Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/12—Messaging; Mailboxes; Announcements
  • H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
  • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
  • G06F16/33—Querying
  • G06F16/3331—Query processing
  • G06F16/334—Query execution
  • G06F16/3344—Query execution using natural language analysis
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
  • G06F3/16—Sound input; Sound output
  • G06F3/167—Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F40/00—Handling natural language data
  • G06F40/40—Processing or translation of natural language
  • G06F40/58—Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q10/00—Administration; Management
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
  • G06Q50/10—Services
  • G06Q50/22—Social work

Definitions

• the invention is in the field of bidirectional communications between a plurality of sources and a plurality of recipients, and more specifically relates to a method of communication between a plurality of connected objects or services each having a clean built language and being able to communicate.
• an intelligent communication platform comprising a plurality of distributed data processing units communicating via at least one bidirectional natural language exchange unit and each comprising at least one software unit and and / or hardware for media and protocol adaptation, at least one software and / or hardware language conversion unit, and at least one bidirectional software and / or hardware interface arranged between the two-way natural language exchange unit and the information processing unit.
• the invention also relates to an intelligent communication platform between a plurality of connected objects or services each having a clean built language and being capable of being a source and / or recipient of information comprising a plurality of distributed processing units.
• information communicating via at least one bidirectional natural language exchange unit and each comprising at least one software and / or hardware media adaptation and protocol unit, at least one software and / or hardware language conversion unit, and at least one bidirectional interface software and / or hardware unit arranged between the bidirectional natural language exchange unit and said information processing unit,
• the invention also relates to a communication system between a plurality of connected objects or services comprising such an intelligent platform.
• the invention also relates to a computer program stored on a recording medium and comprising instructions for implementing the method according to the invention when it is executed by computer. STATE OF THE PRIOR ART
• GUIs graphical user interfaces
• CLIs command-line interfaces
• NLP Natural Language Processing
• Siri ⁇ of Apple ⁇ or Cortana ⁇ of Microsoft ⁇ offer a virtual assistant service to perform operations such as searching for information on the Internet or booking transportation tickets using voice commands
• Nuance Communication ⁇ also markets customer support products and services from virtual agents simulating human operators
• Alexa ⁇ of Amazon ⁇ offers a voice interface service for third-party services.
• NLI Natural Language Interface
• GUI graphical interfaces
• CLI command line
• An object of the invention is to overcome the disadvantages of the prior art described above.
• Another object of the invention is to unify the exchanges that humans, connected objects and digital services can have with each other (for example between connected objects, between humans and objects, etc.) around a common natural language. .
• Other users may also be concerned, especially animals and robots.
• natural target language (CNL - Core Natural Language) is used to denote the common natural language used, and by constructed language, a numerical language composed of commands, parameters, encodings of information, implicit or explicit conventions, etc. coupled to one or more communication protocols for communicating with one or more connected objects.
• CNL Core Natural Language
• These built languages may vary depending on the objects and applications.
• the target natural language may for example be a widely spoken language such as English, but other natural languages are also possible. It is chosen either by configuration or any other mode (voting, negotiation ).
• the method according to the invention also comprises a step of analyzing the information exchanged in the target natural language and a step of resolving the ambiguities and inconsistencies identified by means of a software and / or hardware control and resolution unit. ambiguity and relevance of the information exchanged.
• Said step of resolving ambiguities and inconsistencies consists in verifying whether the information exchanged in target natural language between the connected objects or services requires lexical, syntactical or semantic ambiguity resolution, additional information or an implicit confirmation or explicit, as well as the possible implementation of these ambiguity resolutions, a request for information and confirmations.
• the method according to the invention further comprises a step of converting a natural language used by a source or a recipient to the selected target natural language, by means of a software and / or hardware bidirectional language alignment unit.
