Information processing device and information processing method

Abstract

An information processing device (10) comprises: an estimation unit (12) that estimates the status of a discussion on the basis of statement content data indicating the statement content of each participant in the discussion; and a determination unit (13) that determines the content of a facilitation on the basis of an evaluation relating to the status of the discussion estimated by the estimation unit (12).

Description

Information Processing Apparatus and Information Processing Method

[0001] The present disclosure relates to an information processing apparatus and an information processing method.

[0002] Techniques related to facilitation, which is a technique for smoothly advancing a meeting and improving the significance of the meeting for participants, are known. A "good meeting" in facilitation is a state where all participants reach a conclusion in a state of agreement within a predetermined time. The role of a facilitator, who is the person who executes facilitation, is not to directly transmit various ideas himself / herself in order to aim for a good meeting, but to draw out the opinions of the participants so that the discussion proceeds smoothly and summarize them so that all participants can agree. The execution of facilitation as described above requires a plurality of advanced skills such as perception of the discussion situation, in-depth exploration of ideas, presentation of perspectives, and organization of discussions. Therefore, the concentration of burden due to dependence on a specific person with skills becomes a problem, and there is also an aspect that it is difficult to ensure the quality of the meeting.

[0003] Patent Document 1 below describes a technique for picking up a topic that has not been deeply discussed (that is, one with a high level of abstraction) from the conversation structure of the discussion content and determining the content of the questions as a facilitator (for example, prompting concretization).

[0004] Patent No. 7360655

[0005] However, in order to aim for a good meeting, it is necessary to execute facilitation from a multi-faceted perspective such as not only concretizing the ideas that have already emerged as in Patent Document 1, but also conducting a more comprehensive discussion and summarizing the conclusion that all participants can agree within a predetermined time.

[0006] Therefore, the present disclosure aims to automatically execute facilitation and efficiently advance a good meeting.

[0007] The information processing apparatus according to the present disclosure includes an estimation unit that estimates the situation of the discussion based on the speech content data indicating the speech content of each participant in the discussion, and a determination unit that determines the content of the facilitation based on an evaluation regarding the situation of the discussion estimated by the estimation unit.

[0008] According to this disclosure, facilitation can be performed automatically, enabling effective meetings to be conducted efficiently.

[0009] This is a configuration diagram showing one example of the configuration of an information processing device. This is a flowchart of the processing performed by the information processing device. This is a diagram illustrating an example of calculating the degree of equality of assertiveness. This is a diagram illustrating an example of processing by the decision unit. This is a configuration diagram showing another example of the configuration of the information processing device. This is a diagram showing an example of the hardware configuration of the information processing device.

[0010] Hereinafter, an embodiment of the information processing apparatus and information processing method relating to this disclosure will be described with reference to the drawings.

[0011] [Configuration of the Information Processing Device] Figure 1 shows a configuration diagram of the information processing device 10. As shown in Figure 1, the information processing device 10 includes an acquisition unit 11, an estimation unit 12, a determination unit 13, and an output unit 14 as components that realize the functions related to this disclosure. The functions of each unit will be described below.

[0012] The acquisition unit 11 is a functional unit that acquires speech content data indicating the content of each participant's statements from the audio data of the discussion, and includes an audio acquisition unit 11A and a speech recognition unit 11B. The "speech content data" is, for example, text data for each participant indicating the content of each participant's statements. The audio acquisition unit 11A acquires the audio data of the discussion collected by microphones set up in the conference room, the speech recognition unit 11B acquires audio data for each participant by identifying speakers based on existing technology using the acquired audio data, and acquires speech content data for each participant by converting the acquired audio data for each participant into text data.

[0013] The estimation unit 12 is a functional unit that estimates the state of the discussion based on the acquired data of each participant's statements. Specifically, the estimation unit 12 calculates the following five scores based on the data of each participant's statements, and uses the obtained scores as estimates of the degree of the discussion's state: • Idea abstraction level X1, which is the level of abstraction of the ideas that emerged in the discussion; • Number of ideas X2, which is the number of ideas that emerged in the discussion within a certain period; • Number of categories X3, which represents the number of categories into which the ideas that emerged in the discussion within a certain period were categorized; • Equality of participation level X4, which is the degree of equality of the participants' participation in the discussion; • Agenda relevance level X5, which is the degree of relevance of the participants' statements to the topic.

