Enrichment process, electronic device and corresponding computer program product

Abstract

Method for enriching at least one audiovisual element, electronic device and corresponding computer program product. This application relates to a method for enriching an audiovisual element rendered on a first output user interface of an electronic device, the method being implemented by the electronic device and comprising, during a current rendering of the audiovisual element: A conditional proposal for rendering, on at least a second output interface of said electronic device, of an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory capacity of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory capacity taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering.said audiovisual element and / or said audiovisual sequence, on at least one output interface of said electronic device. Figure for the abbreviation: Fig. 3,

Description

Title of the invention: Enrichment process, electronic device and corresponding computer program product 1. technical field

[0001] The present application relates to the field of enriching audiovisual, textual, vocal and / or image elements rendered on at least one output interface of at least one electronic device. It concerns in particular a method for at least partially automatic enrichment (or annotation) of such elements, as well as a corresponding electronic device, computer program product and medium. 2. State of the art

[0002] With the rise of digital usage, a user of an electronic device consumes a great deal of audiovisual content. This content may contain audiovisual elements that the user is unfamiliar with or has forgotten. The user may then have to conduct their own research to understand the meaning of this element or, more generally, to acquire a greater understanding of it. They may therefore waste time on these searches, or even fail to find the desired information.

[0003] As a result, some solutions enrich certain content elements, which they believe may be unknown to at least some users, with additional information, enabling a user to better understand these content elements.

[0004] However, this enrichment may not be suitable for all users. For example, the enriched content elements may not be those for which the user in question would want additional information. Furthermore, an abundance of additional information may disrupt the user's reading experience.

[0005] Also, there is a need for an enrichment process better suited to the needs of a user.

[0006] The purpose of this application is to propose improvements to at least some of the drawbacks of the prior art. 3. Description of the invention

[0007] The present application aims to improve the situation by means of a method for enriching at least one audiovisual element rendered on at least one first output user interface of an electronic device, said method being implemented by said electronic device and comprising, during a normal rendering of said audiovisual element: - A conditional proposal for rendering, on at least one second output interface of said electronic device, of an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

[0008] By rendering, we mean here a display (or "output" according to English terminology) on at least one user interface, in any form whatsoever, for example including textual, audio and / or video components, or a combination of such components.

[0009] According to at least one embodiment, said conditional proposal further takes into account at least one coefficient of ease of learning said user for said audiovisual element.

[0010] According to at least one embodiment, said user learning ease coefficient for said audiovisual element takes into account a memory capacity of said user.

[0011] According to at least one embodiment, said user's memory capacity takes into account a plurality of renderings of audiovisual elements for said user.

[0012] According to at least one embodiment, said method includes, during said current rendering, a calculation of a current knowledge rate by the user of said audiovisual sequence associated with said audiovisual element, taking into account said memory strength, a time elapsed since at least one rendering event of said history, preceding said current rendering and / or said learning ease coefficient and said rendering proposal is implemented according to said calculated current knowledge rate.

[0013] According to at least one embodiment, said current knowledge rate also takes into account a knowledge rate calculated previously for said previous rendering of said history.

[0014] According to at least one embodiment, said process comprises:

[0015] - an update, following the current audit report, of said knowledge rate, of said memory strength and / or said learning ease coefficient,

[0016] - a storage of at least one rendering event representative of said current rendering in the aforementioned history, and

[0017] - a storage, in association with said history, of said knowledge rate updated, of the said updated memory strength and / or the ease coefficient updated learning.

[0018] According to at least one embodiment, a rendering event of said rendering history: A category of said rendering event; A timestamp of the rendering of the audiovisual element to which said rendering event relates and / or of said associated audiovisual sequence

[0019] According to at least one embodiment, the calculation of said knowledge rate also takes into account a number of successive renderings of said audiovisual element without rendering of said audiovisual sequence.

[0020] According to at least one embodiment, the process includes, during said current rendering, an acquisition of an acceptance and / or a refusal of said rendering proposal.

[0021] The features, presented individually in this application in connection with certain embodiments of the process of this application, can be combined with each other according to other embodiments of this process.

[0022] According to another aspect, the present application also relates to an electronic device adapted to implement the process of the present application in any of its embodiments.

[0023] For example, the present application relates to an electronic device comprising at least one processor configured for: enhancing at least one audiovisual element rendered on at least one first output user interface of an electronic device, said at least one processor being configured for: A conditional proposal, during a current rendering of said audiovisual element, to render, on at least one second output interface of said electronic device, an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

[0024] The present application also relates to a computer program comprising instructions for implementing the various embodiments of the above process, where the computer program is executed by a processor and a recording medium readable by an electronic device and on which such a computer program is recorded.

[0025] For example, the present application thus relates to a computer program including instructions for the implementation, when the computer program is executed by a processor of an electronic device, of a method for enriching at least one audiovisual element rendered on at least one first output user interface of an electronic device, said method being implemented by said electronic device and comprising, during a normal rendering of said audiovisual element: - A conditional proposal for rendering, on at least one second output interface of said electronic device, of an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

[0026] For example, the present application also relates to a recording medium readable by a processor of an electronic device and on which is recorded a computer program comprising instructions for the implementation, when the computer program is executed by the processor, of a method for enhancing at least one audiovisual element rendered on at least one first output user interface of an electronic device, said method being implemented by said electronic device and comprising, during a normal rendering of said audiovisual element: - A conditional proposal for rendering, on at least one second output interface of said electronic device, of an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

[0027] The programs mentioned above may use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0028] The information storage media mentioned above can be any entity or device capable of storing the program. For example, a storage medium may include a storage medium, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a magnetic recording medium.

[0029] Such a means of storage can, for example, be a hard drive, a flash memory, etc.

[0030] On the other hand, an information medium can be a transmissible medium such as an electrical or optical signal, which can be transmitted via an electrical or optical cable, by radio, or by other means. A program according to the invention can, in particular, be downloaded onto an Internet-type network.

[0031] Alternatively, an information carrier may be an integrated circuit in which a program is incorporated, the circuit being adapted to execute any one of the embodiments of the method that is the subject of this patent application, or to be used in that execution.

[0032] In this application, an audiovisual element may relate in particular, but not exclusively, to names of technologies, concepts, places, people, etc., or any other information (also called "knowledge" or "skill") that may be useful to the user.

[0033] The term “terminal” includes, but is not limited to, an electronic device such as a personal computer (desktop or laptop), a digital tablet, a personal digital assistant, a smartphone, a workstation, etc., or any other device that a user can use to receive, send or search for audiovisual streams.

[0034] By "audiovisual stream", we mean a stream having at least one audio component and / or at least one visual component (text or images in particular), such as an email, a message (instant or not), a document, a web page, a result of a web query, a social network news feed, content published on a social network, etc.

