Information processing device and information processing method

Abstract

The present disclosure relates to an information processing device and an information processing method that make it possible to improve the quality of communication in a vehicle. A vehicle-mounted system determines a common keyword indicating a matter of concern common to a plurality of occupants in a vehicle, transmits the common keyword to a cloud system, and receives and reproduces a common content that is a content delivered from the cloud system on the basis of the common keyword and attribute data of the plurality of occupants. The cloud system generates a content search word on the basis of the common keyword and the attribute data of the plurality of occupants, searches a content data storage unit using the content search word, and delivers, as the common content, content data obtained as a result of the search to the vehicle-mounted system. The present technology can be applied to, for example, a content delivery system that delivers a content to a vehicle via a network.

Description

Information Processing Apparatus and Information Processing Method

[0001] The present disclosure relates to an information processing apparatus and an information processing method, and more particularly to an information processing apparatus and an information processing method capable of improving the quality of communication in a vehicle.

[0002] In recent years, electric vehicles are configured such that multiple passengers can simultaneously view content on the same display device by equipping the driver's seat and the front passenger seat with large display devices or installing display devices in the rear seats. Therefore, for example, by playing content that multiple passengers are commonly interested in on the display device, it is expected that multiple passengers in an electric vehicle can communicate well with each other.

[0003] Patent Document 1 discloses an information providing system that identifies the attributes of users riding in a vehicle and outputs content in an output mode associated with those attributes. Patent Document 2 discloses a content distribution system that determines one of a plurality of viewers as the content selection subject based on user profiles associated with the user IDs of the plurality of viewers existing near an in-vehicle device, and outputs content based on the preference information of that one viewer.

[0004] Japanese Patent Application Laid-Open No. 2023-172500, Japanese Patent Application Laid-Open No. 2017-79417

[0005] By each passenger permitting the use of their attribute information, as described above, it becomes possible to play content that multiple passengers are commonly interested in. However, for example, in a situation where it is not known with whom one will ride in the vehicle, from the viewpoints of data security and communication, it is difficult for a passenger to permit the use of their attribute information, and as described above, it has not been possible to easily achieve good communication.

[0006] For example, if an information device installed in a vehicle is designed to be used by only one person at a time, the content output will be based solely on that one person's preferences. Furthermore, if the information device is designed to incorporate the preferences and opinions of multiple passengers, it will require constant dialogue and decision-making, resulting in significant communication costs.

[0007] This disclosure is made in light of these circumstances and aims to improve the quality of communication within vehicles.

[0008] The information processing device in the first aspect of this disclosure includes a common keyword determination unit that determines common keywords indicating matters of common interest to multiple passengers in a vehicle and transmits the common keywords to a cloud system, and a content playback unit that receives and plays common content, which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers.

[0009] The first aspect of the information processing method of this disclosure includes determining common keywords that indicate common interests for multiple passengers in a vehicle, transmitting the common keywords to a cloud system, and receiving and playing common content, which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers.

[0010] In the first aspect of this disclosure, common keywords are determined that indicate common interests for multiple passengers in the vehicle, the common keywords are transmitted to a cloud system, and common content, which is content delivered from the cloud system based on the common keywords and attribute data of the multiple passengers, is received and played.

[0011] The information processing device in the second aspect of this disclosure includes a content search word generation processing unit that generates content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers, and a common content extraction unit that searches a content data storage unit using the content search words and distributes the content data obtained as a search result to the in-vehicle system as common content.

[0012] The information processing method of the second aspect of this disclosure includes generating content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers, and searching a content data storage unit using the content search words, and distributing the content data obtained as a result of the search to the in-vehicle system as common content.

[0013] In the second aspect of this disclosure, content search words are generated based on common keywords indicating common interests for multiple passengers in the vehicle, transmitted from the in-vehicle system, and attribute data of multiple passengers. The content data storage unit is searched using the content search words, and the content data obtained as a result of the search is distributed to the in-vehicle system as common content.

[0014] This is a diagram illustrating a content distribution system to which this technology is applied. This is a block diagram illustrating an example configuration of the first embodiment of the content distribution system. This is a diagram illustrating an example of voice common keyword determination processing. This is a diagram illustrating an example of attribute common keyword determination processing. This is a diagram illustrating a first example of content search word generation processing. This is a diagram illustrating a second example of content search word generation processing. This is a flowchart illustrating an example of content distribution processing on the in-vehicle system side. This is a flowchart illustrating an example of content distribution processing on the cloud system side. This is a flowchart illustrating an example of voice common keyword determination processing. This is a flowchart illustrating an example of personal authentication processing. This is a flowchart illustrating an example of attribute common keyword determination processing. This is a flowchart illustrating a first example of content search word generation processing. This is a flowchart illustrating a second example of content search word generation processing. This is a block diagram illustrating an example configuration of the second embodiment of the content distribution system. This is a flowchart illustrating an example of content distribution processing on the in-vehicle system side in the content distribution system of Figure 14. This is a flowchart illustrating gaze common keyword determination processing. This is a block diagram illustrating an example configuration of one embodiment of a computer to which this technology is applied.

[0015] The following describes in detail a specific embodiment of this technology, with reference to the drawings.

[0016] <First Configuration Example of a Content Distribution System> A first embodiment of a content distribution system to which this technology is applied will be described with reference to Figures 1 to 13.

[0017] Figure 1 shows an example of the configuration of the content distribution system 11.

[0018] As shown in Figure 1, the content distribution system 11 is configured by connecting the in-vehicle system 22 and the cloud system 23 via the network 21. In this embodiment, the distribution of content based on a conversation between two passengers a and passenger b is described, but this technology can be applied to the distribution of content based on conversations between two or more passengers.

[0019] The in-vehicle system 22 comprises a data input unit 31, a data processing unit 32, and a content playback unit 33, and is installed in the vehicle. Furthermore, if passengers a and b are in the vehicle, personal information terminals 34a and 34b owned by passengers a and b, respectively, also constitute the in-vehicle system 22.

[0020] The data input unit 31 is comprised of, for example, cameras that photograph the interior and exterior of the vehicle, and microphones that capture the conversations of passengers a and b. The data input unit 31 then supplies the image data of the interior and exterior of the vehicle obtained by the cameras, and the audio data of the conversations of passengers a and b obtained by the microphones, to the data processing unit 32.

[0021] The data processing unit 32 generates general attribute data (for example, gender, clothing, age, etc.) that indicates general attributes of passengers a and b based on image data supplied from the data input unit 31. The data processing unit 32 also determines common voice keywords, which are keywords extracted from the conversation between passengers a and b and indicate common interests for passengers a and b, based on the voice data supplied from the data input unit 31. The data processing unit 32 then transmits the general attribute data and common voice keywords to the cloud system 23 via the network 21.