• At least one set of connected objects or services is connected to the intelligent platform via at least one connected gateway having a clean built language and being able to be source or recipient of information, said gateway being connected to at least one distributed information processing unit by the software and / or hardware media adaptation and protocol unit and is intended to provide at least one of the following functions:
• the method according to the invention furthermore comprises a target natural language learning procedure used in order to improve the conversion performances between the constructed languages specific to the objects, the connected services and the connected gateway on the one hand, and the target natural language on the other hand, as well as procedures for resolving ambiguities and inconsistencies of the messages exchanged in the target natural language.
• said learning procedure is executed automatically, in the background, without directly interfering with the conversion and ambiguity resolution steps and comprises the following steps:
• the natural language information exchange services are either SMS services (Short Message Service), either Multimedia Message Service (MMS), e-mail services, instant messaging services, discussion forums, public or professional social networks, or dedicated communication services.
• SMS services Short Message Service
• MMS Multimedia Message Service
• e-mail services instant messaging services
• discussion forums public or professional social networks
• dedicated communication services dedicated communication services.
• the method according to the invention is implemented via an intelligent communication platform in which the software and / or hardware media adaptation and protocol unit is configured to intercept the information sent by an object or a service connected to a device. a built-in language specific to that connected object or service acting as a source, and secondly to provide the exchanged information in a built-in language specific to a connected object or service when that object or service is the recipient of that information,
• the software and / or hardware language conversion unit is configured, on the one hand, to automatically convert said received information into a specific built-in language of the transmitting connected object or service to a target natural language previously selected from among a plurality of natural languages, and secondly, to automatically convert the information exchanged in target natural language for a connected object or service recipient of said information to the built language used by this object or by this connected connected service
• the bidirectional interface software and / or hardware unit is configured, on the one hand, to transmit the target natural language information to the bidirectional natural language exchange unit so that it sends them to the object or the recipient connected service, and secondly, to receive the target natural language information transmitted by the transmitting connected objects and services through the natural language two-way exchange unit.
• Said platform also comprises at least one software and / or hardware unit for controlling and resolving ambiguity and relevance, and a bidirectional software and / or hardware unit for aligning the languages, the software unit and / or the hardware of the platform.
• control and resolution of ambiguity and relevance being able to verify whether the information exchanged in target natural language between the objects or connected services require lexical ambiguity resolution, syntactic or semantic, additional information or confirmation implicit or explicit, as well as the possible implementation of these ambiguity resolutions, requests for information and confirmations
• the bidirectional software and / or hardware unit of language alignment is responsible for the conversion of a language. a source or recipient to a previously selected target natural language.
• the platform according to the invention is integrated in a communication system between a plurality of connected objects or services each having a clean built language and being capable of being source or recipient of information exchanged via said intelligent platform. It further comprises a connected gateway arranged between a part of said connected objects or services intended to provide at least one of the following functions:
• Said gateway connected to a clean constructed language, is connected to at least one distributed information processing unit by the software and / or hardware media adaptation and protocol unit, and is capable of being a source or recipient information exchanged.