[0014] The estimation unit 12 estimates the idea abstraction level X1 by, for example, following the procedure below: (1) The estimation unit 12 divides a sentence about an idea contained in the speech content data of each participant into multiple words by morphological analysis, (2) calculates the co-occurrence probability of each divided word with a word list contained in a dictionary that includes words with multiple meanings for word sense disambiguation (WSD), (3) then repeats (1) and (2) above for each sentence about the idea contained in the speech content data to calculate the co-occurrence probability of each word in the entire sentence about the idea, calculates the average value of the obtained co-occurrence probabilities, and takes the obtained average value as the idea abstraction level for that idea. Note that "abstraction level" may also be information indicating whether the idea is sufficiently specific (or abstract) in relation to the topic, and may be a numerical value in the range of 0 to 100, or information indicating which level it is among several predetermined levels.

[0015] Regarding the number of ideas X2, the estimation unit 12 extracts ideas contained in the utterance data (i.e., ideas that have come up in the discussion so far) and estimates the number of extracted ideas as the number of ideas X2. For example, the estimation unit 12 may send a prompt to a large language model (LLM) built into the information processing device 10 or running on an external server to inquire about the number of ideas contained in the utterance data, along with the utterance data itself, and estimate the number of ideas responded to by the LLM as the number of ideas X2.

[0016] Regarding the number of perspectives X3, the estimation unit 12 extracts ideas contained in the utterance data (i.e., ideas that have come up in the discussion so far), categorizes the extracted ideas according to predetermined criteria, and estimates the number of perspectives (categories) obtained as the number of perspectives X3. For example, similar to the number of ideas X2 described above, the estimation unit 12 may send a prompt to the LLM to inquire about the number of perspectives contained in the utterance data and the utterance data itself, and estimate the number of perspectives answered by the LLM as the number of perspectives X3. Alternatively, the number of perspectives X3 may be estimated by inputting the target utterance data into a machine learning model generated by machine learning, which uses the utterance data as an explanatory variable and perspectives or the number of perspectives as the dependent variable, thereby obtaining the output perspectives or the number of perspectives.

[0017] Regarding the equality of active participation X4, the estimation unit 12 calculates the degree of equality of active participation among participants in the discussion based on the degree of equality of the number of times each participant speaks during the discussion, as follows: (i) The estimation unit 12 calculates the average number of times all participants speak. (ii) The estimation unit 12 calculates the standard deviation σ from the variance of the number of times each participant speaks relative to the calculated average. Note that the smaller the standard deviation σ, the more evenly the number of times each participant speaks. (iii) The estimation unit 12 calculates the equality of active participation X4 among participants using, for example, the following formula (1): Equality of active participation X4 = 1 - (σ / σ) ｍａｘ ) (1) Here, σ is the standard deviation, σ ｍａｘ σ is the largest possible standard deviation.ｍａｘ This can also be the standard deviation of only the maximum and minimum number of statements made by each participant. A concrete example of calculating the degree of equality of active participation X4 based on the distribution of statements made by each participant will be explained using specific numerical examples in the processing explanation below. Furthermore, it is not essential to determine the degree of equality of "number of statements" based on the distribution of statements made by each participant as a measure of the degree of equality of active participation among participants. Alternatively, for example, the degree of equality of "speaking volume" which indicates the amount of speaking by each participant may be determined.

[0018] The estimation unit 12 determines the topic relevance score X5 based on whether or not there have been any statements related to the purpose of the topic within a certain period of time. For example, the estimation unit 12 may provide the aforementioned LLM with statement content data and information on the purpose of the topic, and send a prompt instructing it to "determine whether or not the various statements that can be grasped from the statement content data are related to the purpose of the topic, and to determine the degree of relevance of the statements to the purpose of the topic in the overall discussion within a predetermined numerical range (for example, a range of 0.0 to 1.0: the higher the number, the higher the degree of relevance)," and estimate the degree of relevance returned by the LLM as the topic relevance score X5.