[0035] Generally speaking, in the present application, obtaining an element means, for example, receiving that element from a communication network, and / or acquiring that element (via, for example, user interface (or human-machine interface) elements or sensors), and / or creating that element by various processing means such as copying, encoding, decoding, transformation, etc., and / or accessing that element from a local or remote (possibly removable) storage medium accessible to at least one electronic device implementing, at least partially, that obtaining. 4. Brief description of the drawings

[0036] Other features and advantages of the invention will become more apparent upon reading the following description of particular embodiments, given by way of simple illustrative and non-limiting examples, and the accompanying drawings, among which:

[0037] Figure 1 presents a simplified view of a system, cited by way of example, in which at least some embodiments of the method of the present application can be implemented.

[0038] Figure 2 presents a simplified view of a device adapted to implement at least certain embodiments of the process of the present application.

[0039] Figure 3 presents an overview of the enrichment process of the present application, in at least some of its embodiments. 5. Description of the implementation methods

[0040] The present application aims, in its first aspect, to conditionally provide supplementary information (for example, contextual help such as a definition) relating to at least one audiovisual element when that audiovisual element is rendered on at least one output interface of a device. This involves providing such supplementary information, or offering a rendering of such supplementary information, with the provision and / or rendering of this supplementary information being personalized for a user of the device. This conditional provision and / or rendering may, in particular, take into account the user's prior knowledge of the rendered audiovisual element.

[0041] Depending on the embodiment, the proposal and / or rendering of this additional information can be carried out via the same output interface as that(s) used for rendering the audiovisual element, or on at least one other output interface than that(s) used for rendering the audiovisual element).

[0042] However, it is difficult to assess an individual's knowledge of a concept (represented here by the supplementary information associated with the rendered audiovisual element). This is all the more difficult in situations where this assessment must be at least partially automated. Therefore, this application proposes to personalize the enrichment (i.e., the suggested rendering and / or the rendering of the supplementary information) by dynamically calculating the user's memory strength with respect to the supplementary information (for example, a definition) associated with the audiovisual element. This dynamic calculation may, in particular, take into account at least part of a rendering history of this audiovisual element and / or the associated supplementary information on at least one of the user's devices in order to try to assess the relevance, for that user, of the rendering of supplementary information for this audiovisual element.Indeed, this additional information may, for example, be relevant to one user but not to another user.

[0043] According to this application, the supplementary information may include at least one audiovisual sequence. Depending on the embodiment, this may be a sequence of the same nature as the audiovisual element provided (such as a sequence textual for a textual element, a voice sequence for a voice element, an image sequence for an image element), or of a different nature (such as a voice sequence for a textual or image element, a textual sequence for a voice or image element, an image sequence for a textual or voice element).

[0044] This audiovisual sequence may, for example, be accessible to the device in a local or remote data structure (stored, for example, on the server 160 or the storage device 150 of [Fig. 1] discussed below), such as at least one file or a database. The structure (or database, for simplicity) may vary depending on the embodiment. For example, in some embodiments, it may be a glossary or dictionary associating each audiovisual element of the glossary (or entry) with at least one audiovisual sequence representing a definition or explanation relating to that audiovisual element in at least one language.

[0045] The rendering event history can be stored in association with the audiovisual element to which it relates. Depending on the embodiment, it can be stored in the same data structure as the audiovisual sequence associated with the audiovisual element or in a different data structure, for example a data structure independent of the data structure of the audiovisual sequences.

[0046] Using different data structures for rendering history and for sequences can, in certain embodiments, facilitate updates to the structure storing the audiovisual sequences (i.e., the "glossary"), to add new entries, or to update the information associated with certain entries. For example, the data structure storing the audiovisual sequences can be stored on a server, or on a local device (such as a gateway) shared by several users and can be downloaded periodically or during at least one maintenance operation. The data structure relating to the rendering event history can be stored locally on the device due to the more personal, private nature of the (user-specific) data it contains.

[0047] Using the same data structure can help simplify the implementation of the process and limit the memory cost associated with its implementation.

[0048] In certain embodiments, and particularly in the embodiments detailed below in relation to [Fig. 3], an audiovisual element may, for example, be a textual element (also sometimes called a "named entity") having a meaning for a glossary or dictionary. For example, "carbon footprint" or "corporate social responsibility" are named entities, just as "environment" is for a data source such as "Wikipedia" ©.

[0049] In at least some embodiments, to assess the knowledge that a For users of the audiovisual sequence associated with an audiovisual element rendered on a device, this application may include a calculation of a knowledge rate (for example, a real number between 0 and 1). This knowledge rate may, in particular, take into account, for example, the time elapsed since a previous rendering of the audiovisual sequence, in association with the audiovisual element, for that user. This knowledge rate may also take into account the user's memory strength regarding that audiovisual element.

[0050] The knowledge rate represents the probability that the user, at a current time of rendering of the rendered audiovisual element, is aware of the additional information associated with the rendered audiovisual element.

[0051] It is a function in particular of the user's memory strength, at that moment, with respect to the rendered audiovisual element (for example the memory strength from the history and not yet recalculated following the current rendering).

[0052] Memory strength represents the variation in the rate of knowledge of supplementary information during the time elapsed since the previous rendering of the currently rendered audiovisual element and / or of the supplementary information associated with that element.

[0053] In at least some embodiments of this application, a knowledge rate can be calculated based on the recall following the last rendering of the audiovisual sequence, and the time elapsed since the last rendering of the element and / or the audiovisual sequence. For example, the knowledge rate can be obtained, at the time of rendering, using the following formula, based on the forgetting curve defined by Hermann Ebbinghaus, to express the knowledge rate (or "retention percentage") of the supplementary information associated with an audiovisual element rendered at the time of that rendering.

[0054] kr = e^

[0055] Where

[0056] kr represents (as a percentage) the user's level of knowledge of the additional information associated with the rendered audiovisual element;

[0057] t (expressed in days) represents the time elapsed since the last rendering of the additional information, in association with the audiovisual element (or an indication provided by the user indicating (explicitly, for example) his knowledge of this association.

[0058] ms (as a percentage) represents the user's memory strength relative to the additional information.

[0059] As can be seen in the formula above, memory strength influences the steepness of the slope of the forgetting curve. The greater the memory strength, the more The user will remember the information for a long time.

[0060] This application proposes to vary the user's memory strength with respect to the audiovisual element to take into account the user's interactions with the audiovisual element during previous renderings of the audiovisual element (related to that user or their device). For example, in certain embodiments, during a current rendering of the audiovisual element, the memory strength (which will be taken into account for the next rendering) can be increased if the user declares knowing the information associated with the audiovisual element or if it is presented to them, and conversely, decreased when the user does not know the audiovisual sequence associated with the audiovisual element. Thus, events relating to successive renderings of the audiovisual element (and possibly the associated audiovisual sequence) can influence the level of knowledge via memory strength.

[0061] More specifically, the present application proposes to fluctuate the memory strength according to the occurrence of the rendering of audiovisual elements, and possibly the rendering of the associated audiovisual sequence, as well as the possible response of the user with respect to a proposed rendering of the sequence.

