13). Here, since the user utters the wake word "Hey, listen to me," it is assumed that a trigger indicating "there is voice input by the user" has occurred (S13: Yes), and character string information of the content uttered by the user is collected according to the setting information. Note that, if it is determined in step S13 that none of the trigger occurrence conditions are satisfied (S13: No), the terminal device 20 ends the process.

[0082] Here, since the content uttered by the user has already been acquired as character string information in step S12, the terminal device 20 sends request information including the character string information and information identifying the trigger that has occurred (trigger name "voice input has been made by the user") to the server 10 (S14).

[0083] The server 10 receives the request information from the terminal device 20. Then, the server 10 determines whether the character string information included in the request information is information related to an event by comparing the character string information included in the request information with a predetermined pattern of information related to an event (S15).

[0084] If the pattern is "*[tomorrow|the day after tomorrow|weekend|next week][D+day][W+week][day][is|is]W+[ga][aru|nan]*", the accepted character string information is "Hey, listen. Tomorrow is a date...", so the server 10 judges that it matches the pattern. In other words, this character string information is judged to be information related to an event (S15: Yes).

[0085] 1 On the other hand, if it is determined that the information is not related to an event (S15: No), the server 10 executes another process, that is, a process obtained by referring to the action database.

[0086] The server 10 then extracts date and time information and event specification information from this character string information. (S16). Here, since "tomorrow" is selected, the server 10 selects the date and time when this process is being executed. (For example, December 15th) and obtains date and time information of "December 16th", which is the day after that. In addition, the server 10 extracts "date" from the character string information as event specifying information.

[0087] Next, the server 10 generates a conversation sentence. The server 10 first randomly acquires one number of days from the number of days candidates predefined in the number of days data table as the utterance period of the conversation sentence (S17: Decision of utterance period). Here, it is assumed that "7 days" is acquired as the number of days candidate. In the process of this step S16, the server 10 determines the utterance period length (here, "7 days") and the date and time indicator recorded in the number of days data table in association with the acquired number of days candidate. (here, "during this period") is obtained, and using the date and time information extracted in step S16 (December 16th), the obtained number of days candidate, and the utterance period length, the utterance period is determined to be "from December 23rd to December 30th."

[0088] In the process of determining the speech period, an example has been given in which one number of days is randomly determined from the candidate days predetermined in the number of days data table, but the present embodiment is not limited to this, and the server 10 may acquire a predetermined number of days associated with the event-specific information acquired in step S16 as the speech period.

[0089] In this example, for example, a data table is stored in the memory unit 12, in which a relatively short number of days is "4 days" when the event-specific information is a "date" (an event that can occur relatively frequently and whose topic lifetime is considered to be relatively short), and a relatively long number of days is "14 days" when the event-specific information is a "travel" (an event whose topic lifetime is considered to be relatively long), and the server 10 sets the speech period by referring to this data table.

[0090] In another example, the utterance period may be determined by referring to a data table that stores a plurality of candidate number of days in association with each of the event specification information acquired in step S16.

[0091] In this example, when the event-specific information is a "date" (an event that can occur relatively frequently and whose topic life-time is considered to be relatively short), the relatively shortest number of days are "1 day, 2 days, 3 days, 4 days" as candidate days, and when the event-specific information is a "trip" (an event whose topic life-time is considered to be relatively long), the relatively longest number of days are included, and a predetermined data table such as "1 day, 2 days, ..., 13 days, 14 days" is stored in the memory unit 12.

[0092] Then, the server 10 randomly selects one number of days from the number of days candidates predefined in the data table in association with the event identification information acquired in step S16, and sets the selected number of days as the utterance period.

[0093] In this example, if the event identified by the event identification information obtained in step S16 is a "date", a speech period of 1 to 4 days is set, and if the event identified by the event identification information obtained in step S16 is a "trip", a speech period of 1 to 14 days is set.

[0094] The server 10 generates a conversation sentence using the date and time noun associated with the selected number of days candidate, the event specifying information output by the event information acquisition unit 43, and information on the predetermined conversation sentence pattern candidate (S18). Here, the server 10 selects one from a plurality of predetermined conversation sentence pattern candidates, and generates a conversation sentence, for example, a conversation sentence such as "By the way, how was the date the other day?" by inserting the date and time noun ("the other day") and the event specifying information ("date").