[0022] The content playback unit 33 is composed of, for example, a display device that displays video and an audio device that outputs sound, and plays common content distributed from the cloud system 23 via the network 21. Here, the common content is content that is presumed to be of common interest to passengers a and b.

[0023] As the display device for the content playback unit 33, for example, a direct-view display such as an LCD (Liquid Crystal Display), an LED (Light Emitting Diode) display, or an OLED (Organic Light Emitting Diode) display can be used. Alternatively, as the display device for the content playback unit 33, a spatial display type display such as a HUD (Head Up Display) that projects images onto the vehicle window or displays images on a transparent display installed on the vehicle window may be used.

[0024] Furthermore, when Augmented Reality (AR) content is distributed and displayed in the content distribution system 11, a glasses-type display such as so-called AR glasses can be used as the display device for the content playback unit 33. A Head-Up Display (HUD) can also be used when displaying AR content. AR content is content designed for AR display, intended to be superimposed onto real space. For example, the position and content of the AR content are determined based on objects (position and content) in the background of real space, and the AR content is displayed superimposed on the background.

[0025] Personal information terminal 34a is, for example, passenger a's smartphone, and if passenger a has given permission for the use of personal attribute data on the cloud system 23, it notifies the cloud system 23 of passenger a's permission to use personal attribute data via the network 21. Similarly, personal information terminal 34b is, for example, passenger b's smartphone, and if passenger b has given permission for the use of personal attribute data on the cloud system 23, it notifies the cloud system 23 of passenger b's permission to use personal attribute data via the network 21.

[0026] The cloud system 23 is configured to include a personal attribute data storage unit 41, a content data storage unit 42, and a content distribution processing unit 43, and is built by multiple servers located on the network 21.

[0027] The personal attribute data storage unit 41 stores personal attribute data (for example, age, gender, height, hobbies, favorite vehicles, vehicles that the user of the content distribution system 11 dislikes or is not good at) that indicates the personal attributes of passengers a and passenger b.

[0028] The content data storage unit 42 stores data for various types of content distributed by the content distribution system 11. For example, this content may consist of moving images, still images, text information, audio information, and so on.

[0029] The content distribution processing unit 43 acquires either general attribute data of passengers a and b transmitted from the in-vehicle system 22, or personal attribute data of passengers a and b stored in the personal attribute data storage unit 41. The content distribution processing unit 43 then compares the attribute data of passengers a and b (either the general attribute data or the personal attribute data acquired by the content distribution processing unit 43) with a common voice keyword transmitted from the in-vehicle system 22, and generates a content search word to be used when searching for common content from the content data storage unit 42.

[0030] For example, the content distribution processing unit 43 generates content search words that are positive in both attribute data indicating the attributes of passengers a and b, and common voice keywords extracted from the conversation between passengers a and b. Alternatively, the content distribution processing unit 43 generates content search words that are positive in at least one of passengers a and b, and not negative in the other (positive, or neither positive nor negative), in both attribute data indicating the attributes of passengers a and b, and common voice keywords extracted from the conversation between passengers a and b.

[0031] The content distribution processing unit 43 then transmits the content data obtained as a result of searching the content data storage unit 42 using the content search word to the in-vehicle system 22.

[0032] The content distribution system 11 configured in this way can play common content that is estimated to be of interest to both passengers a and b by comparing common voice keywords extracted from the content of the conversation between passengers a and b with the attribute data (general attribute data or personal attribute data) of passengers a and b. For example, even if the level of intimacy between passengers a and b is low and passengers a and b cannot disclose their own attribute data to each other, the content distribution system 11 can estimate common content that is of interest to both passengers a and b.

[0033] As a result, the content distribution system 11 can improve the quality of communication between passengers a and b in the vehicle by playing common content, without requiring them to incur significant communication costs.

[0034] Figure 2 is a block diagram showing a first embodiment of a content distribution system 11 to which this technology is applied.

[0035] As shown in Figure 2, the content distribution system 11 consists of an in-vehicle system 22 equipped with a data input unit 31, a data processing unit 32, a content playback unit 33, and personal information terminals 34a and 34b, and a cloud system 23 equipped with a personal attribute data storage unit 41, a content data storage unit 42, and a content distribution processing unit 43.

[0036] The data processing unit 32 is configured to include a general-purpose attribute data generation unit 51 and a voice common keyword determination processing unit 52.

[0037] The general-purpose attribute data generation unit 51 performs image recognition processing on the image data supplied from the data input unit 31 to recognize the gender, clothing, age, etc. of passengers a and b, generate general-purpose attribute data for passengers a and b, and transmit it to the cloud system 23.

[0038] The voice common keyword determination processing unit 52 recognizes the conversation between passenger a and passenger b by performing speech recognition processing on the voice data supplied from the data input unit 31. The voice common keyword determination processing unit 52 then determines the keywords that both passenger a and passenger b agree with from among the keywords extracted from the conversation between passenger a and passenger b as the voice common keyword and transmits it to the cloud system 23.

[0039] For example, if audio data of a conversation as shown in Figure 3A is supplied, the common audio keyword determination processing unit 52 extracts the keywords "roller coaster," "Ferris wheel," and "cruise ship" from the audio data of that conversation. Then, from the context of the conversation between passenger a and passenger b, the common audio keyword determination processing unit 52 infers, as shown in Figure 3B, that passenger a is positive towards the keywords "roller coaster," "Ferris wheel," and "cruise ship," and that passenger b is negative towards the keyword "roller coaster" and positive towards the keywords "Ferris wheel" and "cruise ship." Therefore, the common audio keyword determination processing unit 52 can determine that the keywords "Ferris wheel" and "cruise ship," which are positive towards both passenger a and passenger b, are common audio keywords. Then, as shown in Figure 3C, the common audio keyword determination processing unit 52 creates a list in which the common audio keywords "Ferris wheel" and "cruise ship" are registered.

[0040] The content distribution processing unit 43 is comprised of a personal authentication processing unit 61, an attribute data integration unit 62, an attribute common keyword determination processing unit 63, a common keyword acquisition unit 64, a content search word generation processing unit 65, and a common content extraction unit 66.