[0062] In certain embodiments, the method may further include weighting a user's memory strength for an audiovisual element. For example, in certain embodiments, the weighting may take into account the complexity of the audiovisual sequence or a context of said user (such as fatigue, for example).

[0063] In certain embodiments, the fluctuation may take into account a learning ease coefficient (also called the "ease factor" hereafter, according to English terminology), measuring the ease with which the user concerned can memorize the audiovisual sequence. When we encounter an audiovisual element, we do not always manage to remember its definition, even if we have already been aware of it. However, the effort made to try to remember it will facilitate the memorization of this definition if it is presented to us again. Thus, after a first rendering (i.e., initial rendering) of the supplementary information associated with this audiovisual element and then a second rendering of the audiovisual element and / or the associated audiovisual sequence, the audiovisual sequence may be easier to memorize following the second rendering than during the first rendering, even if the audiovisual sequence itself is not rendered.We will undoubtedly pay closer attention to this definition when we recall it.

[0064] The learning ease coefficient reflects this increase in memory strength following the existence of previous rendering(s) of the audiovisual element and / or the associated audiovisual sequence (as defined). It may, for example, be a multiplicative coefficient strictly greater than 1, applied to memory strength. as a multiplicative coefficient belonging to the range of values ​​[1.1; 2.5]. Of course, this range of values ​​can vary depending on the implementation. Increasing the range of values ​​improves the accuracy of the learning ease coefficient and therefore the strength of memory.

[0065] Reducing the range of values ​​can help, in some embodiments, to limit the coding cost of the learning ease coefficient, as well as the resulting memory strength.

[0066] The operation (multiplication, addition etc.) carried out via the coefficient to increase memory strength can vary according to the embodiments.

[0067] Each encounter of the user with the audiovisual element and / or the associated audiovisual sequence increases his ease of learning with respect to the audiovisual sequence associated with the audiovisual element; As a result, according to at least some embodiments, the coefficient of ease of learning will increase progressively during the user's encounters with the audiovisual element (and consequently, through the coefficient of ease of learning, his memorization strength with respect to the audiovisual sequence).

[0068] Depending on the embodiment, different variations of the learning coefficient can be envisaged. Thus, in some embodiments, it may be a linear variation. For example, it may be multiplied by 2 with each rendering of the audiovisual element, being capped at least in some embodiments at a maximum value (such as the upper value of its range, like 2.5 in the example above). In other embodiments, the variation may not be linear.For example, in some embodiments, such as those detailed later, the ease of learning coefficient may increase slowly during the user's first encounters with the audiovisual element (for example, during the first n encounters of the user with the audiovisual element, (with n an integer equal to 3 or 5 for example) and / or with the associated sequence) and then more rapidly afterwards (with a possible ceiling).

[0069] The inventors noted that the more frequently an audiovisual element is encountered, the more its definition enters the user's (or even their interlocutors') "habitual" language, which helps it to be remembered for longer. Thus, in certain embodiments, the learning coefficient can vary more significantly when the audiovisual element is rendered successively without rendering the associated sequence.

[0070] In certain embodiments (as in example 2 below), the knowledge rate can also be impacted on the one hand by the learning ease coefficient, and on the other hand by the number of successive renderings of the audiovisual element, without the associated sequence being rendered (thus, the more the audiovisual element is rendered, the easier it will be for the user to remember it).

[0071] Thus, in certain embodiments, the knowledge rate can be increased (addition) by a value taking into account both the learning coefficient and the number of successive renderings of the audiovisual element without rendering of the associated sequence.

[0072] In some embodiments, the method may include managing an indicator measuring the number of times the audiovisual sequence associated with the audiovisual element has been rendered before that sequence is considered to be known (in association with that audiovisual element) by the user.

[0073] This indicator increases each time the audiovisual sequence is rendered, at the user's request, following a suggestion to render it during the rendering of the audiovisual element, until the first explicit declaration by the user indicating that they know (i.e., remember) the audiovisual sequence (the "I know" event hereafter). The value of this indicator following this first explicit declaration is hereafter referred to as the "final value" of the indicator. The average of the final values ​​of this indicator, for all the audiovisual elements concerned, is referred to in the remainder of this application as the user's "memory capacity" (also called "Memory Capacity" in English terminology).

[0074] In some embodiments, the calculation of memory strength and / or knowledge rate, during rendering, may take into account (via the learning ease coefficient for example) the user's memory capacity.

[0075] The present application is now described in more detail in relation to [Fig.1].

[0076] Figure 1 represents a telecommunications system 100 in which certain embodiments of the invention can be implemented. The system 100 comprises one or more electronic devices, at least some of which can communicate with each other via one or more communication networks, possibly interconnected, such as a local area network (LAN) and / or a wide area network (WAN). For example, the network may include a corporate or home LAN and / or a WAN of the internet, cellular, GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), Wi-Fi (Wireless), etc. type.

[0077] As illustrated in [Fig. 1], the system 100 may also include several electronic devices, such as a terminal (like a laptop 110, a smartphone 120, a tablet 130), an additional output interface 140, and / or a server 160, for example an application server, a storage device 150. The system may also include network management and / or interconnection elements (not shown). These electronic devices may be associated with at least one user 132 (for example, via a user account accessible by login), some of the electronic devices 110, 120, 130 can be associated with the same user 132. Some of these devices 110, 140 can be coupled together.

[0078] Figure 2 illustrates a simplified structure of an electronic device 200 of the system 100, for example device 100, 120, 130 of [Fig. 1], adapted to implement the principles of this application. Depending on the embodiment, this may be a server and / or a terminal.

[0079] The device 200 includes, in particular, at least one memory M 210. The device 200 may, in particular, include a buffer memory, volatile memory, for example of the RAM type (for "Random Access Memory" according to English terminology), and / or non-volatile memory (for example of the ROM type (for "Read Only Memory" according to English terminology). The device 200 may also include a processing unit UT 220, equipped, for example, with at least one processor P 222, and driven by a computer program PG 212 stored in memory M 210. At initialization, the code instructions of the computer program PG are, for example, loaded into RAM before being executed by the processor P. Said at least one processor P 222 of the processing unit UT 220 may, in particular, implement, individually or collectively, any one of the embodiments of the method of the present application (described in particular in relation to [Fig.3]), according to the instructions of the PG computer program. .

[0080] The device 200 may also include, or be coupled to, at least one input / output module LO 230, such as a communication module, enabling, for example, the device 200 to communicate with other devices of the system 100, via wired or wireless communication interfaces, and / or such as an interface module with a user of the device (also referred to more simply in this application as a "user interface" or "human-machine interface").

[0081] By user interface (or “human-machine interface”) of the device, we mean, for example, an interface integrated into the device 200, or part of a third-party device coupled to that device by wired or wireless communication means (such as the device 140 in [Fig. 1]). For example, it could be a secondary display of the device or a set of speakers connected wirelessly to the device.