[0095] The server 10 associates the conversation sentence generated in the process of step S18 with the speech period determined in the process of step S17 as a speech condition, and accumulates the associated conversation sentence in a conversation sentence queue stored in the storage unit 12 (S19).

[0096] By this process, the conversation sentence queue contains the conversation sentences, (1) Utterance conditions: The maximum temperature was 35 degrees or higher, and the time was after 6 p.m. Dialogue: "It was hot today." (2) Utterance condition: The time is between 2:00 a.m. and 4:00 a.m. Along with the dialogue "Shouldn't you go to bed soon?"... (n) Speech condition: The speech period is from December 23 to December 30. Conversation sentence: The conversation sentence "By the way, how was your date the other day?" is accumulated.

[0097] During this operation, the server 10 generates conversation history information by sequentially recording the contents of the voice input by the user and the contents of the conversation sentences uttered by the user's terminal device 20. For example, when the following conversation takes place between the user and the server 10, the conversation history information is stored.

[0098] In other words, the server 10 records conversation history information such as: User: "Hey, listen. We have a date tomorrow." Terminal device 20's utterance: "Oh, really?" User: "I wonder what the weather is like." Terminal device 20's utterance: "It looks like it's going to be sunny tomorrow."

[0099] In addition, the server 10 may execute other processes, that is, processes obtained by referring to the action database, in parallel with the processes in steps S16 to S19.

[0100] Thereafter, for example, on December 24th, if the user speaks to the terminal device 20, such as "Wake me up. Is there any news?" (S21 in FIG. 9), the terminal device 20 executes a process of recognizing the user's voice (S22) and obtains character string information corresponding to the voice spoken by the user.

[0101] The terminal device 20 also refers to the setting information to check whether any trigger occurrence condition has been satisfied (S23). In this case, since the user has uttered the wake word, it is assumed that a trigger indicating "there has been voice input by the user" has occurred (S23: Yes), and according to the setting information, the terminal device 20 collects character string information of the content uttered by the user, "Wake up. Is there any news?". The terminal device 20 then transmits request information including the character string information and information identifying the trigger that has occurred (trigger name "there has been voice input by the user") to the server 10 (S24).

[0102] The server 10 compares the comparison character string information "*News [for|is]* [not|tell|read it out]*" associated with the trigger "there has been voice input by the user" with the character string information "Wake up. Is there any news?" sent by the terminal device 20, and determines whether they match (S25).

[0103] In this case, the character string information “Wake up. Is there any news?” that the server 10 received from the terminal device 20 matches the comparison character string information, so the server 10 determines in step S25 that the comparison character string information matches the received character string information, and starts processing specified by the trigger indicating that “voice input has been made by the user” and the information associated with the comparison character string information.

[0104] For example, the server 10 acquires news character string information from a predetermined web server on the Internet, and transmits the obtained character string information to the terminal device 20 as action information together with an instruction to read the character string information out loud (S26).

[0105] In accordance with this instruction, the terminal device 20 executes a process of reading out the news information (S27). For example, the news that is read out may be something like "The warm weather continues from last week, but a cold wave is expected to hit at the end of the year."

[0106] The server 10 records the character string information transmitted and received between the server 10 and the terminal device 20 up to this point as a conversation history. In the above example, the conversation history is recorded as follows: User: "Wake up. Is there any news?" Terminal device 20 utterance: "'It's been warm since last week, but they say a cold wave is expected to hit at the end of the year,'"

[0107] In the processing up to this point, the server 10 determines whether the character string information included in the request information is event-related information or not by comparing the character string information included in the request information with a predetermined pattern of event-related information. However, since the character string information "Wake up. Is there any news?" does not match the pattern "*[tomorrow|the day after tomorrow|weekend|next week][D+day][W+week][day][is|is]W+[is][is|is|what]*", it is not determined to be event-related information, and the corresponding processing is not performed.