[0041] The personal authentication processing unit 61 communicates with the personal information terminal 34a regarding the handling of personal attribute data and determines whether or not the use of personal attribute data has been authorized by passenger a. For example, if the personal authentication processing unit 61 receives notification from the personal information terminal 34a that permission to use personal attribute data has been granted by passenger a, it determines that the use of personal attribute data has been granted by passenger a, obtains passenger a's personal attribute data from the personal attribute data storage unit 41, and supplies it to the attribute data integration unit 62. On the other hand, if the personal authentication processing unit 61 does not receive notification from the personal information terminal 34a that permission to use personal attribute data has been granted by passenger a, it determines that the use of personal attribute data has not been granted by passenger a, and instructs the attribute data integration unit 62 to obtain passenger a's general attribute data. Similarly, the personal authentication processing unit 61, according to the results of communication with the personal information terminal 34b regarding the handling of personal attribute data, instructs the attribute data integration unit 62 to obtain passenger b's personal attribute data from the personal attribute data storage unit 41, or to obtain passenger b's general attribute data.

[0042] When the personal attribute data of passenger a is supplied by the personal authentication processing unit 61, the attribute data integration unit 62 acquires the personal attribute data of passenger a. When the personal attribute data of passenger b is supplied by the personal authentication processing unit 61, the attribute data integration unit 62 acquires the personal attribute data of passenger b. Alternatively, when the personal authentication processing unit 61 instructs the attribute data integration unit 62 to acquire the general attribute data of passenger a, the attribute data integration unit 62 acquires the general attribute data of passenger a from the general attribute data generation unit 51. When the personal authentication processing unit 61 instructs the attribute data integration unit 62 to acquire the general attribute data of passenger b, the attribute data integration unit 62 acquires the general attribute data of passenger b from the general attribute data generation unit 51. The attribute data integration unit 62 then supplies the attribute data common keyword determination processing unit 63 with a list of attribute data that integrates the attribute data of passenger a and passenger b (either the general attribute data or the personal attribute data acquired by the attribute data integration unit 62).

[0043] For example, in A of FIG. 4, an example of a list of attribute data in which the personal attribute data of each of passenger a and passenger b is registered for attribute items such as "age", "gender", "height", "hobby", "favorite vehicle", and "unfavorable / hated vehicle" is shown.

[0044] The attribute common keyword determination processing unit 63 determines, as attribute common keywords, the keywords that are commonly registered for both passenger a and passenger b in the positive attribute items in the list of attribute data supplied from the attribute data integration unit 62, and supplies them to the content search keyword generation processing unit 65.

[0045] For example, when attribute data as shown in A of FIG. 4 is supplied, the attribute common keyword determination processing unit 63 can extract, as attribute common keywords, the keywords "theme park" and "cruise ship" that are commonly registered for both passenger a and passenger b in the positive attribute items "hobby" and "favorite vehicle". Then, as shown in B of FIG. 4, the attribute common keyword determination processing unit 63 creates a list in which the attribute common keywords "theme park" and "cruise ship", which are common and positive for both passenger a and passenger b, are registered.

[0046] The common keyword acquisition unit 64 acquires the voice common keywords transmitted from the voice common keyword determination processing unit 52 and supplies them to the content search keyword generation processing unit 65.

[0047] The content search keyword generation processing unit 65 compares the attribute common keywords supplied from the attribute common keyword determination processing unit 63 with the voice common keywords supplied from the common keyword acquisition unit 64, generates content search keywords according to the comparison result, and supplies them to the common content extraction unit 66.

[0048] For example, as shown in FIG. 5, the content search keyword generation processing unit 65 compares the attribute common keywords "theme park", "cruise ship", and "Ferris wheel" with the voice common keywords "theme park", "cruise ship", and "merry-go-round". Then, according to the comparison results, the content search keyword generation processing unit 65 can generate the keywords "theme park" and "cruise ship" included in both the attribute common keywords and the voice common keywords as content search keywords.

[0049] Alternatively, as shown in FIG. 6, the content search keyword generation processing unit 65 may generate content search keywords according to the comparison results between the voice common keywords and the attribute data. For example, the content search keyword generation processing unit 65 compares the voice common keywords with the attribute data, and among the voice common keywords, generates those that are both positive in the attribute data as content search keywords. Alternatively, the content search keyword generation processing unit 65 generates those in which one is positive and the other is not negative (i.e., positive or neither positive nor negative) in the attribute data as content search keywords.

[0050] That is, the content search keyword generation processing unit 65 confirms the characteristics (positive / negative / neither) that apply to each of the voice common keywords "theme park", "cruise ship", and "Ferris wheel" based on the attribute data. In the example shown in FIG. 6, for the voice common keyword "theme park", it is positive for both passenger a and passenger b. For the voice common keyword "cruise ship", passenger a is positive and passenger b is neither. For the voice common keyword "Ferris wheel", passenger a is neither and passenger b is negative. Therefore, the content search keyword generation processing unit 65 can generate the voice common keywords "theme park" and "cruise ship" in which one of passenger a and passenger b is positive and the other is not negative as content search keywords.

[0051] In this way, the content search word generation processing unit 65 generates content search words from among the common voice keywords that are not rejected by either passenger a or passenger b in the attribute data, so that it can handle cases such as when a passenger becomes interested in something during a conversation, even if they were not initially very interested.

[0052] The common content extraction unit 66 searches the content data storage unit 42 using content search words supplied from the content search word generation processing unit 65, and distributes the content data obtained as a result of the search to the in-vehicle system 22 as common content.

[0053] As described above, the content distribution system 11 is configured to determine common voice keywords from among the keywords extracted from the conversation between passengers a and b that are positive for both passengers a and b. Therefore, the content distribution system 11 can identify common content that interests both passengers a and b without requiring them to confirm each other's intentions.

[0054] The content distribution system 11 then compares common voice keywords with the attribute data of passengers a and b, extracts common items between them, and adjusts the ratio of interest levels in the conversation to the ratio of common items, thereby automatically presenting common content of interest to both parties without bias towards one's interests. In this way, the content distribution system 11 can estimate common content without passengers a and b disclosing their own attribute data to each other, and can improve the quality of communication within the vehicle, even with people who are not very close to each other.

[0055] <Example of content distribution processing> The content distribution processing performed in the content distribution system 11 will be explained with reference to Figures 7 to 13.

[0056] Figure 7 is a flowchart illustrating an example of the content distribution process on the in-vehicle system 22 side. For example, the processes in steps S11 to S13 and steps S14 to S16 are performed in parallel.

[0057] In step S11, the data input unit 31 captures the conversation between passenger a and passenger b using a microphone and supplies the audio data of that conversation to the audio common keyword determination unit 52 of the data processing unit 32.