[0019] Returning to Figure 1, the decision unit 13 is a functional unit that determines the content of the facilitation based on the evaluation of the discussion status estimated by the estimation unit 12. Specifically, the decision unit 13 evaluates the discussion status from four aspects based on the degree of the discussion status (five scores X1 to X5) estimated by the estimation unit 12: (a) the degree of specificity of ideas, (b) the degree of comprehensiveness of the discussion, (c) the degree of participant satisfaction, and (d) the degree of relevance to the agenda. Based on the four indicators obtained (evaluation results) and predetermined thresholds for each indicator, the decision unit 13 determines the indicators that require improvement and determines the content of the facilitation according to the determined indicators. If there are multiple determined indicators, the decision unit 13 determines one indicator based on predetermined priority and determines the content of the facilitation according to the determined indicator. A specific example of how the facilitation content is determined will be explained using specific numerical examples in the processing explanation described later.

[0020] The output unit 14 is a functional unit that outputs the content of the facilitation determined by the determination unit 13. In this case, "output" can take various forms, such as display output, print output, and data transmission to the information processing device 10.

[0021] [Regarding the processing performed in the information processing device] The processing performed in the information processing device 10 (processing related to the information processing method of this disclosure) will be described below in accordance with the flowchart in Figure 2. For example, when a user (operator) of the information processing device 10 inputs a predetermined execution start command, the processing in Figure 2 is started in the information processing device 10.

[0022] First, the voice acquisition unit 11A acquires audio data of the discussion collected by microphones set up in the conference room (step S1 in Figure 2). Then, the speech recognition unit 11B acquires audio data for each participant by identifying the speaker based on existing technology using the acquired audio data, and acquires content data of each participant's statements by converting the acquired audio data for each participant into text data based on existing speech recognition technology (step S2).

[0023] The estimation unit 12 estimates the five scores mentioned above as a degree relating to the state of the discussion, based on the content data of each participant's statements (step S3). Regarding the idea abstraction level X1, the estimation unit 12 estimates the idea abstraction level X1 using the existing technology mentioned above.

[0024] Furthermore, regarding the number of ideas X2, the estimation unit 12 sends a prompt to the LLM, for example, to inquire about the number of ideas included in the utterance data, and the utterance data itself, and estimates the number of ideas responded to by the LLM as the number of ideas X2.

[0025] Furthermore, regarding the number of perspectives X3, the estimation unit 12 sends a prompt to the LLM, for example, to inquire about the number of perspectives included in the utterance data, along with the utterance data itself, and estimates the number of perspectives responded to by the LLM as the number of perspectives X3. Alternatively, the estimation unit 12 may input the target utterance data into a machine learning model generated by machine learning, which uses the utterance data as explanatory variables and perspectives or the number of perspectives as the objective variable, thereby obtaining the output perspectives or the number of perspectives and estimating the number of perspectives X3.

[0026] Furthermore, regarding the degree of equality of active participation X4, the estimation unit 12 calculates the degree of equality of the participants' active participation in the discussion based on the degree of equality of the number of times each participant speaks during the discussion, as follows: (i) The estimation unit 12 calculates the average number of times all participants speak. If participant A speaks 3 times, participant B speaks 8 times, and participant C speaks 7 times, as shown in Figure 3, the average number of times all participants speak is calculated to be "6 times". (ii) The estimation unit 12 calculates the standard deviation σ from the variance of the number of times each participant speaks relative to the calculated average. In the example in Figure 3, the variance of the number of times each participant speaks relative to the average is "4.666...", so the standard deviation σ is calculated to be "2.160...". (iii) The estimation unit 12 calculates the degree of equality of active participation X4 using, for example, the formula (1) described above. Degree of equality of active participation X4 = 1 - (σ / σ) ｍａｘ ) (1) Here, σ is the standard deviation, σ ｍａｘ σ is the largest possible standard deviation. ｍａｘ This is the standard deviation of only the maximum and minimum number of times each participant speaks. In the example in Figure 3, σ ｍａｘ This results in a standard deviation of 2.5, considering only the maximum value "8" and the minimum value "3". Therefore, the above σ and σ ｍａｘ By substituting this into equation (1), we can calculate the degree of equality of assertiveness X4 = 1 - (2.160... / 2.5) = 0.1359... ≈ 0.13.