[0082] A user interface may, in particular, be an "output" user interface adapted for rendering (or controlling the rendering) of an output element of a computer application used by the device 200, for example, an application running at least partially on the device 200 or an "online" application running at least partially remotely, for example on the server 160 of the system 100, or an application accessible via the device 200. Examples The device's output user interface includes one or more screens, including at least one graphic display (e.g., touchscreen), one or more speakers, and a connected headset.

[0083] Furthermore, a user interface can be a user interface, called "Input", adapted to the acquisition of information provided by a user of device 200. This may include information related to a rendered item (for example, an indication of knowledge (event "IKnow") or non-knowledge (event "IdontKnow") by the user of a rendered audiovisual element, or a request for rendering (on proposal of the device for example) of an audiovisual sequence representing additional information in relation to the rendered audiovisual element), and / or a command to be transmitted to a computer application used by device 200, for example an application running at least partially on device 200 or an "online" application running at least partially remotely, for example on server 160 of system 100.Examples of input user interfaces for device 200 include a sensor, an audio and / or video acquisition means (microphone, camera (webcam) for example), a keyboard, a mouse.

[0084] Said at least one microprocessor of the device 200 may in particular be adapted for enriching at least one audiovisual element rendered on at least one first output user interface of an electronic device, said processor being configured to: - A conditional proposal, during a current rendering of said audiovisual element, to render, on at least one second output interface of said electronic device, an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

[0085] Some of the above input / output modules are optional and may therefore be absent from device 200 in certain embodiments. In particular, while the present application is sometimes detailed in connection with a device communicating with at least one other device of system 100, the method can also be implemented locally by a device (for example, one of the terminals of system 100), to enrich, for example, an audiovisual element with text stored locally on the device using word sequences also stored locally on the device. device. According to another example, the process can be implemented centrally (on a server 160 or a gateway of system 100 for example), so as to take into account, in the rendering history of the audiovisual element, the renderings of this audiovisual element on output interfaces of several terminals of the same user).

[0086] On the contrary, in some of its embodiments, the process can be implemented in a distributed manner between at least two devices 110, 120, 130, 140, 150, and / or 160 of the system 100. (for example, to store locally the different rendering histories and access a remote data structure, associating audiovisual sequences with audiovisual elements as described above).

[0087] The term "module" or the term "component" or "element" of the device refers here to a hardware element, in particular a wired one, or a software element, or a combination of at least one hardware element and at least one software element. The method according to the invention can therefore be implemented in various ways, in particular in wired and / or software form.

[0088] Figure 3 illustrates some embodiments of the method 300 of this application. The method 300 can, for example, be implemented by the electronic device 200 illustrated in Figure 2.

[0089] In the illustrated embodiment, the method may include obtaining 310 at least one audiovisual element rendered by the device 200 and associated with an audiovisual sequence in a data structure accessible to said device. The way in which this audiovisual element is obtained may vary depending on the embodiment. In particular, it may be detected during rendering via a software and / or hardware probe adapted to acquiring a stream rendered on an output interface. For example, the audiovisual element may be obtained from an image representing a visual stream (for example, text) appearing on the screen of said device, via a character recognition (or OCR) technique.The audiovisual element can be obtained, in certain embodiments, by analyzing, using a speech recognition technique, an audio stream played on a loudspeaker of said device.

[0090] The stream may, for example, be being received from another device) or be fully accessible locally by device 200.

[0091] Such techniques can help the solution to be independent (or at least weakly dependent) on the application implementing the rendering of the audiovisual element. Thus, in at least some embodiments, the method of the present application can take into account the rendering of the same audiovisual element by several applications implementing the same or different output interfaces of the device (without adaptation being necessary, for example).

[0092] Obtaining the audiovisual element may include verifying the existence of an association between this audiovisual element and an audiovisual sequence. This verification may be carried out, according to the embodiments, prior to or during the implementation of the process of this application. For the sake of simplicity, it will be assumed hereafter that each audiovisual element obtained is associated with additional information comprising an audiovisual sequence.

[0093] The audiovisual sequence can, for example, be stored in a data structure in association with the audiovisual element that it is intended to enrich.

[0094] It can for example be obtained 312 (as illustrated) as soon as the audiovisual element is obtained, or when the possible rendering of the sequence is proposed, or on explicit request from the user from the data structure introduced above.

[0095] Obtaining the sequence associated with a rendered audiovisual element at a later date (for example, when proposing the rendering or in response to a user request to render the sequence) can help limit the costs of accessing the sequences. Thus, obtaining the sequences in response to a user request to render the sequence can help limit the costs of accessing the sequences to those that are actually rendered.

[0096] Obtaining a sequence as soon as the audiovisual element (or rendering proposal) is obtained (therefore prior to its eventual rendering) can help to render the sequence faster when requested by the user, and can also help to guard against possible network communication problems requiring multiple accesses to the data structure.

[0097] In the embodiment illustrated in [Fig.3], the method may include obtaining 320 at least a part of a rendering history of the audiovisual element.

[0098] As detailed below, a rendering of the audiovisual element may result in the addition to the rendering history associated with the audiovisual element (for example via an identifier of the audiovisual element, such as an identifier used in the sequence data structure) of a so-called rendering event comprising at least the following data: - A category (or type) of the rendering event, and - A timestamp of the current rendering.

[0099] In certain embodiments, the rendering event may further include - An indicator of the occurrence of said rendering proposal and / or a rendering of said audiovisual sequence (This indicator may be optional in certain embodiments), and - indicative information regarding the user's response to the proposed rendering, if applicable. (This information may be optional in certain embodiments, for example in embodiments where the ca Rendering event categories include event categories representative of such a response (such as the "IKnow" or "IdontKnow" events detailed below).

[0100] The rendering history can, depending on the embodiment, group data relating to a variable number of renderings preceding the current rendering. Thus, in some embodiments, the history includes rendering event data relating to all renderings that occurred during a first period, for example, a period originating from a fixed date or timestamp (for example, the launch timestamp of the application implementing the process of this application). In other embodiments, the history includes rendering event data relating to all renderings that occurred during a floating period, representing a fixed duration up to the current time. These periods can be configurable (via access to a configuration file, for example).

[0101] Such embodiments may allow, during the current rendering (to avoid lengthy storage of certain variables for reasons of confidentiality, for example), successive calculations of variables resulting from each previous rendering present in the history and necessary for calculating their value during the current rendering. Such variables may include, for example, the knowledge rate, memory strength, learning ability coefficient, memory capacity, and / or any other weighting coefficients. Such embodiments may, for example, use indicators of the occurrence of the rendering proposal and / or a rendering of the audiovisual sequence, and / or information indicating a user response to a rendering proposal, where applicable, associated with the rendering events.