[0058] In step S12, the voice common keyword determination processing unit 52 performs a voice common keyword determination process (see Figure 9, described later) to determine a voice common keyword based on the voice data of the conversation between passenger a and passenger b supplied from the data input unit 31 in step S11.

[0059] In step S13, the voice common keyword determination processing unit 52 sends a list of registered voice common keywords determined in the voice common keyword determination process of step S12 to the cloud system 23.

[0060] In step S14, the data input unit 31 photographs passengers a and b with a camera and supplies the image data obtained from the photography to the general-purpose attribute data generation unit 51 of the data processing unit 32.

[0061] In step S15, the general-purpose attribute data generation unit 51 generates general-purpose attribute data for passengers a and passenger b based on the image data of passengers a and passenger b supplied from the data input unit 31 in step S14.

[0062] In step S16, the general-purpose attribute data generation unit 51 transmits the general-purpose attribute data of passenger a and passenger b generated in step S15 to the cloud system 23.

[0063] After the processing in steps S13 and S16, when the common content is transmitted in the content distribution process on the cloud system 23 side (step S26 in Figure 8), the process proceeds to step S17.

[0064] In step S17, the content playback unit 33 receives and acquires the common content transmitted from the cloud system 23.

[0065] In step S18, the content playback unit 33 plays the common content acquired in step S17, for example, by displaying video on the display device and outputting audio from the audio device, and presenting it to passengers a and b. After that, the content distribution process on the in-vehicle system 22 side is terminated.

[0066] Figure 8 is a flowchart illustrating an example of the content distribution process on the cloud system 23 side.

[0067] In step S21, the personal authentication processing unit 61 performs a personal authentication process (see Figure 10, described later) to obtain the personal attribute data or general attribute data of passenger a and the personal attribute data or general attribute data of passenger b.

[0068] In step S22, the attribute data integration unit 62 integrates the attribute data of passenger a and the attribute data of passenger b obtained in the personal authentication process in step S21 to generate a list in which the attribute data of passenger a and passenger b are registered, and supplies it to the attribute common keyword determination processing unit 63.

[0069] In step S23, the attribute common keyword determination processing unit 63 executes an attribute common keyword determination process (see Figure 11, described later) which determines the attribute common keyword based on the attribute data supplied in step S22.

[0070] In step S24, the common keyword acquisition unit 64 acquires the voice common keyword transmitted from the voice common keyword determination processing unit 52 in step S13 of Figure 7 described above, and supplies it to the content search word generation processing unit 65.

[0071] In step S25, the content search word generation processing unit 65 executes a content search word generation process (see Figure 12 or Figure 13 described later) that generates content search words based on the attribute common keyword provided in the attribute common keyword determination process in step S23 and the voice common keyword provided in step S24.

[0072] In step S26, the common content extraction unit 66 searches the content data storage unit 42 using the content search words supplied in the content search word generation process in step S25. The common content extraction unit 66 then transmits the content data obtained as a search result to the in-vehicle system 22 as common content, and the content distribution process on the cloud system 23 side is then terminated.

[0073] Figure 9 is a flowchart illustrating an example of the voice common keyword determination process performed in step S12 of Figure 7.

[0074] In step S31, the voice common keyword determination processing unit 52 acquires the voice data of the conversation between passenger a and passenger b supplied from the data input unit 31 in step S11 of Figure 7.

[0075] In step S32, the voice common keyword determination processing unit 52 performs voice recognition processing on the voice data acquired in step S31 and extracts keywords from the conversation between passenger a and passenger b.

[0076] In step S33, the voice common keyword determination processing unit 52 determines whether the keyword extracted in step S32 is positive for both passenger a and passenger b.

[0077] In step S33, if the voice common keyword determination processing unit 52 determines that both passenger a and passenger b are positive about the keyword, the process proceeds to step S34.

[0078] In step S34, the voice common keyword determination processing unit 52 determines the keyword that was determined to be positive in step S33 as the voice common keyword.

[0079] In step S35, the voice common keyword determination processing unit 52 adds (registers) the voice common keyword determined in step S34 to the list of voice common keywords, and the process proceeds to step S36.

[0080] On the other hand, in step S33, if the voice common keyword determination processing unit 52 determines that neither passenger a nor passenger b is positive about the keyword (either passenger a or passenger b is negative about the keyword, or neither positive nor negative), the process skips steps S34 and S35 and proceeds to step S36.

[0081] In step S36, the voice common keyword determination processing unit 52 determines whether the conversation between passenger a and passenger b has ended based on the voice data acquired in step S31.

[0082] In step S36, if the voice common keyword determination processing unit 52 determines that the conversation between passenger a and passenger b has not ended, the process returns to step S32, and the same process is repeated thereafter.

[0083] On the other hand, in step S36, if the voice common keyword determination processing unit 52 determines that the conversation between passenger a and passenger b has ended, the voice common keyword determination process is terminated.

[0084] Figure 10 is a flowchart illustrating an example of the personal authentication process performed in step S21 of Figure 8. While this explanation focuses on the personal authentication process for passenger a, the process for passenger b is performed similarly.

[0085] In step S41, the personal authentication processing unit 61 communicates with the personal information terminal 34a regarding the handling of personal attribute data.

[0086] In step S42, the personal authentication processing unit 61 determines whether or not passenger a has authorized the use of personal attribute data, according to the result of the communication in step S41. For example, the personal authentication processing unit 61 can determine that passenger a has authorized the use of personal attribute data only if permission to use the personal attribute data has been notified from the personal information terminal 34a.

[0087] In step S42, if the personal authentication processing unit 61 determines that the use of personal attribute data has been authorized by passenger a, the process proceeds to step S43. In step S43, the personal authentication processing unit 61 obtains passenger a's personal attribute data from the personal attribute data storage unit 41 and supplies it to the attribute data integration unit 62.

[0088] On the other hand, if in step S42 the personal authentication processing unit 61 determines that the use of personal attribute data has not been authorized by passenger a, the process proceeds to step S44. In step S44, the personal authentication processing unit 61 instructs the attribute data integration unit 62 to acquire general attribute data of passenger a, and the attribute data integration unit 62 acquires general attribute data of passenger a from the general attribute data generation unit 51.

[0089] After step S43 or S44, the personal authentication process is terminated.

[0090] Figure 11 is a flowchart illustrating an example of the attribute common keyword determination process performed in step S23 of Figure 8.

[0091] In step S51, the attribute common keyword determination processing unit 63 obtains a list of attribute data supplied from the attribute data integration unit 62 in step S22 of Figure 8.