[0027] Furthermore, with respect to the agenda relevance X5, the estimation unit 12 provides, for example, the utterance content data and the purpose of the agenda, as described above, and sends a prompt to the LLM instructing it to "determine whether the various utterances that can be grasped from the utterance content data are related to the purpose of the agenda, and to determine the degree of relevance of the utterances to the purpose of the agenda in the overall discussion within a predetermined numerical range (for example, a range of 0.0 to 1.0: the higher the number, the higher the degree of relevance)." The estimation unit 12 then estimates the degree of relevance provided by the LLM as the agenda relevance X5.

[0028] Returning to Figure 2, in the next step S4, the decision unit 13 evaluates the state of the discussion from four aspects, for example, as follows, based on the evaluation of the discussion state estimated by the estimation unit 12: (a) the degree of specificity of the ideas, (b) the degree of comprehensiveness of the discussion, (c) the degree of participants' acceptance, and (d) the degree of relevance to the agenda.

[0029] As an example, the decision unit 13 calculates an index indicating the degree of specificity of the idea, "Idea specificity Y1," according to the following formula (2): Y1 = 1 - X1 (2) As shown in Figure 4, if X1 = 0.7, X2 = 3, X3 = 12, X4 = 0.8, and X5 = 0.7, then the idea specificity Y1 = 1 - 0.7 = 0.3 is calculated.

[0030] Furthermore, the determination unit 13 calculates (b) an index indicating the degree of comprehensiveness of the discussion, "Comprehensiveness of the discussion Y2," according to the following formula (3): Y2 = X2 + X3 (3) From the numerical examples (X1 to X5) in Figure 4 mentioned above, the comprehensiveness of the discussion Y2 = 3 + 12 = 15 is calculated. Note that the above calculation method (addition of X2 and X3) is just one example, and other calculation methods such as multiplication of X2 and X3 may be adopted.

[0031] Furthermore, the decision unit 13 adopts the degree of participation equality X4 obtained in step S3 as (c) an index indicating the degree of participant satisfaction, "total satisfaction Y3". That is, Y3 = X4 = 0.8.

[0032] Similarly, the decision unit 13 adopts the agenda relevance X5 obtained in step S3 as the index "Agenda Relevance Y4" indicating the degree of agenda relevance. That is, Y4 = X5 = 0.7.

[0033] Returning to Figure 2, in the next step S5, the decision unit 13 determines which indicators require improvement based on the four indicators (Y1 to Y4) obtained in step S4 and predetermined thresholds for each indicator, and then determines the content of the facilitation according to the determined indicators. Here, as shown in Figure 4, the thresholds t1 = 0.5 for indicator Y1, t2 = 20 for indicator Y2, t3 = 0.7 for indicator Y3, and t4 = 0.5 for indicator Y4 are predetermined by prior machine learning or the like.

[0034] Specifically, the decision unit 13 determines whether each of the four indicators Y1 to Y4 exceeds the corresponding threshold t1 to t4, and selects the indicators that did not exceed the threshold as "missing features". The decision unit 13 then determines the content of the facilitation according to the selected indicators, i.e., "missing features," for example as follows. Note that the content of the facilitation may also be generated based on the response from the LLM after consulting with them. - If the missing feature is idea specificity Y1, ask questions to encourage deeper exploration of the ideas that have emerged from the discussion so far. - If the missing feature is comprehensiveness of the discussion Y2, present new perspectives and ask questions to encourage the generation of new ideas. - If the missing feature is everyone's agreement Y3, ask questions to check if there are any points to notice based on the opinions of others. - If the missing feature is topic relevance Y4, provide comments to summarize the opinions and ideas that have emerged so far.