[0102] In other embodiments, the history includes data relating only to rendering events concerning the immediately preceding rendering of the audiovisual element before the current rendering, or to the immediately preceding rendering of the audiovisual element before the current rendering involving a rendering of the audiovisual sequence (more simply, the last rendering of the audiovisual sequence before the current rendering of the audiovisual element). In still other embodiments, the history includes data relating only to the most recent rendering event that occurred before the current rendering and involving a rendering of the audiovisual sequence (more simply, the last rendering of the audiovisual sequence before the current rendering of the audiovisual element).The most up-to-date values ​​of the variables (such as knowledge rate, memory strength, ease of learning coefficient, memory capacity, and / or possible other weighting coefficients) resulting from the last rendering of the audiovisual element (and / or associated audiovisual sequence) and necessary for calculating the current knowledge rate and the . Subsequent values ​​of these variables (for the next render, for example) can also be stored, either in association with the history or independently. For example, the user's memory capacity (common to all previous renders, regardless of the audiovisual element considered) can be stored independently of a history relating to at least one render of at least one audiovisual element (and the associated audiovisual sequence, if applicable) for the user.

[0103] These variables take into account, in particular, the last rendering of the audiovisual sequence, and any other rendering events that may have occurred between this last rendering of the audiovisual sequence and the current rendering. For example, in certain embodiments, they may take into account all the rendering events that have occurred relating to the audiovisual element. Such embodiments (where the entire history is not stored in the history) can help to limit the memory usage and computational load of the process described in this application and help to limit its execution time, for example, for adaptation to audiovisual elements rendered continuously by the device.

[0104] The invention, in at least some embodiments, proposes to identify audiovisual elements that may be unknown, or simply forgotten, by a user based on a rate (or index, or degree) of knowledge of the user for this audiovisual element (itself taking into account the strength of the user's memory for this audiovisual element), and to supplement its rendering by rendering of additional information (the audiovisual sequence) providing it, for example, with elements of understanding of this audiovisual element when the rate of knowledge (for example because it is less than a first rate (also more precisely called the first value of the rate of knowledge), like a threshold) is representative of a low knowledge of the user.No additional rendering is offered, for example, when the user's knowledge of this audiovisual element appears sufficient (for example, because the level of knowledge is higher than the first level).

[0105] Thus, in the illustrated embodiment, the process can include obtaining (for example, a calculation) 330 the user's knowledge rate regarding the commonly rendered audiovisual element (also referred to hereafter as the current knowledge rate), comparing 340 the current knowledge rate with the first knowledge rate, of constant numerical value for example, and making a conditional proposal 350 (depending on the result of this comparison 340 in particular) for the rendering of the complementary audiovisual sequence.

[0106] As explained above, depending on the embodiment, the calculation 330 of the knowledge rate may include a sequential analysis of rendering events successive history, by successively calculating during this analysis, the impact of each rendering event on the knowledge rate, memory strength, learning ease coefficient, memory capacity, and / or any other weighting coefficients, or taking into account the last rendering event of the audiovisual element and / or audiovisual sequence and the already up-to-date values ​​(i.e. taking into account the rendering events that have already occurred) of the knowledge rate, memory strength, learning ease coefficient, memory capacity, and / or any other weighting coefficients) stored in association with the history relating to the audiovisual element.

[0107] In certain embodiments, as in some of the examples described below, several categories of events can be distinguished that are likely to cause a fluctuation in the strength of memorization. These different categories of events can have different effects on the strength of memory.

[0108] In certain embodiments, the following rendering events can be distinguished. Event Label Definition Consequent Action Appearance Rendering of the audiovisual element appears on the user's screen. A calculation of the audiovisual element's knowledge rate is performed using the memory strength of the previous rendering if it exists, otherwise its initial value. Highlight The audiovisual element is considered unknown during its rendering. A rendering suggestion for the complementary audiovisual sequence associated with the audiovisual element is implemented. ShowDef The user clicked on the rendering suggestion for the audiovisual sequence. The audiovisual sequence is rendered. The knowledge rate is set to its maximum value (here, 1). Iknow: The user explicitly declares knowing the audiovisual element (and therefore the associated audiovisual sequence). The knowledge level reaches its maximum value (here, 1). Memory strength increases. IdontKnow: The user explicitly declares not knowing the audiovisual element (and therefore the associated audiovisual sequence). The knowledge level reaches its minimum value (here, 0). The audiovisual sequence is rendered. Memory strength decreases (for example, it reaches a minimum value).

[0109] Of course, the categories of rendering events may vary depending on the implementation methods.

[0110] Examples of calculating the knowledge rate, memory strength, learning ease coefficient and memory capacity will be described later as a function of the occurrence of rendering events as introduced above.

[0111] In the embodiment illustrated in [Fig. 3], the method may include, in response to a possible rendering proposal, a 360° action by the user to accept or reject the rendering of the sequence. This 360° action, if the rendering is accepted (for example, clicking on a link in the proposal), may trigger a 370° rendering of the audiovisual sequence on an output interface of the device.

[0112] As illustrated in [Fig.3], the process may include, following a proposal to render the audiovisual sequence, or following the actual rendering of the audiovisual sequence, an action 352, 372 by the user to explicitly indicate whether or not he knows the sequence associated with the audiovisual element.

[0113] In the embodiment illustrated in [Fig. 3], the method may include determining a possible evolution (update) 380 of at least certain variables among the knowledge rate, memory strength, learning ease coefficient, and memory capacity following the rendering of the audiovisual element, the rendering proposal, and any user actions. According to [Fig. 3], the method may include updating 390 of the history to take into account the current rendering of the audiovisual element and, optionally, the rendering proposal of the audiovisual sequence associated with the audiovisual element as well as the possible rendering of this sequence and any user instructions, and storage, in association with this history, of the updated variables.

[0114] We now describe in more detail, by way of example, a calculation of the knowledge rate as a function of the occurrence of network events already introduced according to a first and a second example of implementation.

[0115] In both examples, the current knowledge rate is notably a function of the previous knowledge rate (stored in association with the history).

[0116] In the first example, the current knowledge rate is forced (fixed) to 1 in the case of multiple renderings of the audiovisual element (events "appearance").

[0117] In the second implementation example, the current knowledge rate is increased before being used (for the conditional proposition in particular) by adding the following value: 0.002 *ease factor^nb repetition2 where "ease factor" is the coefficient of ease of learning already introduced in connection with memory strength and "nb-repetition" designates the number of successive renderings of the audiovisual element without rendering of the associated audiovisual sequence (succession of events of type "Appearance" in the example), or alternatively the number of successive renderings of the audiovisual element without explicit indication of knowledge of the associated audiovisual sequence by the user.

[0118] In these examples, the audiovisual element is a textual element, such as a named entity (such as "carbon footprint"). A named entity is considered to be known when the user's level of knowledge about that named entity exceeds a first level (threshold) of the knowledge level (called here "knowledge threshold" and set at 0.7).

[0119] In these two examples, for the sake of simplicity, the user's memory capacity (the use of which will be detailed in another example) is not taken into account in the calculations. Indeed, when the number of audiovisual elements on which the memory capacity calculation is based is small, it may not be taken into account, as detailed later.

[0120] Example 1: (current knowledge rate forced to 1 in case of multiple renderings of the audiovisual element (events "appearance")). • First rendering of the audiovisual element:

[0121] During the first rendering of this named entity (at tO), as there is no history, the knowledge level is initialized to 0. The knowledge rate being less than the first value of the knowledge rate, a "proposal" for rendering the audiovisual sequence associated with the named entity (here a definition) is made (for example the named entity is highlighted, for example by highlighting, on the screen of the user's device).