[0092] In step S52, the attribute common keyword determination processing unit 63 refers to the list of attribute data obtained in step S51 and compares the positive attribute items of passenger a and passenger b (in the example of Figure 4 above, hobbies and favorite vehicles).

[0093] In step S53, the attribute common keyword determination processing unit 63 determines whether there are any keywords common to both passenger a and passenger b among the keywords registered in the attribute items compared in step S52.

[0094] In step S53, if the attribute common keyword determination processing unit 63 determines that there is a keyword common to both passenger a and passenger b, the process proceeds to step S45.

[0095] In step S54, the attribute common keyword determination processing unit 63 determines the keyword that was determined to be positive in step S53 as the attribute common keyword.

[0096] In step S55, the attribute common keyword determination processing unit 63 adds (registers) the attribute common keyword determined in step S54 to the attribute common keyword list, and the process proceeds to step S56.

[0097] On the other hand, if in step S53 the attribute common keyword determination processing unit 63 determines that there are no keywords common to both passenger a and passenger b, the process skips steps S54 and S55 and proceeds to step S56.

[0098] In step S56, the attribute common keyword determination processing unit 63 determines whether all attribute items were compared in step S52 for positive attribute items in the attribute data list.

[0099] In step S56, if the attribute common keyword determination processing unit 63 determines that not all attribute items were compared in step S52, that is, if there are still attribute items that have not been compared, the process returns to step S52, and the same process is repeated thereafter.

[0100] On the other hand, if in step S56 the attribute common keyword determination processing unit 63 determines that all attribute items were used for comparison in step S52, the process proceeds to step S57.

[0101] In step S57, the attribute common keyword determination processing unit 63 supplies a list of attribute common keywords to the content search word generation processing unit 65, and then the attribute common keyword determination process is terminated.

[0102] Figure 12 is a flowchart illustrating a first example of the content search word generation process performed in step S25 of Figure 8.

[0103] In step S61, the content search word generation processing unit 65 obtains the list of common voice keywords transmitted in step S13 in Figure 7, and the list of common attribute keywords supplied in step S57 in Figure 11. The content search word generation processing unit 65 then uses one of the common voice keywords registered in the list of common voice keywords as the comparison target.

[0104] In step S62, the content search word generation processing unit 65 compares the common audio keyword used for comparison in step S61 with the keyword registered in the list of common attribute keywords.

[0105] In step S63, the content search word generation processing unit 65 determines, based on the comparison results from step S62, whether or not a keyword common to the audio common keyword being compared is registered in the attribute common keyword list.

[0106] In step S63, if the content search word generation processing unit 65 determines that a keyword common to the audio common keyword being compared is registered in the attribute common keyword list, the process proceeds to step S64.

[0107] In step S64, the content search word generation processing unit 65 adds (registers) the common audio keyword used for comparison in step S61 to the list of content search words, and the process proceeds to step S65.

[0108] On the other hand, in step S63, if the content search word generation processing unit 65 determines that there are no keywords in common with the audio common keyword being compared that are registered in the attribute common keyword list, the process skips step S64 and proceeds to step S65.

[0109] In step S65, the content search word generation processing unit 65 determines whether or not all of the common voice keywords registered in the list of common voice keywords obtained in step S61 were used as comparison targets.

[0110] In step S65, if the content search word generation processing unit 65 determines that not all audio common keywords have been compared, the process proceeds to step S66. In step S66, the content search word generation processing unit 65 selects the audio common keywords that have not yet been compared as the next comparison target, and the process returns to step S62, and the same process is repeated thereafter.

[0111] On the other hand, if the content search word generation processing unit 65 determines in step S65 that all common audio keywords have been used for comparison, the process proceeds to step S67. In step S67, the content search word generation processing unit 65 supplies the list of content search words obtained by repeating the processes in steps S62 to S66 to the common content extraction unit 66, and then the content search word generation process is terminated.

[0112] Figure 13 is a flowchart illustrating a second example of the content search word generation process performed in step S25 of Figure 8.

[0113] In step S71, the content search word generation processing unit 65 obtains the list of common voice keywords transmitted in step S13 in Figure 7, and the list of attribute data generated by the attribute data integration unit 62 in step S22 in Figure 8. The content search word generation processing unit 65 then selects one common voice keyword registered in the list of common voice keywords as the target for verification.

[0114] In step S72, the content search word generation processing unit 65 checks the list of attribute data obtained in step S71 for the common audio keywords that were the target of confirmation in step S71.

[0115] In step S73, the content search word generation processing unit 65 determines, based on the results of the verification in step S72, whether at least one of the common audio keywords to be verified is negative or not.

[0116] In step S73, if the content search word generation processing unit 65 determines that at least one of the audio common keywords to be checked is not negative (i.e., both are positive, or one is positive and the other is neither positive nor negative), the process proceeds to step S74.

[0117] In step S74, the content search word generation processing unit 65 adds (registers) the common audio keywords that were confirmed in step S71 to the list of content search words, and the process proceeds to step S75.

[0118] On the other hand, if in step S73 the content search word generation processing unit 65 determines that at least one of the audio common keywords to be checked is negative, the process skips step S74 and proceeds to step S75.

[0119] In step S75, the content search word generation processing unit 65 determines whether all of the common voice keywords registered in the list of common voice keywords obtained in step S71 were to be checked.

[0120] In step S75, if the content search word generation processing unit 65 determines that not all audio common keywords have been checked, the process proceeds to step S76. In step S76, the content search word generation processing unit 65 selects the audio common keywords that have not yet been compared as the next check target, and the process returns to step S72, and the same process is repeated thereafter.

[0121] On the other hand, if the content search word generation processing unit 65 determines in step S75 that all common audio keywords have been identified as targets for verification, the process proceeds to step S77. In step S77, the content search word generation processing unit 65 supplies the list of content search words obtained by repeating the processes in steps S72 to S76 to the common content extraction unit 66, and then the content search word generation process is terminated.

[0122] The content distribution process described above is performed in the content distribution system 11, and common content that is presumed to be of interest to both passenger a and passenger b is played, thereby improving the quality of communication within the vehicle.

[0123] <Second Configuration Example of Content Distribution System> A second embodiment of a content distribution system to which this technology is applied will be described with reference to Figures 14 to 16.

[0124] Figure 14 is a block diagram showing a second embodiment of a content distribution system 11 to which this technology is applied. In the content distribution system 11A shown in Figure 14, components common to the content distribution system 11 in Figure 2 are denoted by the same reference numerals, and their detailed descriptions are omitted.

[0125] As shown in Figure 14, the content distribution system 11A is composed of an in-vehicle system 22A and a cloud system 23A.