[0108] Thereafter, when the user further utters to the terminal device 20, for example, "Yes, it certainly was warm last week" (S28), the terminal device 20 acquires character string information corresponding to the voice uttered by the user. Then, the terminal device 20 determines that a trigger has occurred, for example, that "the user is having a conversation", and sends request information including the character string information of the content uttered by the user, "Yes, it certainly was warm last week", and information identifying the generated trigger, to the server 10 in accordance with the setting information (S29).

[0109] The server 10 judges whether the character string information included in this request information is event-related information or not by comparing the character string information included in the request information with a predetermined pattern of information related to an event. However, since this character string information does not match the above pattern, it is not regarded as event-related information and the corresponding process is not performed.

[0110] Meanwhile, the server 10 executes a process specified by information associated with information specifying the trigger "users are having a conversation", selects character string information of the conversational sentence, and sends an instruction to the terminal device 20 to vocalize the character string information (S30).

[0111] That is, in the process of step S30, the server 10 extracts a conversation sentence that satisfies four utterance conditions associated with the conversation sentence from among the conversation sentences stored in the conversation sentence queue (S41), as exemplified in Fig. 10. The server 10 also selects one of the conversation sentences that has not been selected here, for example at random, from among the conversation sentences (S42).

[0112] On the other hand, the server 10 refers to the conversation history relating to the user of the terminal device 20 that sent the request, and determines whether or not the conversational sentence selected in step S42 will result in a natural conversation when spoken following the currently recorded conversation history (S43).

[0113] Specifically, the server 10 obtains a numerical value (the more appropriate the value, the larger the value) indicating the appropriateness of the selected conversational sentence as a sentence that follows the currently recorded conversation history through next sentence prediction processing using a BERT model that has been machine-learned from text of conversations between humans.Then, when the obtained value exceeds a predetermined threshold, the server 10 determines that the conversation is natural (continuity exists), and when it does not, determines that the conversation is not natural (no continuity exists).

[0114] In step S43, when the server 10 determines that the selected conversation sentence will result in a natural conversation when spoken (S43: Yes), the server 10 generates action information including an instruction to read out the character string information of the selected conversation sentence.Then, the server 10 transmits the action information to the terminal device 20 (S44).

[0115] In step S43, if it is determined that the selected conversation sentence will not result in a natural conversation when spoken (S43: No), the server 10 returns to process S42 and continues the process. In addition, if there is no unselected conversation sentence in process S42, the server 10 executes a predetermined process, such as generating action information including an instruction to read out character string information of a predetermined conversation sentence and sending it to the terminal device 20 (S45: Execute default process).

[0116] Returning to FIG. 9, the terminal device 20 executes a process of reading out character string information in accordance with an instruction from the action information (S31).

[0117] As a specific example, in the processing of step S43 above, following a conversation history such as User: "Wake up. Is there any news?" and Terminal device 20's utterance: "'It's been warm since last week, but a cold wave is expected to hit at the end of the year,' they say," User: "Yeah. It certainly was warm last week," it is determined whether the conversation sentence "By the way, how was your date the other day?" naturally follows as one of the conversation sentences for which the utterance condition is satisfied.

[0118] If it is determined that there is continuity in the conversation, the server 10 instructs the terminal device 20 to speak this conversational sentence, so that the overall conversation will be something like this: User: "Wake up. Is there any news?" Terminal device 20 utterance: "'It's been warm since last week, but a cold wave is expected to hit at the end of the year,' they say." User: "Yeah. It was certainly warm last week." Terminal device 20 utterance: "By the way, how was your date the other day?"

[0119] In this manner, in this embodiment, conversations about past plans are displayed, making it possible to realize conversations that are tailored to the user, thereby evoking a sense of closeness.

[0120] [In the case of a single terminal device] In the explanation so far, the terminal device 20 recognizes the voice uttered by the user and transmits the obtained character string information to the server 10. Then, the server 10 generates and provides character string information (conversational text) that is the basis of the voice data to be uttered by the terminal device 20.

[0121] However, in one aspect of the embodiment of the present invention, the terminal device 20 may function as the information processing device. In this case, the server 10 is not necessarily required.

[0122] In this example, the control unit 31 of the terminal device 20 realizes the functions of a request sending unit 51, an action information receiving unit 52, a voice synthesis unit 53, and an action processing execution unit 54, and also operates as a receiving unit 41, an event management unit 42, an event information acquisition unit 43, a conversation sentence generation unit 44, a conversation history management unit 45, and an action information generation unit 46.