[0122] A rendering event of type "Appearance" does not modify the memory strength, so the memory strength remains at its lowest value.

[0123] Following the proposal made, the user requests (for the first time) a rendering of the audiovisual sequence. This sequence is then rendered.

[0124] Due to the (first) rendering of the sequence (also referred to here as the initial rendering), the knowledge rate is set to 1, the ease of learning coefficient is initialized to 1.1, and the memory strength is initialized; its initial value is chosen here to be 0.12 to correspond to the memory strength obtained for the first value (threshold) of the knowledge rate and a duration of one day. The temporary memory capacity indicator is set to 1 (first rendering of the sequence). • Second rendering of the audiovisual element:

[0125] During the second appearance of the named entity, at t0+3h, the knowledge rate is calculated using the formula:

[0126] k rnew = k rM

[0127] Where

[0128] __________ oM ln( knowledge threshold)

[0129] With "new" denotes the current rendering and "old" the previous rendering, (with krold = 1 here)

[0130] Therefore, krnew is equal in our example: ~ q 95

[0131] Since the knowledge rate is greater than the first value (0.7 in our example), no associated sequence rendering suggestion is made. No modification is made to the memory strength, given that it is not certain that the user paid attention to the named entity. • Third rendering of the audiovisual element:

[0132] When the named entity appears, at t+2j, the knowledge rate for the current rendering is • [°133] kr^ = kr^e^ = 0.96*^ = 0.49

[0134] The knowledge rate is less than the first value of the knowledge rate, therefore the proposal for rendering the sequence is carried out.

[0135] The knowledge rate remains unchanged because the Appearance-type event did not trigger a recall of the "definition" of the audiovisual element. Similarly, the learning ease coefficient is not increased for the same reason, and since the latter does not change, memory strength does not increase either.

[0136] The user displays the definition of the named entity. The knowledge rate goes to its maximum (1).

[0137] The learning ease coefficient is multiplied by 1.2. Its new value is Therefore, 1.1*1.2=1.32.

[0138] Memory strength is obtained by multiplying its previous value by the learning ease coefficient (i.e., 1.32 here). Its former value being its initial value --!—, memory strength takes the value -LLL ~ 3 7. ln(0.7) in(0.7) '

[0139] The temporary memory capacity indicator changes to 2. (2nd rendering of the sequence) • Fourth rendering of the audiovisual element:

[0140] When the audiovisual element appears, at t+4j, the current knowledge rate krnewest is 0.58-

[0141] The current knowledge rate is lower than the first (threshold) knowledge rate, therefore the proposal for rendering the sequence is made.

[0142] The user does not request the rendering of the definition. • Fifth rendering of the audiovisual element:

[0143] During the next appearance of the audiovisual element, at t+5j, the knowledge rate is = 0.58¼^ s 0.44-

[0144] The knowledge rate is lower than the first (threshold) knowledge rate, therefore the proposal for rendering the sequence is made. • Sixth rendering of the audiovisual element:

[0145] 111 there is a succession of three Appearance-type events. In this example, a The threshold number of repetitions (here 3) is defined. When this threshold is reached (as here), the fill rate is forced to 1 and the learning ease coefficient is multiplied by 1.5, giving it the value 1.32 * 1.5 = 1.98.

[0146] The memory strength is therefore multiplied by 1.98, giving -1.32*1.98 -2.6136 ^733 ln(0.7) ln(0.7) ~

[0147] The knowledge rate is higher than the first (threshold) knowledge rate, therefore the proposal to render the sequence is not carried out.

[0148] In this example, the sequence is also considered known due to the succession of renderings of the audiovisual element without a request to render the sequence; therefore, the user's memory capacity is initialized to 2. (For the sake of simplicity, the memory capacity is not used at this stage in this example and will be detailed later in connection with another example.) • Seventh rendering of the audiovisual element:

[0149] When the named entity appears, at t+9j, the knowledge rate is krM*e^ - = 0.76-

[0150] The knowledge rate is higher than the first (threshold) knowledge rate, therefore the proposal to render the sequence is not carried out.

[0151] Eighth rendering of the audiovisual element:

[0152] During the next occurrence of the named entity, at t+10j, the knowledge rate is krrtew = 0.76 s 0.66'

[0153] The knowledge rate is lower than the first (threshold) knowledge rate, therefore the proposal for rendering the sequence is made. • Ninth rendering of the audiovisual element:

[0154] When the named entity appears, at t+12j, there is a succession of three Appearance type events, so the knowledge rate goes back to 1 and the learning ease coefficient is multiplied by 1.5, which gives 1.98*1.5 = 2.97.

[0155] Since the ease of learning coefficient exceeds 2.5 (its maximum value in the example), its new value is set to 2.5. The memory strength is therefore multiplied by 2.5, which gives 2..6i.36^2.5 _ ..^534 > o ln(0.7) ln(0.7)

[0156] The knowledge rate (1) is higher than the first (threshold) knowledge rate, therefore the proposal to render the sequence is not carried out. • Eleventh rendering of the audiovisual element:

[0157] When the named entity appears, at t+14j, the knowledge rate is krM*m = 1*^^ = 0.9-

[0158] The knowledge rate is higher than the first (threshold) knowledge rate, therefore the proposal for rendering the sequence is made.

[0159] In example 1, the ease of learning coefficient can be multiplied by 1.2 or by 1.5. This is of course an example and this multiplicative factor can of course vary according to the implementations, as described in more detail later in relation to the user's memory capacity.

[0160] Example 2 (with current knowledge rate increased during audiovisual element renderings) • First rendering of the audiovisual element:

[0161] During the first rendering of the audiovisual element (at tO), as there is no history, the knowledge level is initialized to 0. The knowledge rate being less than the first (threshold) knowledge rate (here at 0.7), a "proposal" for rendering the audiovisual sequence associated with the audiovisual element (here a definition) is made (for example the audiovisual element is highlighted, for example by highlighting, on the screen of the user's device).

[0162] Following the proposal made, the user requests (for the first time) a rendering of the audiovisual sequence (for example, the user indicates that they want a display of the resolution associated with the currently rendered audiovisual element). This audiovisual sequence is then rendered.