[0035] In the numerical example in Figure 4, indicators Y1 and Y2 are selected as "missing features" because they did not exceed their respective thresholds t1 and t2. If multiple indicators are selected in this way, indicator Y1 is selected because it has a higher priority than indicator Y2, according to a predetermined priority order (for example, Y4 → Y1 → Y3 → Y2). In this case, the decision unit 13 may decide on the content of the facilitation to include questions that encourage further exploration of the ideas being discussed, such as, "What are your thoughts on point XX regarding the ideas being discussed?"

[0036] The priority order of "Y4 → Y1 → Y3 → Y2" in the above example follows the following principles: ・Relevance to the agenda (Y4) prioritizes producing an output relevant to the agenda. The idea is that it's important to produce as much output as possible, regardless of its nature. ・Specificity of the idea (Y1) prioritizes concrete output. The idea is that even if the output focuses on only one perspective or is biased towards someone's opinion, the more specific the output, the easier it is to move the discussion forward. ・All participants agree (Y3) prioritizes the agreement of all participants. Even if the output focuses on only one perspective or is an excellent idea, since discussion is a collaborative effort involving multiple participants, it's desirable to avoid bias and ensure that all participants agree as much as possible. ・Comprehensiveness of the discussion (Y2) prioritizes the comprehensiveness of the discussion. The idea is that the more diverse the perspectives considered, the better the idea.

[0037] Returning to Figure 2, in the next step S6, the output unit 14 outputs the facilitation content determined by the determination unit 13. This allows the user of the information processing device 10 to recognize the determined facilitation content.

[0038] According to the embodiments described above, facilitation can be performed automatically, enabling efficient and effective meetings. For example, facilitation can be performed from multiple perspectives, such as: concretizing ideas, conducting comprehensive discussions, and reaching a conclusion that satisfies all participants within a set time.

[0039] Note that the information processing apparatus 10 is not limited to the configuration of FIG. 1 described above, and other configurations can also be adopted. For example, like the information processing apparatus 10S shown in FIG. 5, it may be configured not to include the acquisition unit 11 of FIG. 1. In this case, the information processing apparatus 10S acquires the speech content data for each participant from an external server 20 having the functional units (voice acquisition unit 20A, voice recognition unit 20B) of the acquisition unit 11 of FIG. 1, thereby realizing the same functions as those of the above-described embodiments and obtaining the same effects.

[0040] In addition, in the above embodiment, in step S3 (estimation of the discussion situation) of FIG. 2, an example of calculating five scores X1 to X5 was shown. However, it is not essential to calculate all five scores. At least one of the five scores may be calculated, and the obtained score may be used as the estimation result of the discussion situation.

[0041] Similarly, in the above embodiment, in step S4 (evaluation of the discussion situation) of FIG. 2, an example of calculating four indicators Y1 to Y4 was shown. However, it is not essential to calculate all four indicators. Based on the score obtained in step S3 (estimation of the discussion situation), at least one of the four indicators may be calculated, and the obtained indicator may be used as the evaluation result of the discussion situation.

[0042] Also, in the above embodiment, in step S5 (determination of facilitation content) in FIG. 2, when determining an index that requires improvement, if there are a plurality of indices that did not exceed the threshold value, an example was shown in which one index is determined according to a predetermined priority order. However, the determination method is not limited to this, and another processing form as follows may be adopted. That is, when there are a plurality of indices that did not exceed the threshold value, one index may be determined based on the degree of deviation from the threshold value (that is, the degree to which the threshold value was not reached). In the numerical example of FIG. 4, as follows, when Y1 = 0.3, Y1 / t1 = 0.3 / 0.5 = 0.6; when Y2 = 15, Y2 / t2 = 15 / 20 = 0.75. The ratio of the score to the threshold value may be obtained, and the one with the smallest obtained ratio (in the above example, "index Y1") may be selected. In this case, since an index with a higher degree of deviation from the threshold value is determined as the "index that requires improvement", there is an effect that an appropriate index can be determined according to the degree of deviation from the threshold value (the degree to which the threshold value was not reached).