[0123] In this case, the action database, the conversation sentence queue, and other data stored in the storage unit 12 in the above description are all stored in the storage unit 32 of the terminal device 20.

[0124] In this example, the request sending unit 51 outputs the request information to the receiving unit 41 realized by the control unit 31 itself. The receiving unit 41 accepts and processes the output request information. The action information generating unit 46 outputs the generated action information to the action information receiving unit 52 realized by the control unit 31 itself.

[0125] The output and reception of this information may be performed via a network (communication unit 36) through a local loopback, or may be performed by storing and reading out the information in the storage unit 32 without going through a network.

[0126] [Speech stopping motion] In addition, the terminal device 20 may be configured to interrupt the playback of audio data (including audio data synthesized based on character string information received from the server 10) when the user performs a predetermined operation on the terminal device 20 during playback of the audio data.

[0127] For example, if the sensor unit 33 is equipped with a touch sensor, the predetermined operation may be performed by touching the touch sensor. In this example, when the terminal device 20 detects that the user has touched the touch sensor during playback of the audio data, the terminal device 20 interrupts the playback of the audio data.

[0128] In another example, the predetermined operation may be the user uttering a predetermined word. For example, when the terminal device 20 determines that the user uttered a word "shut" requesting quietness while playing back audio data, the terminal device 20 stops playing back the audio data.

[0129] In yet another example, the information processing system 1 may perform control so as not to vocalize a predetermined conversation sentence even when the user does not perform an operation.

[0130] Specifically, the sensor unit 33 of the terminal device 20 may include a human presence sensor (which is a widely known device and will not be described in detail) capable of detecting the number of people. Then, information on the number of people detected by the human presence sensor around the terminal device 20 may be used for selecting a conversation sentence.

[0131] In this example, when the server 10 or the terminal device 20 executing the function of the conversation sentence generation unit 44 generates a conversation sentence based on the information output by the event information acquisition unit 43 and registers it in a conversation sentence queue, the speech condition includes a condition related to the information on the number of people detected by the terminal device 20, in addition to the information on the speech period. As an example, the condition related to the number of people is set to a condition that the number of people is "1" (singular).

[0132] When the terminal device 20 selects a conversation sentence at the server 10, the terminal device 20 transmits request information to the server 10 including number information indicating the number of people detected in the vicinity.

[0133] Then, the server 10 or the terminal device 20, which performs the function of the action information generation unit 46, selects a conversation sentence that also satisfies the condition using the number of people information when extracting a conversation sentence that satisfies the speech condition associated with the conversation sentence from among the conversation sentences stored in the conversation sentence queue.

[0134] As in the above example, if the condition for the number of people to be "1" is included as a speaking condition for a conversation sentence related to past event information, when there are multiple people around the terminal device 20, the conversation sentence related to past event information will not be selected, thereby reducing the opportunity for the user's private information to be leaked.

[0135] [Expression of emotions] In one example of the present embodiment, the action information may further include information related to the emotion of the character displayed on the display unit 34 of the terminal device 20. The emotion information may include, for example, joy, The emotion information may include information that specifies an emotion, such as joy, sadness, etc. The emotion information may also include information that indicates no emotion (flat).

[0136] The terminal device 20 refers to the emotion information included in the received action information and selects the image data of the eyes to be displayed on the display unit 34. For example, when the emotion information is "Sad," the terminal device 20 selects and displays the image data of an animation of crying eyes from the image data of the eyes.

[0137] Furthermore, in one example of the present embodiment, when determining the emotion information to be included in the action information, the server 10 or the terminal device 20 that generates the character string information to be uttered may determine the emotion based on the words included in the character string information. Such processing can be performed, for example, as a process of determining the polarity of the sentence represented by the character string information based on the words included in the character string information. Specifically, when uttering news character string information, if the news character string information contains words representing a tragic incident, the news character string information is included in the action information together with information specifying the emotion of sadness.

[0138] [Information deleted] In addition, in this embodiment, the server 10 or the terminal device 20 storing the conversation sentence queue may delete conversation sentences associated with speech periods that have already passed (speech periods that have ended) from the conversation sentence queue at predetermined timing.