[0163] Due to the (first) rendering of the sequence (also referred to herein as the initial rendering), the rate of

[0164]

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[0177] knowledge is set to 1 (indeed, the associated audiovisual sequence is now considered to be known to the user), the ease of learning coefficient is initialized to the minimum value of its range of values, here 1.1, and memory strength is initialized. Its initial value can, for example, be chosen here at 0.12 to correspond to the memory strength obtained for the first value (threshold) of the knowledge rate and to a fairly short duration, such as a duration on the order of a few days (for example, 1 day). The temporary memory capacity indicator changes to 1 (first rendering of the sequence). • Second rendering of the audiovisual element: During the second appearance of the named entity, at tO+3h, the knowledge rate is calculated using the formula: krnew = krold*e^ Or jn { knowledge threshold ) Therefore, krncw is equal to in our example: _ ^—7- ~ q Since the knowledge rate is higher than the first rate (threshold 0.7 in our example), we consider that the sequence associated with the audiovisual element is known, therefore no rendering proposal for the associated sequence is made. No modification is made to the memory strength, given that it is not certain that the user has paid attention to the named entity. • Third rendering of the audiovisual element: When the named entity appears, at t+2j, the knowledge rate for the current rendering is ■ krne = krM*e^ = 0.96*^ s 0.49 According to the second example, as there is a succession of events of type "Appearance", the current knowledge rate is increased (addition) by 0.002*ea$'e factor^nb repetition2 — 0.002*1.1*12 = 0.0022- The current knowledge rate once increased is therefore 0.4922 (or about 0.49). The increased knowledge rate is lower than the first (threshold) knowledge rate, therefore the proposal for rendering the sequence is made. The user displays the definition of the named entity. The knowledge rate reaches its maximum (1). The ease of learning coefficient is multiplied by 1.2 (an increase of 20%). Its new value is therefore 1.1*1.2=1.32. Memory strength is obtained by multiplying its previous value by the coefficient of ease of learning (i.e., 1.32 here). Its former value being its initial value --1—, the memory strength takes the value —LAL. ~ 3 7. ln(0.7) In(0.7)

[0178] The temporary memory capacity indicator changes to 2. (2nd rendering of the sequence) • Fourth rendering of the audiovisual element:

[0179] When the named entity appears, at t+4j, the current knowledge rate krnew is krM*e^ = = 0.58250554 s 0.58-

[0180] In a first variant, for example where we do not take into account events of type "IKnow" and / or "IdontKnow", the number of repetitions can be reduced to 1, due to the rendering of the sequence.

[0181] In a second variant, as detailed below in connection with this example 2, the rendering of the sequence is not taken into account, with regard to the number of repetitions of "Apparitions" because the rendering of the sequence was not followed by a confirmation by the user of his knowledge or lack of knowledge of the sequence.

[0182] Thus, according to the second example, since no IdontKnow / IKnow type event has occurred, the number of repetitions is increased. Consequently, the knowledge rate is also increased again due to the succession of Appearance type events. 0.002*ease factor*nb repetition2 = 0.002*1.32*22 = 0.01056- The knowledge rate is therefore 0.59306554 (or approximately 0.59).

[0183] The knowledge rate is lower than the first knowledge rate, therefore the proposal for rendering the sequence is made.

[0184] Here, the user does not request the rendering of the audiovisual sequence associated with the audiovisual element, nor does he specify whether or not he is familiar with it. Therefore, the learning coefficient and memory strength do not change.

[0185] Fifth rendering of the audiovisual element:

[0186] When the named entity appears, at t+5j, the knowledge rate is krold*e^ = 0.59306554*^ - 0.45263978-

[0187] Due to the succession of Apparition-type events, the knowledge rate is again increased by 0.002 *ea?e factor^nb repetition2 = 0.002*1.32*32 = 0.02376- The knowledge rate is therefore 0.47639978 (or approximately 0.48).

[0188] The knowledge rate is less than the first value of the knowledge rate, therefore the proposal for rendering the sequence is made.

[0189] Here again, the user does not request the rendering of the audiovisual sequence associated with the element, nor does he specify whether or not he is aware of it. Therefore, the co Learning efficiency and memory strength do not change. • Sixth rendering of the audiovisual element:

[0190] During the next appearance of the named entity, at t+7j, the knowledge rate is krM*e^ = 0.47639978 = 0.27750551-

[0191] The knowledge rate is increased by 0.002*ease factor^nb repetition2 — 0.002*1.32*42 = 0.04224- The knowledge rate is therefore 0.31974551 (or approximately 0.32).

[0192] The knowledge rate is lower than the first knowledge rate, therefore the proposal for rendering the sequence is made.

[0193] According to one variant, the knowledge rate therefore continues to increase, over the succession of "Appearance" type events as described above, or following a rendering request by the user (Showdef event), or an "IKnow" event in certain embodiments) until it becomes greater than the first value, where the learning coefficient increases again by 20% (thus also varying the memory strength).

[0194] According to another variant; after a succession of several Appearance-type events (for example, 3 here), the learning ease coefficient can be increased. Indeed, the more the element is rendered, the more likely the user is to have paid attention to the element during at least one of these renderings (thus increasing its learning ease as explained above).

[0195] In this example, the ease of learning coefficient is thus multiplied by 1.2, which gives 1.32*1.2= 1.584.

[0196] The memory force is therefore multiplied by 1.584, giving - 5.86214433- ln(0.7) ln[0.7]

[0197] The knowledge rate is lower than the first knowledge rate, therefore the proposal for rendering the sequence is made. • Seventh rendering of the audiovisual element:

[0198] When the named entity appears, at t+9j, the knowledge rate is krM*m = 0.3197455 l*e^ = 0.22731877-

[0199] the knowledge rate is increased by 0.002 * ease factor * number of repetitions² = 0.002 * 1.584 * 5" 0.0792 - The knowledge rate is therefore 0.30651877 (approximately 0.31). The knowledge rate is lower than the first value of the knowledge rate, so the proposed rendering of the sequence is carried out. • Eighth rendering of the audiovisual element:

[0200] When the named entity appears, at t+10j, the knowledge rate is krM^ = 0.30651877 W ® 0.2584476- L6 the knowledge rate is increased by 0.002*ease factor*nb repetition2 = 0.002*1.584*62 = 0.114048- The knowledge rate is therefore 0.3724956 (or approximately 0.37).

[0201] The knowledge rate is lower than the first knowledge rate, therefore the proposal for rendering the sequence is made. • Ninth rendering of the audiovisual element:

[0202] During the next occurrence of the named entity, at t+12j, the knowledge rate is krol^ = 0.3724956*^ = 0.26482074- The knowledge rate is increased by 0.002*ease factor*nb repetition2 = 0.002*1.584*72 = 0.155232- The knowledge rate is therefore 0.42005274 (or approximately 0.42).

[0203] As before, due to the succession of several (here three) Apparition type events, the learning ease coefficient is again multiplied by 1.2, which gives 1.584*1.2 = 1.9008.

[0204] The memory strength is therefore multiplied by 1.9008, which gives -2.09088*1.9008 - -3.9743447 - iii / 10-7^20 ln(0.7) “ in(0.7) - Ll. 1427639-

[0205] The knowledge rate is lower than the first knowledge rate, therefore the proposal for rendering the sequence is made. • Tenth rendering of the audiovisual element:

[0206] When the named entity appears, at t+14j, the knowledge rate is krold*eÆ = 0.42005274 = 0.35103699- L6 knowledge rate is augmented by 0.002*ease factor^nb repetition2 = 0.002*1.9008*82 = 0.2433024- The knowledge rate is therefore 0.59433939 (or approximately 0.60). • Eleventh rendering of the audiovisual element:

[0207] When the named entity appears, at t+17j, the knowledge rate is krold*eÆ, = 0.59433939*e™ = 0.45405462- The knowledge rate is increased by 0.002 * ease factor * number of repetitions² = 0.002 * 1.9008 * 92 = 0.3079296

[0208] The knowledge rate is therefore 0.76198422 (or approximately 0.76).