[0126] The in-vehicle system 22A is configured similarly to the in-vehicle system 22 in Figure 2, in that it includes a content playback unit 33 and personal information terminals 34a and 34b. However, the in-vehicle system 22A differs from the in-vehicle system 22 in that it includes a data input unit 31A and a data processing unit 32A.

[0127] The data input unit 31A, like the data input unit 31 in Figure 2, has cameras for photographing the interior and exterior of the vehicle, and microphones for capturing the conversations of passengers a and b. It also has a camera for photographing the faces of passengers a and b. Of course, the camera for photographing the interior of the vehicle may also function as the camera for photographing the faces of passengers a and b. The data input unit 31A then supplies the image data of the interior and exterior of the vehicle, the audio data of the conversations of passengers a and b, and the image data of the faces of passengers a and b to the data processing unit 32A.

[0128] The data processing unit 32A is configured similarly to the data processing unit 32 in Figure 2, including a general-purpose attribute data generation unit 51 and a voice common keyword determination processing unit 52. Furthermore, it differs from the data processing unit 32 in that it includes a gaze common keyword determination processing unit 53.

[0129] The gaze-gazing common keyword determination processing unit 53 detects the direction of the gazes of passengers a and b by performing image recognition processing on the facial image data of passengers a and b supplied from the data input unit 31. Furthermore, the gaze-gazing common keyword determination processing unit 53 recognizes the scenery in the direction of the gazes of passengers a and b by performing image recognition processing on the external image data of the vehicle supplied from the data input unit 31. The gaze-gazing common keyword determination processing unit 53 then identifies the scenery that both passengers a and b are looking at simultaneously as a gaze-gazing scenery that is positive for both of them, determines the information representing that gaze-gazing scenery as a gaze-gazing common keyword, and transmits it to the cloud system 23.

[0130] For example, the gaze-gazing common keyword determination processing unit 53 can extract information representing the gazed-on scenery (e.g., the names of buildings or shops) by referring to map data according to the vehicle's current location. For example, if passengers a and b are looking at the same shop at the same time, the gaze-gazing common keyword determination processing unit 53 determines the name of that shop as the gaze-gazing common keyword. Alternatively, when AR content is being distributed by the content distribution system 11, if passengers a and b are looking at the same AR character (a character within the AR content) at the same time, the gaze-gazing common keyword determination processing unit 53 determines the name of that AR character as the gaze-gazing common keyword.

[0131] Cloud system 23A is configured similarly to cloud system 23 in Figure 2, in that it includes a personal attribute data storage unit 41 and a content data storage unit 42. However, cloud system 23A is configured differently from cloud system 23 in Figure 2, in that it includes a content distribution processing unit 43A.

[0132] The content distribution processing unit 43A is configured similarly to the content distribution processing unit 43 in Figure 2, and includes a personal authentication processing unit 61, an attribute data integration unit 62, an attribute common keyword determination processing unit 63, and a common content extraction unit 66. Furthermore, the content distribution processing unit 43A is configured to include a common keyword acquisition unit 64A and a content search word generation processing unit 65A.

[0133] The common keyword acquisition unit 64A acquires the voice common keyword transmitted from the voice common keyword determination processing unit 52, and also acquires the gaze common keyword transmitted from the gaze common keyword determination processing unit 53. The common keyword acquisition unit 64A then supplies the voice common keyword and the gaze common keyword to the content search word generation processing unit 65A.

[0134] The content search word generation processing unit 65A compares the attribute common keyword supplied from the attribute common keyword determination processing unit 63 with the voice common keyword and gaze common keyword supplied from the common keyword acquisition unit 64, generates content search words according to the comparison result, and supplies them to the common content extraction unit 66.

[0135] The content distribution system 11A configured as described above can estimate common content that is of greater interest to both passenger a and passenger b by utilizing not only common voice keywords extracted from the conversation between passenger a and passenger b, but also common gaze keywords extracted from the gaze of passenger a and passenger b.

[0136] Figure 15 is a flowchart illustrating an example of the content distribution process on the in-vehicle system 22A side. Steps S11 to S18 are performed in the same manner as in Figure 7, and steps S81 to S83 are performed in parallel with steps S11 to S13 and steps S14 to S16.

[0137] In step S81, the data input unit 31A captures the faces of passengers a and b with a camera, as well as the scenery, and supplies the image data obtained from the capture to the gaze common keyword determination unit 53 of the data processing unit 32A.

[0138] In step S82, the gaze-common keyword determination processing unit 53 performs a gaze-common keyword determination process (see Figure 16, described later) to determine a gaze-common keyword based on the face and scenery image data of passengers a and b supplied from the data input unit 31 in step S81.

[0139] In step S83, the eye-gaze common keyword determination processing unit 53 sends a list of eye-gaze common keywords determined in the eye-gaze common keyword determination process of step S82 to the cloud system 23.

[0140] Figure 16 is a flowchart illustrating the process of determining the common gaze keyword in step S82 of Figure 15.

[0141] In step S91, the gaze common keyword determination processing unit 53 acquires image data of the faces of passengers a and b, as well as image data of the scenery, which are supplied from the data input unit 31 in step S81 of Figure 15.

[0142] In step S92, the gaze common keyword determination processing unit 53 performs image recognition processing on the facial image data of passenger a and passenger b acquired in step S91 to detect the direction of the gaze of passenger a and passenger b.

[0143] In step S93, the gaze-common keyword determination processing unit 53 performs image recognition processing on the landscape image data acquired in step S91, and identifies the landscape that both passenger a and passenger b are looking at simultaneously as the gaze-focused landscape, according to the gaze detected in step S92.

[0144] In step S94, the gaze-common keyword determination processing unit 53 determines the names of objects included in the gaze-focused scenery as gaze-common keywords and transmits them to the cloud system 23.

[0145] By performing the content distribution process described above in the content distribution system 11A, it is possible to improve the quality of communication within the vehicle, similar to the content distribution system 11 described above.

[0146] <Example of Computer Configuration> Next, the series of processes (information processing methods) described above can be performed by hardware or by software. When the series of processes are performed by software, the programs that make up that software are installed on a general-purpose computer or the like.

[0147] Figure 17 is a block diagram showing an example configuration of one embodiment of a computer on which the program that performs the series of processes described above is installed.

[0148] The program can be pre-recorded on the hard disk 105 or ROM 103, which are recording media built into the computer.

[0149] Alternatively, the program can be stored (recorded) on a removable recording medium 111 driven by the drive 109. Such a removable recording medium 111 can be provided as so-called packaged software. Examples of removable recording media 111 include flexible disks, CD-ROMs (Compact Disc Read Only Memory), MO (Magneto Optical) disks, DVDs (Digital Versatile Discs), magnetic disks, semiconductor memory, etc.