• FIG 1 is a general diagram illustrating a communication platform according to the invention
• FIG. 2 diagrammatically represents an architecture of the platform of FIG. 1 showing the different information processing layers exchanged between a source and a recipient via the platform of FIG. 1,
• FIG. 3 schematically illustrates a technical environment of the elements making up the platform of FIG. 1,
• FIG. 4 schematically and partially represents the units of platform 1 making it possible to exchange information between a human and a connected object
• FIG. 5 represents schematically and partially the units of the platform 1 making it possible to exchange information between two connected objects
• FIGS. 6 and 7 respectively represent functional diagrams illustrating in detail the steps of processing the information exchanged between a human and an object connected via the platform according to the invention
• FIGS. 8 and 9 represent functional diagrams illustrating in detail the steps of processing information exchanged between two objects connected via the platform according to the invention
• FIGS. 10A and 10B respectively illustrate the essential processing steps applied to a message transmitted by a remote source to a recipient, and the essential processing steps applied to a target natural language message sent by the recipient in response to the message received from said remote source,
• FIG. 11 is a detailed flowchart illustrating the alignment of the natural language of the remote source on a selected target natural language
• FIG. 12 is a detailed flowchart of the alignment step of the units used by the remote source with those used by the recipient,
• FIG. 13 is a detailed flowchart of the step of aligning the date, time and duration references used by the remote source with those used by a connected object or a digital service,
• FIG. 14 is a detailed flowchart of the step of aligning the date, time and duration references used by a recipient, transmitter of a target natural language message, with those used by the remote source of the figure 10,
• FIG. 15 is a detailed flowchart of the alignment step of the units used by the recipient, transmitter of a target natural language message, on those used by the remote source of FIG. 10,
• FIG. 16 is a detailed flowchart of the target natural language alignment step of the recipient, transmitter to the natural language of the remote source of FIG. 10,
• FIG. 17 represents a detailed view of a unit for resolving the ambiguity and relevance of the platform according to the invention
• FIG. 18 represents a flowchart of the ambiguity and relevance control steps of a target natural language message of a remote user by means of the unit of FIG. 17,
• FIG. 19 represents a flowchart of the steps of transforming the target natural language information into a constructed language used by a connected object or a digital service,
• FIG. 20 represents a flowchart of the stages of transformation of the information in constructed language (digital format for controlling connected objects or digital format for piloting digital services) in target natural language,
• FIG. 21 diagrammatically illustrates the steps of an exchange relating to a request for assistance between two communicating objects
• FIG. 22 diagrammatically illustrates a communication system between a plurality of connected objects or services intended to implement the method according to the invention.
• FIG. 1 represents a general view showing sources and recipients of different natures capable of communicating via a platform 1 according to the invention.
• sources and recipients can be either humans 2 provided with a communication device such as for example a computer, a tablet 4, or a smartphone, or connected robots 6, or animals 7 equipped with electronic boxes with means of connection to the platform 1 and for transmitting to animals information representing instructions, or to receive information from these animals about their behavior for example.
• Humans can express themselves in natural language by speaking in a microphone with automatic transcription in text 8, or by text input by means of a conventional keyboard 10 or a Braille keyboard 12 connected to a communication device. They can also express themselves by means of a sign language transcriber 14 or by detection of brain activity 16.
• Connected objects can be of different natures, such as for example industrial robots, service robots, miniaturized sensors associated with clothes 17 such as for example combinations for professional use, sensors and actuators located in residential premises 34, vehicles 36, factories and offices 31, in the public domain 32, etc.
• Sources and recipients may further be digital services provided by remote servers.
• natural language will designate a language naturally used by human beings such as English, French, Mandarin Chinese, etc.
• target natural language will designate a natural language selected from among several natural languages depending on its area of use, its range of use or the ease of its automatic learning. It can be modified by configuration, election or any other means to take into account the specificities of the sources and recipients and the intended application.
• a formal language comprising a set of symbols used to construct the different structures. It is defined by a formal grammar, such as algebraic grammars and computer languages, and is likely to be parsed by automata.
• a typical example of a built-in language is application programming interfaces (APIs) consisting of a set of classes, functions, parameters, coding conventions, and so on. whereby connected objects and digital services provide services to other software applications.
• APIs application programming interfaces
• FIG. 2 represents a layered architecture of the platform 1 according to the invention.
• This architecture comprises a first control layer 40 which groups together units that provide the conventional access control functions to platform 1, in particular the centralized authentication and access authorization functions for users of all kinds. , metering for statistical, billing, directory, and security reasons, and a second layer grouping management units 42 which provide the centralized functions of communication supervision, selection of a target natural language, updates of data processing software exchanged via platform 1, statistical calculations, availability management and improvements.
• the control units 40 and management 42 are for example software applications downloaded from local or remote servers controlled by the manager of the platform 1. The functions described above may reside within the control layer 40 or outside this layer and be interfaced with it.