[0209] The knowledge rate is higher than the first knowledge rate, therefore the pro The rendering position of the sequence is not performed.

[0210] When the sequence is considered to be known (as in the last rendering above), the current value of the temporary memory capacity indicator (called (hereinafter the final value of the temporary memory capacity indicator) is used to initialize (or update) the user's memory capacity.

[0211] As explained above, in some embodiments (such as in Examples 1 and 2), at least one multiplicative factor (for example, 1.2 or 1.5) can be applied to the learning ease coefficient following the rendering of an audiovisual element and / or the associated audiovisual sequence. Thus, in Example 2, the learning ease coefficient can be multiplied by 1.2. This is, of course, just an example, and this multiplicative factor can vary depending on the implementation.

[0212] In some embodiments, the same multiplicative factor can be applied regardless of the user. However, in reality, individuals are all different and learn at varying speeds. Therefore, in some embodiments, the present application proposes to personalize this rate (or rates) for a user, that is, to vary it / them according to the user.

[0213] For example, after initialization of the process of this application, a default value of the multiplicative factor (e.g. 20% i.e. 1.2) may be applied initially (e.g. for a fixed period or until a significant amount of data is available (such as until the final value of the temporary memory capacity indicators of at least 50 audiovisual elements is obtained).

[0214] In a second step, the multiplicative factor can, for example, be varied based on the user's rendering history. Thus, the calculation of the learning ease coefficient for the individual can be based, for example, on the final value of the temporary indicators of the audiovisual elements for the user, using the user's average ability.

[0215] As explained above, the user's memory capacity represents the average of the final values ​​of the temporary indicators of the audiovisual elements for the user; that is, the average number of repetitions required for the user to learn the sequence associated with an audiovisual element. In other words, the user's memory capacity represents the average number of times the audiovisual sequence associated with an audiovisual element (a named entity in the example) will be played by the user in order to be learned.

[0216] Taking as an assumption in our example that the default value (20%) of the multiplicative factor corresponds to the ability of an individual to memorize the audiovisual element after 5 repetitions, we can vary this multiplicative factor according to the user's memory capacity.

[0217] For example, a possible variation would be to add (or remove) a factor of a % (where a is a real number of the order of 1, 3, 5 or 10 for example) per additional (or less) repetition.

[0218] With this example, for an average capacity of 3.2 repetitions for the user, we obtain a variation in the number of repetitions of: 5-3.2 = +1.8

[0219] The personalized learning factor would therefore be: 20 + (1.8*3) = 25.4%

[0220] Similarly, for an average capacity of 6.5 repetitions for the user, we obtain a variation in the number of repetitions of 5-6.5 = -1.5

[0221] The personalized learning factor would therefore be: 20 + (-1.5*3) = 15.5%

[0222] The present application offers the advantage in at least some embodiments, to be adapted (unlike some prior art solutions) to an implementation for the enrichment of content consumed as it is generated (such as emails, telephone conversations or chats), which could not be enriched before their broadcast, and / or to the enrichment of audiovisual elements whose rendering time may not be predictable.

[0223] In at least some embodiments, the proposed solution can be easy for the user to use since the user is only offered access to additional audiovisual sequences for automatically selected audiovisual elements, without any action being required from the user.

[0224] In at least some embodiments, the proposed solution can help limit the computing resources used when rendering audiovisual content, as well as network traffic to and / or from the device, since it helps limit the number of notifications offering audiovisual sequences, so as to offer the user only the audiovisual sequences that appear to be needed. Furthermore, the actual rendering of these audiovisual sequences may only occur following an explicit request from the user.

[0225] The solution described in this application can find applications in many fields. For example, it can be used to help a terminal user learn information, helping to reduce the time a user spends searching for information and helping them access the information and services they need.

[0226] User data may, for example, be stored locally on the device; to help preserve the protection of their data.

Claims

Demands

1. A method for enriching at least one audiovisual element rendered on at least one first output user interface of an electronic device, said method being implemented by said electronic device and comprising, during a current rendering of said audiovisual element: - A conditional proposal for a rendering, on at least one second output interface of said electronic device, of an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory strength of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory strength taking into account a history of at least one rendering event relating to at least one rendering, preceding said current rendering, of said audiovisual element and / or of said audiovisual sequence, on at least one output interface of said electronic device.

2. Method according to claim 1, characterized in that said conditional proposition further takes into account at least one coefficient of ease of learning said user for said audiovisual element.

3. Method according to claim 2, characterized in that said user learning ease coefficient for said audiovisual element takes into account a memory capacity of said user.

4. A method according to at least one of claims 1 to 3 wherein said method comprises, during said current rendering, a calculation of a current knowledge rate by the user of said audiovisual sequence associated with said audiovisual element, taking into account said memory strength, a time elapsed since at least one rendering event of said history, preceding said current rendering and / or said learningability coefficient and wherein said rendering proposal is implemented according to said calculated current knowledge rate.

5. Method according to claim 4 wherein said current knowledge rate further takes into account a knowledge rate calculated previously for said previous rendering of said history.

6. A method according to at least one of claims 1 to 5 wherein an event of rendering said rendering history: - A category of said rendering event; A timestamp of the rendering of the audiovisual element to which said rendering event relates and / or of said associated audiovisual sequence.

7. A method according to at least one of claims 4 to 6 wherein said method comprises: - an update, following said current rendering, of said knowledge rate, of said memory strength and / or of said learning ease coefficient, - a storage of at least one rendering event representative of said current rendering in said history, and - a storage, in association with said history, of said updated knowledge rate, of said updated memory strength and / or the updated learning ease coefficient.

8. A method according to at least one of claims 4 to 7 wherein the calculation of said knowledge rate further takes into account a number of successive renderings of said audiovisual element without rendering of said audiovisual sequence.

9. A method according to at least one of claims 1 to 8 wherein said method comprises, during said current rendering, an acquisition of an acceptance and / or a rejection of said rendering proposal.

10. An electronic device comprising at least one processor configured for enhancing at least one audiovisual element rendered on at least one first output user interface of an electronic device, said at least one processor being configured to: - A conditional proposal, during a current rendering of said audiovisual element, to render, on at least one second output interface of said electronic device, an audiovisual sequence associated with said audiovisual element, said proposal being implemented conditionally taking into account a memory capacity of a user of said device for said audiovisual sequence associated with said audiovisual element, said memory capacity taking into account a history of at least one rendering event relating to the less one rendering, preceding the current rendering, of the said audiovisual element and / or of the said audiovisual sequence, on at least one output interface of the said electronic device.

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