[0043] The gist of the present disclosure resides in the following [1] to [9].

[0044] [1] An information processing apparatus comprising: an estimation unit that estimates the situation of the discussion based on speech content data indicating the speech content of each participant in the discussion; and a determination unit that determines the content of facilitation based on an evaluation regarding the situation of the discussion estimated by the estimation unit.

[0045] [2] The information processing apparatus according to [1], wherein the estimation unit estimates the degree regarding the situation of the discussion from at least one viewpoint.

[0046] [3] The degree regarding the situation of the discussion includes at least one of the abstraction level of the ideas being discussed, the number of ideas being discussed, the number of categories (number of cutting edges) representing the number of ideas being discussed, the degree of equality of the participants' enthusiasm for the discussion, or the relevance of the participants' speech content to the topic of the discussion. The information processing apparatus according to [2].

[0047] [4] The information processing apparatus according to any one of [1] to [3], wherein the determination unit evaluates the status of the discussion from at least one aspect based on the status of the discussion estimated by the estimation unit, and determines the content of the facilitation based on the evaluation result obtained.

[0048] [5] The decision unit evaluates the status of the discussion from at least one of the following aspects: the degree of specificity of the ideas, the degree of comprehensiveness of the discussion, the degree of satisfaction of the participants, or the degree of relevance to the agenda, as described in [4].

[0049] [6] The information processing apparatus according to [4] or [5], wherein the determination unit determines an aspect that requires improvement based on a predetermined threshold value and the evaluation result for the aspect, and determines the content of the facilitation corresponding to the determined aspect.

[0050] [7] The information processing apparatus according to [6], wherein, if there are multiple determined sides, the determination unit determines one side based on a predetermined priority order and determines the content of the facilitation corresponding to the determined side.

[0051] [8] An information processing device according to any one of [1] to [7], further comprising: an acquisition unit that acquires data on the content of each participant's statements from the audio data of the discussion; and an output unit that outputs the content of the facilitation determined by the determination unit.

[0052] [9] An information processing method comprising: an information processing device estimating the status of a discussion based on content data indicating the content of statements made by each participant in the discussion; and an information processing device determining the content of facilitation based on an evaluation of the estimated status of the discussion.

[0053] [Explanation of terms, explanation of hardware configuration (Figure 6), etc.] The block diagram used in the description of the above embodiment shows functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or it may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wired, wireless, etc.). A functional block may be realized by combining the above one device or the above multiple devices with software.

[0054] Functions include, but are not limited to, judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, exploration, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, assumption, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating (mapping), and assigning. For example, a functional block (configuration part) that enables transmission is called a transmitting unit or transmitter. As mentioned above, the method of implementation is not particularly limited.

[0055] For example, the information processing device in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. Figure 6 is a diagram showing an example of the hardware configuration of the information processing device 10 according to one embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, bus 1007, etc.

[0056] In the following explanation, the term "device" can be replaced with "circuit," "device," "unit," etc. The hardware configuration of the information processing device 10 may include one or more of the devices shown in the figure, or it may be configured to omit some of the devices.

[0057] Each function in the information processing device 10 is realized by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, which allows the processor 1001 to perform calculations, control communication by the communication device 1004, and control at least one of data reading and writing in the memory 1002 and storage 1003.

[0058] The processor 1001 controls the entire computer, for example, by running an operating system. The processor 1001 may be composed of a central processing unit (CPU) that includes interfaces with peripheral devices, control units, arithmetic units, registers, etc.

[0059] Furthermore, the processor 1001 reads programs (program code), software modules, data, etc., from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes accordingly. The program used is one that causes the computer to execute at least a part of the operations described in the above embodiment. Although it has been explained that the various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The program may also be transmitted from a network via a telecommunications line.