[0150] In addition to installing the program from the removable storage medium 111 as described above, the program can also be downloaded to the computer via a communication network or broadcasting network and installed on the built-in hard disk 105. That is, the program can be transferred wirelessly to the computer from a download site via a satellite for digital satellite broadcasting, or transferred via a wired connection to the computer via a network such as a LAN (Local Area Network) or the Internet.

[0151] The computer has a built-in CPU (Central Processing Unit) 102, and an input / output interface 110 is connected to the CPU 102 via a bus 101.

[0152] When the CPU 102 receives a command from the user via the input / output interface 110, such as by operating the input unit 107, it executes a program stored in the ROM (Read Only Memory) 103 accordingly. Alternatively, the CPU 102 loads a program stored in the hard disk 105 into the RAM (Random Access Memory) 104 and executes it.

[0153] As a result, the CPU 102 performs processing according to the flowchart described above, or processing according to the configuration of the block diagram described above. The CPU 102 then outputs the processing results as needed, for example, via the input / output interface 110 from the output unit 106, transmits them from the communication unit 108, or records them on the hard disk 105.

[0154] The input unit 107 consists of a keyboard, mouse, microphone, etc. The output unit 106 consists of an LCD (Liquid Crystal Display), speaker, etc.

[0155] In this specification, the processes performed by a computer according to a program do not necessarily have to be performed chronologically in the order described in the flowchart. That is, the processes performed by a computer according to a program include processes that are executed in parallel or individually (e.g., parallel processing or object-based processing).

[0156] Furthermore, the program may be processed by a single computer (processor), or it may be processed in a distributed manner by multiple computers. Moreover, the program may be transferred to a remote computer for execution.

[0157] Furthermore, in this specification, a system means a collection of multiple components (devices, modules (parts), etc.), regardless of whether all components are located in the same enclosure or not. Therefore, multiple devices housed in separate enclosures and connected via a network, and a single device in which multiple modules are housed in one enclosure, are both considered systems.

[0158] Furthermore, for example, the configuration described as a single device (or processing unit) may be divided and configured as multiple devices (or processing units). Conversely, the configurations described above as multiple devices (or processing units) may be combined and configured as a single device (or processing unit). It is also possible to add configurations other than those described above to the configuration of each device (or each processing unit). Moreover, if the overall system configuration and operation are substantially the same, a part of the configuration of one device (or processing unit) may be included in the configuration of another device (or other processing unit).

[0159] Furthermore, for example, this technology can be configured as cloud computing, where a single function is shared and processed collaboratively by multiple devices via a network.

[0160] Furthermore, for example, the program described above can be executed on any device. In that case, the device should have the necessary functions (such as functional blocks) and be able to obtain the necessary information.

[0161] Furthermore, each step described in the flowchart above can be executed by a single device or shared among multiple devices. Additionally, if a single step includes multiple processes, these processes can be executed by a single device or shared among multiple devices. In other words, multiple processes within a single step can be executed as multiple steps. Conversely, processes described as multiple steps can be combined and executed as a single step.

[0162] Furthermore, the program executed by the computer may be executed in a chronological order according to the sequence of steps described herein, or it may be executed in parallel or individually at necessary times, such as when a call is made. In other words, as long as no inconsistencies arise, the processing of each step may be executed in an order different from the sequence described above. Moreover, the processing of the steps of this program may be executed in parallel with the processing of other programs, or it may be executed in combination with the processing of other programs.

[0163] Furthermore, the technologies described in this specification can be implemented independently, as long as they do not create a contradiction. Of course, any multiple technologies can also be implemented in combination. For example, some or all of the technologies described in one embodiment can be combined with some or all of the technologies described in another embodiment. In addition, some or all of the above-mentioned technologies can be implemented in combination with other technologies not mentioned above.

[0164] <Examples of Configuration Combinations> The technology can also take the following configurations: (1) An information processing device comprising: a common keyword determination unit that determines common keywords that indicate matters of common interest to multiple passengers in a vehicle and transmits the common keywords to a cloud system; and a content playback unit that receives and plays common content, which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers. (2) The information processing device according to (1) above, wherein the common keyword determination unit performs speech recognition processing on audio data of conversations between the multiple passengers and determines, among the keywords extracted from the conversations between the multiple passengers, a keyword that is positive for all passengers as a common speech keyword. (3) The information processing device according to (1) or (2) above, wherein the common keyword determination unit performs image recognition processing on image data of the faces of the multiple passengers, detects the direction of the gaze of the multiple passengers, identifies a landscape that all passengers are looking at simultaneously as a gaze landscape, and determines information representing that gaze landscape as a common gaze keyword. (4) An information processing device according to any one of (1) to (3) above, further comprising a general-purpose attribute data generation unit that generates general-purpose attribute data of multiple passengers by applying image recognition processing to image data inside the vehicle and transmits it to the cloud system. (5) An information processing device according to any one of (1) to (4) above, further comprising a personal information terminal owned by each of the multiple passengers, wherein the personal information terminal notifies the cloud system of permission to use the personal attribute data on the cloud system if the use of such personal attribute data is permitted by each of the passengers. (6) An information processing method comprising: determining a common keyword that indicates a common interest for multiple passengers inside the vehicle and transmitting the common keyword to the cloud system; and receiving and playing common content which is content distributed from the cloud system based on the common keyword and the attribute data of the multiple passengers.(7) A program that causes the computer of the information processing device to perform information processing including determining common keywords that indicate matters of common interest to multiple passengers in a vehicle and transmitting the common keywords to a cloud system, and receiving and playing common content which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers. (8) An information processing device comprising a content search word generation processing unit that generates content search words based on common keywords that indicate matters of common interest to multiple passengers in a vehicle transmitted from an in-vehicle system and attribute data of the multiple passengers, and a common content extraction unit that searches a content data storage unit using the content search words and distributes the content data obtained as a search result to the in-vehicle system as common content. (9) The information processing device according to (8) above, wherein speech recognition processing is performed on audio data of conversations of multiple passengers, and keywords that are positive for all passengers among the keywords extracted from the conversations of the multiple passengers are transmitted from the in-vehicle system as common speech keywords. (10) An information processing device according to (8) or (9) above, wherein image recognition processing is applied to image data of the faces of multiple passengers, the direction of the gaze of the multiple passengers is detected, the scenery that all passengers are looking at simultaneously is identified as the gaze scenery, and information representing the gaze scenery is transmitted from the in-vehicle system as a common gaze keyword. (11) An information processing device according to any one of (8) to (10) above, further comprising an attribute common keyword determination processing unit that determines a keyword that is commonly registered for all passengers in a positive attribute item in a list of attribute data of multiple passengers as an attribute common keyword and supplies it to the content search word generation processing unit. (12) An information processing device according to (11) above, wherein the content search word generation processing unit compares the common keyword and the attribute common keyword, and generates the keyword included in both as the content search word according to the comparison result.(13) The information processing device according to (11) above, wherein the content search word generation processing device generates a content search word from among the common keywords, which is not rejected by any of the multiple passengers in the attribute data. (14) The information processing device according to any one of (8) to (13) above, further comprising a personal authentication processing device that communicates with a personal information terminal owned by each of the multiple passengers regarding the handling of personal attribute data on the network and determines whether the use of the personal attribute data is permitted by each of the passengers, wherein the personal authentication processing device acquires the personal attribute data on the network when permission to use the personal attribute data is notified from the personal information terminal, and instructs the acquisition of the passenger's general attribute data generated in the in-vehicle system when permission to use the personal attribute data is not notified from the personal information terminal. (15) An information processing method comprising: generating content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers; searching a content data storage unit using the content search words; and distributing the content data obtained as a search result to the in-vehicle system as common content. (16) A program for causing the computer of the information processing device to execute information processing comprising: generating content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers; searching a content data storage unit using the content search words; and distributing the content data obtained as a search result to the in-vehicle system as common content.(17) An information processing system comprising: a first information processing device having a common keyword determination unit that determines common keywords that indicate matters of common interest to multiple passengers in a vehicle and transmits the common keywords to a cloud system; a content playback unit that receives and plays common content which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers; a content search word generation processing unit that generates content search words based on common keywords that indicate matters of common interest to multiple passengers in a vehicle and attribute data of the multiple passengers transmitted from an in-vehicle system; and a second information processing device having a common content extraction unit that searches a content data storage unit using the content search words and distributes the content data obtained as a search result to the in-vehicle system as common content.