• the control layer 40 also performs the function of handling exceptions in case of failure of an ambiguity resolution procedure found during the exchange of information via the platform 1 or in case of failure of a transaction, for example, in the event of repeated refusals by a connected object to provide information or to execute an order.
• the architecture of FIG. 2 comprises a bidirectional natural language exchange unit 50 connected to the communication devices associated with each source and to each recipient registered on the platform 1, and a set of processing units comprising a software unit and and / or media adaptation hardware and protocol 52, a software and / or hardware language conversion unit 54, a software and / or hardware control and ambiguity resolution and relevance 56, a software unit and and / or bidirectional hardware 58 for converting a natural language used by a source or a recipient into a selected target natural language, and for aligning the units of physical values and time units contained in the exchanged information, and an interface bidirectional 60 which realizes the adaptation between the bidirectional unit of exchange in natural language 50 and each bidirectional unit the 58 of conversion of a natural language.
• a set of processing units comprising a software unit and and / or media adaptation hardware and protocol 52, a software and / or hardware language conversion unit 54, a software and / or hardware control and ambiguity resolution and relevance 56, a software unit and and / or bidirectional hardware
• the software and / or hardware media adaptation and protocol 52-60 units can be implemented in a distributed way on the communication and data processing terminals (servers, computers, tablets, smartphones, boxes, ...) used by each source and each recipient connected to the platform 1, or implemented in one or more local or centralized platforms, or partially implemented on the terminals, local platforms and centralized platforms.
• MNGT Management module
• MPA-x 52 Media and Protocol Adapter
• x indicating the source or recipient type with which the MPA unit is associated
• x H for humans
• x 0 for connected objects
• x S for digital services
• the different units of the platform of FIG. 1 can access resources provided by remote servers such as, for example, a linguistic base 70, a translation service 72 or a directory service.
• the different units are automatically connected in case of need these remote servers 70, 72 74 via a description unit 76 of the connected object or the digital service to obtain:
• language base external resources such as translation services, ontology databases and lists of synonyms, hyponyms, hyperonyms, natural language corpora and various databases to complete or perfect their respective functions
• FIG. 4 schematically represents the distribution of the units making up the platform 1 architecture on the side of a source 2, a human being, equipped with a first communication and data processing terminal assembly 82 (a computer, a tablet or a smartphone for example) and on the side of a recipient 6, a weather station for example, equipped with communication and data processing functions 86 and supplemented by functions hosted by a central platform 85.
• a first communication and data processing terminal assembly 82 a computer, a tablet or a smartphone for example
• a weather station for example, equipped with communication and data processing functions 86 and supplemented by functions hosted by a central platform 85.
• the communication and data processing terminal assembly for the human user 82 comprises an interface 88 of keyboard, screen, microphone, earphone, camera, etc. type. to the user, a media adaptation and protocol MPA unit 52, an IF_NLX interface 60 for communicating in natural language via the NLXS module 50 and a transceiver to the transit network 84.
• the communication and data processing assembly for the connected object 86 comprises the necessary devices for exchanging and processing the messages in language constructed on the home network.
• the central platform 85 includes a transceiver 87 to the home network of the connected object, a media adaptation and protocol MPA 52, a NLAC 54 language conversion unit, a LARC 56 control and resolution of the ambiguity and relevance of the information exchanged, a LUTA 58 for converting a natural language used by the target natural language source, an IF_NLX interface 60 for communicating in natural language via the NLXS module 50 and a transceiver to the transit network 84.
• FIG. 5 schematically represents the distribution of the units composing the architecture of the platform 1 on the side of a source 2, a connected boiler equipped with communication and data processing functions 82 and completed by functions hosted by a central platform 85 , and on the side of a recipient 6, a weather station for example, equipped with communication and data processing functions 86 and supplemented by functions hosted by a central platform 85.
• the communication and data processing functions 82 and 86 comprise the necessary devices for exchanging and processing the messages in language constructed on the home network.
• the bi-directional NLXS 50 natural language exchange units ensure the exchange of information in natural language between different human interlocutors, robots, objects or digital service platforms.