[0060] The memory 1002 is a computer-readable recording medium and may consist of at least one of the following: ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. The memory 1002 may also be called a register, cache, main memory, etc. The memory 1002 can store executable programs (program code), software modules, etc., for carrying out a wireless communication method according to one embodiment of the present disclosure.

[0061] The storage 1003 is a computer-readable recording medium and may consist of at least one of the following: an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disc, a digital multipurpose disc, a Blu-ray® disc), a smart card, flash memory (e.g., a card, a stick, a key drive), a floppy® disk, a magnetic strip, etc. The storage 1003 may also be called an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, server, or other suitable medium including at least one of the memory 1002 and the storage 1003.

[0062] The communication device 1004 is hardware (transceiver / receiver device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc. The communication device 1004 may be configured to include, for example, a high-frequency switch, duplexer, filter, frequency synthesizer, etc., in order to implement at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0063] The input device 1005 is an input device that accepts input from an external source (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.). The output device 1006 is an output device that outputs to an external source (e.g., a display, speaker, LED lamp, etc.). The input device 1005 and the output device 1006 may be configured as an integrated unit (e.g., a touch panel).

[0064] Furthermore, each device, such as the processor 1001 and memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or different buses may be configured for each device.

[0065] Furthermore, the information processing device 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array), and some or all of each functional block may be realized by such hardware. For example, the processor 1001 may be implemented using at least one of these hardware components.

[0066] The notification of information is not limited to the embodiments described herein and may be carried out by other means. For example, the notification of information may be carried out by physical layer signaling (e.g., DCI (Downlink Control Information), UCI (Uplink Control Information)), upper layer signaling (e.g., RRC (Radio Resource Control) signaling, MAC (Medium Access Control) signaling, broadcast information (MIB (Master Information Block), SIB (System Information Block))), other signals, or combinations thereof. RRC signaling may also be called RRC messages, and may be, for example, RRC Connection Setup messages, RRC Connection Reconfiguration messages, etc.

[0067] Each aspect / embodiment described in this disclosure refers to LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (where x is, for example, an integer or decimal)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, may apply to at least one system utilizing UWB (Ultra-WideBand), Bluetooth®, or other appropriate systems, and to next-generation systems extended, modified, generated, or defined based thereon. Alternatively, multiple systems may be applied in combination (e.g., a combination of at least one of LTE and LTE-A with 5G).

[0068] The processing procedures, sequences, flowcharts, etc., of each aspect / embodiment described in this disclosure may be reordered, provided they do not contradict each other. For example, the methods described in this disclosure present various step elements using exemplary order and are not limited to the specific order presented.

[0069] Input and output information may be stored in a specific location (e.g., memory) or managed using a management table. Input and output information may be overwritten, updated, or appended to. Output information may be deleted. Input information may be transmitted to other devices.

[0070] The determination may be made by a value represented by one bit (0 or 1), by a boolean value (true or false), or by a numerical comparison (for example, a comparison with a predetermined value).

[0071] Each aspect / embodiment described in this disclosure may be used individually, in combination, or switched between as needed during implementation. Furthermore, notification of specific information (e.g., notification that "X is") is not limited to explicit notification, but may also be implicit (e.g., by not providing such notification).

[0072] Although the present disclosure has been described in detail above, it will be clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the intent and scope of the present disclosure as defined by the claims. Therefore, the descriptions in the present disclosure are illustrative and not intended to be restrictive in any way.

[0073] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, and so on, whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name.

[0074] Furthermore, software, instructions, information, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using at least one of wired technology (such as coaxial cable, fiber optic cable, twisted pair, or digital subscriber line (DSL)) and wireless technology (such as infrared or microwave), then at least one of these wired and wireless technologies is included in the definition of a transmission medium.

[0075] The information, signals, etc. described in this disclosure may be represented using any of the various different techniques. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0076] In addition, terms used in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of the channel and symbol may be a signal (signaling). Also, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, cell, frequency carrier, etc.

[0077] The terms “system” and “network” as used in this disclosure are interchangeable.

[0078] Furthermore, the information, parameters, etc., described in this disclosure may be expressed using absolute values, relative values ​​from a given value, or other corresponding information. For example, wireless resources may be indicated by an index.