[0139] Furthermore, among the information stored in the conversation sentence queue, the conversation sentence stored by the conversation sentence generating unit 44 may be deleted from the conversation sentence queue when the conversation sentence is spoken, thereby preventing the same conversation sentence from being played back multiple times.

[0140] [Get from schedule information] Furthermore, in the above description of the present embodiment, the server 10 or the terminal device 20 functioning as the event information acquisition unit 43 extracts date and time information and event specification information from character string information when character string information representing the contents of the voice input by the user matches a pattern of information related to the event. However, the present embodiment is not limited to this.

[0141] In one example of the present embodiment, instead of or in addition to the above process, the event information acquisition unit 43 may acquire predetermined schedule information and extract date and time information and event 7 specification information. Specifically, the server 10 or the terminal device 20 functioning as the event information acquisition unit 43 receives in advance from the user settings of access rights to a web service in which the user registers schedule information. The terminal device 20 then acquires schedule information from the web service in accordance with the settings.

[0142] When the schedule information acquired here includes date and time information and event specific information (e.g., "date" or "work") that identifies an event in which the user is involved on that date and time, the event information acquisition unit 43 extracts the date and time information and the event specific information and outputs them to the conversation sentence generation unit 44.

[0143] According to this example, a conversation can be provided based on the user's past schedule, even if it does not appear in the conversation with the user.

[0144] [When the speech period is broadened] In the above explanation, the conversation sentence generation unit 44 generates the entire conversation sentence in advance and stores it in the conversation sentence queue. Therefore, the conversation sentence generation unit 44 includes in advance a relative demonstrative pronoun (such as "yesterday" or "the day before yesterday") that indicates the day when the past event, which is the subject of the conversation, occurred, according to the utterance period.

[0145] However, the present embodiment is not limited to this, and the conversation sentence generation unit 44 may generate a conversation sentence template that indicates only the position of a word indicating the date on which a past event occurred in the conversation sentence and store it in the conversation sentence queue. In this case, after a conversation sentence is selected, in the process of the action information generation unit 46, when an instruction to speak the selected conversation sentence is generated, a word indicating the date on which the target past event occurred may be generated from that point on.

[0146] In this example, the event information acquisition unit 43 causes the event management unit 42 to record the acquired event information and issue an event identifier that is unique to the event and identifies the recorded event.

[0147] When generating a conversation related to the event information (including date and time information and event specification information) acquired by the event information acquisition unit 43, the conversation generation unit 44 generates a conversation template that indicates only the position of a word indicating the date on which a past event occurred, and stores the template in the conversation queue in association with the corresponding event identifier. Here, the conversation template includes a code to be replaced with a word specifying the date and time, such as "How was the date on <date and time>?"

[0148] Thereafter, when the action information generation unit 46 selects the conversational sentence associated with this event identifier as the target of speech, the action information generation unit 46 refers to the event identifier associated with the selected conversational sentence and obtains event information (including at least the date and time information) corresponding to the event identifier from the event management unit 42.

[0149] Then, a word that specifies the current date and time is generated, and the code in the selected conversation sentence that should be replaced with the word that specifies the date and time is replaced. This word can be generated based on the difference (the interval in days) between the current date and time and the date and time when the target event occurred, if the interval is preset based on the number of days, such as "yesterday" for the 1st, "the day before yesterday" for the 2nd, "the other day" for the 3rd to 6th, "last week" for the 7th to 13th, etc.

[0150] Then, the action information generating unit 46 generates action information including an instruction to utter a conversation sentence including a word specifying the date and time.

[0151] [Features of the embodiment] The present embodiment is also characterized as follows: That is, one aspect of the present embodiment is an information processing device, comprising: an acquisition means for acquiring event specification information such as "date" that specifies a user's event associated with date and time information; and a conversation sentence generation means for generating a related conversation sentence that is a conversation sentence related to the event specification information, such as "How was your date last week?", in a process of uttering at a date and time after the date and time represented by the date and time information.

[0152] This information processing device may be implemented as a terminal device provided for each user, or may be implemented as a server communicatively connected to the terminal device to realize each of the above-mentioned means.