• These units include known means of communication, such as SMS (Short Message Service) or MMS (Multimedia Message Service) services, email services, instant messaging services, or any other suitable application for exchanging information in natural language. .
• Media adaptation and MPA-x 52 protocol units such as, for example, a low power wide area network (LPWAN) radio adapter with its transport protocols (COAP, MQTT ...), a wifi interface or an interface Ethernet with its software drivers and its transport protocols (HTTP, TLS, ...) make the link between the users (humans, objects or services) connected to the platform 1 and the NLAC 54 units.
• LPWAN low power wide area network
• COAP transport protocols
• MQTT wireless local area network
• HTTP software drivers and its transport protocols
• HTTP software drivers and its transport protocols
• MPA-H 52 support written exchanges (texts), voice or any other type depending on the nature of the interaction (eg sign language).
• the MPA-0 52 units implement the object programming interface (API) protocol and the possible adaptation to the media with which objects are connected.
• API object programming interface
• These MPA-0 52 are for example software functions that generally implement the 'client' side of the interface with the connected object, the latter being considered as a (data) server in a
• the NLAC language conversion units 54 provide the transformation between, on the one hand, the information in the target natural language, and on the other side, the information in the digital format for controlling the connected objects or the format of the data exchanged with the data. digital services. Additional information such as images, sounds, files, indicators of emotions or prosody for example, can optionally be added to the information in natural language.
• the units for controlling and resolving the ambiguity and relevance of the information exchanged LARC 56 are installed in the receivers of the sources 2 and the recipients 6 and are configured to analyze the information received from the bidirectional units LUTA 58 on the one hand and from NLAC language conversion units 54 to determine the level of ambiguity of the messages exchanged in the target natural language and to ensure that the NLAC units 54 will be able to correctly perform the desired language conversion.
• the LARC units 56 judge that the level of ambiguity or inconsistency is too high, they perform an ambiguity resolution procedure, for example by asking the source of the message to repeat the request or by itself. asking to reformulate it differently.
• the LARC units 56 signal the abandonment of the exchange at the source of the information as well as the control units 40 and the management units 42.
• the bidirectional units LUTA 58 for conversion of a natural language used by a source or a recipient 6 into a selected target natural language are configured to convert, where necessary, the message language so as to use the natural language of the message. human user or target natural language selected to communicate with digital objects and services. These LUTA 58 bidirectional units also perform conversion of units (eg, Celsius / Fahrenheit or centimeters / inches, etc.), dates, and time (especially time zones and day change).
• the bidirectional interfaces IF_NLX 60 perform the adaptation between the NLXS units 50 and the LUTA units 58.
• the IF_NLX 60 interfaces are standard functions such as e-mail client (google ⁇ , outlook ⁇ , yahoo ⁇ %), microsoft skype ⁇ chat client, google hangout ⁇ , sms / mms client, etc.
• the NLAC 54, LARC 56 and LUTA 58 units may optionally automatically connect to the remote 70-74 servers to obtain, in real time or deferred, external resources such as translation services, ontology databases and mailing lists. synonyms, hyponyms, hyperonyms, corpus of natural language and various databases.
• FIG. 6 describes in detail the successive processing of the request of FIG. 5 by the different units of the architecture of platform 1.
• step 200 the request made by the source 2 is intercepted by the media adaptation and protocol adaptation unit 52 MPA-H assigned to the source 2.
• the language of the intercepted query is a human natural language.
• the unit MPA-H 52 transmits the intercepted query "What temperature is it now? At the IF-NLX 60 bi-directional interfaces without modifications.
• the bidirectional interface IF-NLX 60 transmits the request to the bidirectional unit of exchange in NLXS natural language 50.
• the transmission is carried out for example by means of an email service to the email address my_weatherstation@messagerie.com, where "mail" is the name of the email service used by the weather station.
• the NLXS unit 50 can also use an SMS service, an instant messaging service or any other application that makes it possible to exchange digital information in natural language and in real time or in a very short time.