[0165] It should be noted that this embodiment is not limited to the embodiment described above, and various modifications are possible without departing from the spirit of this disclosure. Furthermore, the effects described herein are merely illustrative and not limiting, and other effects may also exist.

[0166] 11 Content distribution system, 21 Network, 22 In-vehicle system, 23 Cloud system, 31 Data input unit, 32 Data processing unit, 33 Content playback unit, 34 Personal information terminal, 41 Personal attribute data storage unit, 42 Content data storage unit, 43 Content distribution processing unit, 51 General-purpose attribute data generation unit, 52 Voice common keyword determination processing unit, 53 Eye gaze common keyword determination processing unit, 61 Personal authentication processing unit, 62 Attribute data integration unit, 63 Attribute common keyword determination processing unit, 64 Common keyword acquisition unit, 65 Content search word generation processing unit, 66 Common content extraction unit

Claims

1. An information processing device comprising: a common keyword determination unit that determines common keywords that indicate common interests for multiple passengers in a vehicle and transmits the common keywords to a cloud system; and a content playback unit that receives and plays common content, which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers.

2. The information processing apparatus according to claim 1, wherein the common keyword determination unit performs speech recognition processing on the audio data of the conversations of the multiple passengers, and determines a keyword that is positive for all of the passengers from among the keywords extracted from the conversations of the multiple passengers as a common audio keyword.

3. The information processing apparatus according to claim 1, wherein the common keyword determination unit performs image recognition processing on image data of the faces of multiple passengers, detects the direction of the gaze of multiple passengers, identifies the scenery that all passengers are looking at simultaneously as the gaze scenery, and determines information representing that gaze scenery as a common gaze keyword.

4. The information processing apparatus according to claim 1, further comprising a general-purpose attribute data generation unit that generates general-purpose attribute data of multiple passengers by applying image recognition processing to image data inside the vehicle and transmits it to the cloud system.

5. The information processing device according to claim 1, further comprising a personal information terminal owned by each of the multiple passengers, wherein the personal information terminal notifies the cloud system of permission to use personal attribute data on the cloud system if the use of such personal attribute data is permitted by each of the passengers.

6. An information processing method comprising: an information processing device determining common keywords that indicate common interests for multiple passengers in a vehicle, transmitting the common keywords to a cloud system, and receiving and playing common content, which is content distributed from the cloud system based on the common keywords and attribute data of the multiple passengers.

7. An information processing device comprising: a content search word generation processing unit that generates content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers; and a common content extraction unit that searches a content data storage unit using the content search words and distributes the content data obtained as a search result to the in-vehicle system as common content.

8. The information processing device according to claim 7, wherein speech recognition processing is performed on the audio data of conversations of multiple passengers, and keywords extracted from the conversations of multiple passengers that are positive for all passengers are transmitted from the in-vehicle system as common speech keywords.

9. The information processing device according to claim 7, wherein image recognition processing is performed on image data of the faces of multiple passengers, the direction of the gaze of the multiple passengers is detected, the scenery that all passengers are looking at simultaneously is identified as the gaze scenery, and information representing the gaze scenery is transmitted from the in-vehicle system as a common gaze keyword.

10. The information processing apparatus according to claim 7, further comprising an attribute common keyword determination processing unit that determines, as an attribute common keyword, a keyword that is commonly registered for all passengers in a positive attribute item in a list of attribute data of multiple passengers, and supplies it to the content search word generation processing unit.

11. The information processing device according to claim 10, wherein the content search word generation processing unit compares the common keyword and the attribute common keyword, and generates keywords contained in both as the content search word according to the comparison result.

12. The information processing device according to claim 10, wherein the content search word generation processing unit generates a content search word from among the common keywords, which is not rejected by any of the multiple passengers in the attribute data.

13. The information processing device according to claim 7, further comprising a personal authentication processing unit that communicates with personal information terminals owned by each of the multiple passengers regarding the handling of personal attribute data on the network and determines whether the use of the personal attribute data is authorized by each of the passengers, wherein the personal authentication processing unit acquires the personal attribute data on the network when permission to use the personal attribute data is notified from the personal information terminal, and instructs the acquisition of general attribute data of the passenger generated in the in-vehicle system when permission to use the personal attribute data is not notified from the personal information terminal.

14. An information processing method comprising: generating content search words based on common keywords indicating common interests for multiple passengers in a vehicle transmitted from an in-vehicle system, and attribute data of multiple said passengers; and searching a content data storage unit using the content search words and distributing the content data obtained as a search result to the in-vehicle system as common content.

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