[0153] According to this example, the information processing device provides conversational text about past plans, and conversations about past events are realized, so that conversations about more private matters can be realized for the user, evoking a sense of closeness.

[0154] In addition, when the conversational text input by the user includes an event-related word such as "date" related to a predetermined event and a date / time-related word specifying a date and time such as "next weekend," a storage means is provided which associates and stores the event-specific information related to the event-related word with the date / time information represented by the date / time-related word.

[0155] In this example, the user can accumulate information about events simply by inputting it as conversation text, without having to register it as schedule information or the like.

[0156] Furthermore, the conversation sentence generation means may include an execution means which records the related conversation sentence, such as "How was your date last week?", in association with information indicating a period in which the related conversation sentence is to be spoken, and, if the period includes the current date and time, determines whether or not there is continuity between the conversation sentence input by the user and the related conversation sentence, and, when it is determined that there is continuity, executes speech processing of the related conversation sentence.

[0157] In this example, conversations about past plans appear at times that are determined to be natural successive, making the conversation sound natural.

[0158] Here, the execution means may determine whether or not the accepted conversational sentence and the related conversational sentence have continuity by using a neural network trained by machine learning using learning data that associates a first conversational sentence, a second conversational sentence, and information indicating the continuity of the first and second conversational sentences with each other.

[0159] Furthermore, when the user performs a predetermined input, such as a motion to forcibly stop the speech, while the related conversation sentence is being spoken, the speech may be stopped. This makes it possible to stop the speech when the speech is inappropriate.

[0160] The present invention may further include a playback device that utters the generated related conversation sentences, and a means for detecting a person in the vicinity of the playback device, and the playback device may be caused to utter the related conversation sentences only when there is a single person in the vicinity of the playback device. This makes it possible to prevent utterances in inappropriate situations. [Explanation of symbols]

[0161] 1 information processing system, 10 server, 11 control unit, 12 memory unit, 13 communication unit, 20 terminal device, 21 leg unit, 22 main body unit, 31 control unit, 32 memory unit, 33 sensor unit, 34 display unit, 35 voice output unit, 36 communication unit, 37 drive unit, 41 receiving unit, 42 event management unit, 43 event information acquisition unit, 44 conversation sentence generation unit, 45 conversation history management unit, 46 action information generation unit, 47 instruction transmission unit, 51 request transmission unit, 52 action information reception unit, 53 voice synthesis unit, 54 action processing execution unit.

Claims

1. An acquisition means for acquiring event identification information that identifies a user's event associated with date and time information; a conversation sentence generating means for generating a conversation sentence related to the event specifying information in a process of making an utterance at a date and time after the date and time represented by the date and time information; An information processing device comprising:

2. 2. The information processing device according to claim 1, a storage means for storing, when a conversation sentence input by a user includes an event-related word relating to a predetermined event and a date-and-time-related word specifying a date and time, the event-specific information related to the event-related word and the date-and-time information represented by the date-and-time-related word in association with each other. Information processing device.

3. 3. The information processing device according to claim 1, the conversation sentence generating means records the related conversation sentence in association with information indicating a period during which the related conversation sentence is to be uttered; and an execution means for executing speech processing of a related conversation sentence when the period includes the current date and time and the related conversation sentence has continuity with a conversation sentence input by a user.

4. 4. The information processing device according to claim 3, The execution means is an information processing device that determines whether the input conversational sentence and the related conversational sentence have continuity by using a neural network that has been machine-trained using learning data that associates a first conversational sentence, a second conversational sentence, and information indicating the continuity of the first and second conversational sentences.

5. 5. An information processing device according to claim 1, The information processing device stops the speech when a user performs a predetermined input while the related conversation sentence is being spoken.

6. 6. An information processing device according to claim 1, a playback device that speaks the generated related conversation sentences; The apparatus further includes a means for detecting a person in the vicinity of the playback device, An information processing device that causes the playback device to speak the related conversation sentence only when there is a single person located near the playback device.

7. Computer, An acquisition means for acquiring event identification information that identifies a user's event associated with date and time information; a conversation sentence generating means for generating a conversation sentence related to the event specifying information in a process of making an utterance at a date and time after the date and time represented by the date and time information; A program that functions as a

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