[0079] The names used for the parameters described above are not restrictive in any way. Furthermore, the formulas and other expressions using these parameters may differ from those expressly disclosed in this disclosure. Various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name, and therefore, the various names assigned to these various channels and information elements are not restrictive in any way.

[0080] As used in this disclosure, the terms “determining” and “determining” may encompass a wide variety of actions. “Determining” may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, or inquiring (e.g., searching in a table, database, or other data structure), or ascertaining. “Determining” may also include receiving (e.g., receiving information), transmitting (e.g., sending information), inputting, outputting, or accessing (e.g., accessing data in memory). Furthermore, "judgment" and "decision" can include considering something as having been "judged" or "decided" after resolving, selecting, choosing, establishing, comparing, etc. In other words, "judgment" and "decision" can include considering something as having been "judged" or "decided" after some action. Also, "judgment (decision)" can be reinterpreted as "assuming," "expecting," or "considering."

[0081] In this disclosure, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on."

[0082] Any reference to elements using the designations “first,” “second,” etc., as used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Accordingly, references to the first and second elements do not imply that only two elements may be employed, or that the first element must precede the second element in any way.

[0083] Where the terms “include,” “including,” and variations thereof are used in this disclosure, these terms are intended to be inclusive, as is the term “comprising.” Furthermore, the term “or” as used in this disclosure is not intended to mean exclusive OR.

[0084] In this disclosure, if articles are added through translation, such as a, an, and the in English, this disclosure may include the fact that the noun following these articles is plural.

[0085] In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combine" may be interpreted similarly to "different."

[0086] 10, 10S... Information processing device, 11... Acquisition unit, 11A, 20A... Voice acquisition unit, 11B, 20B... Voice recognition unit, 12... Estimation unit, 13... Determination unit, 14... Output unit, 20... External server, 1001... Processor, 1002... Memory, 1003... Storage, 1004... Communication device, 1005... Input device, 1006... Output device, 1007... Bus.

Claims

1. An information processing device comprising: an estimation unit that estimates the status of a discussion based on content data showing the content of each participant's statements in the discussion; and a determination unit that determines the content of facilitation based on the evaluation of the status of the discussion estimated by the estimation unit.

2. The information processing apparatus according to claim 1, wherein the estimation unit estimates the degree of the status of the discussion from at least one viewpoint.

3. The information processing apparatus according to claim 2, wherein the degree relating to the status of the discussion includes at least one of the following: the degree of abstraction of the ideas being discussed, the number of ideas being discussed, the number of categories representing the number of ways the ideas being discussed are categorized, the degree of equality of the participants' active participation in the discussion, or the degree of relevance of the participants' statements to the agenda of the discussion.

4. The information processing apparatus according to claim 1, wherein the determination unit evaluates the status of the discussion from at least one aspect based on the status of the discussion estimated by the estimation unit, and determines the content of the facilitation based on the evaluation result obtained.

5. The information processing device according to claim 4, wherein the decision unit evaluates the status of the discussion from at least one of the following aspects: the degree of specificity of the ideas, the degree of comprehensiveness of the discussion, the degree of satisfaction of the participants, or the degree of relevance to the agenda.

6. The information processing apparatus according to claim 4, wherein the determination unit determines the side surface that requires improvement based on a predetermined threshold value and the evaluation result for the side surface, and determines the content of the facilitation corresponding to the determined side surface.

7. The information processing apparatus according to claim 6, wherein, if there are multiple determined sides, the determination unit determines one side based on a predetermined priority order and determines the content of the facilitation corresponding to the determined side.

8. The information processing apparatus according to claim 1, further comprising: an acquisition unit that acquires data on the content of each participant's statements from the audio data of the discussion; and an output unit that outputs the content of the facilitation determined by the determination unit.

9. An information processing method comprising: a step of an information processing device estimating the status of a discussion based on statement data indicating the content of statements made by each participant in the discussion; and a step of the information processing device determining the content of facilitation based on an evaluation of the estimated status of the discussion.

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