• the NLXS 50 is a public email service to which the weather station 6 is previously registered with the email address my_weatherstation@messagerie.com.
• the NLXS unit 50 receives the request from the bidirectional interface IF-NLX 60 on the email client my_weatherstation@messagerie.com and transmits said request to the bidirectional interface IF-NLX 60 implemented on the side of the weather station 6 to the step 204.
• step 206 the bidirectional interface IF-NLX 60 implemented on the side of the weather station 6 receives the request on the client e-mail my_weatherstation@messagerie.com and transmits said request to the bidirectional unit LUTA 58 implemented on the side of the weather station 6.
• bidirectional unit LUTA 58 receives the query "What temperature is it today? And performs the conversion of the natural language used, French in this case, to the selected target natural language, which is for example English in this case, and then transmits the converted request in English (eg "how warm is it today?" To the control unit LARC 56 implemented on the side of the weather station 6.
• step 210 said LARC control unit 56 receives the request, the analysis and, in case of ambiguity, performs a procedure for resolving the ambiguity and relevance of the information exchanged.
• the LARC control unit 56 transmits the target natural language request, English, to the NLAC language conversion unit 54 installed on the side of the weather station 6.
• step 212 the NLAC unit 54 converts the request into the target natural language "How warm is it today?"
• "getmeasure" command of the API associated with weather station 6 http://my_weatherstation.com/api/getmeasure,access_token-[TOKEN]&device_id-
• the NLAC unit 54 then transmits the temperature measurement command to the MPA-0 media adaptation and protocol unit 52 implemented on the weather station side 6.
• said media adaptation and protocol unit MPA-0 52 transmits the request to the weather station 6 on the media and the protocol used to join the weather station 6.
• FIG. 7 illustrates the response of the weather station 6 to the request of the source 2.
• the weather station 6 Upon receipt of the temperature measurement command, the weather station 6 performs the measurement requested and generates the message ⁇ "status": "ok", “body”: [ ⁇ "beg_time”.-123456500, "value”: [ 69.8] ⁇ ] ⁇ , then transmits this message, in step 300, to the unit MPA-0 50.
• the unit MPA-0 50 receives the message from the weather station 6 adapts to the media (radio, Ethernet, etc.) and transport protocols (http, tls, mqtt, coap ... ) and transmits it to the NLAC unit 54 installed on the side of the weather station 6.
• step 304 said NLAC unit 54 receives the message in constructed language transmitted by the unit MPA-0 50, automatically converts it into target natural language, English in this example, "the current temperature is 69.8 ° F" and transmits the target natural language message to the LARC control unit 56 installed on the weather station side 6.
• the LARC control unit 56 receives the target natural language message "the current temperature is 69.8 ° F", and transmits it without processing to the bidirectional unit LUTA 58 installed on the weather station side 6 .
• the bidirectional unit LUTA 58 receives the target natural language message "the current temperature is 69.8 ° F" and performs the conversion of the target natural language into the natural language of source 2, the French in this case, and then converts the unit of measure from degrees Fahrenheit to degrees Celsius to obtain the user-defined natural language message "temperature is 21 degrees Celsius", and then transmits this message to the bidirectional interface IF-NLX 60 cooperating with the station weather 6.
• the bidirectional interface IF-NLX 60 sends the message in natural user language to the client whose email address is alice@aliceaddress.com.
• step 312 the NLXS unit 50 receives the message from the bidirectional interface IF-NLX 60 and retransmits it to the email client at the address source@sourceaddress.com.
• step 314 the bidirectional interface IF-NLX 60 in charge of the source 2 transmits the content of the message in natural language user "the temperature is 21 degrees Celsius" to the unit MPA-H of media adaptation and protocol 52 installed in the terminal of the source 2.
• step 316 the unit MPA-H 52 delivers the message in natural language user "the temperature is 21 degrees Celsius" to the source 2, either by a voice message, or by a display on the screen of the terminal of source 2.
• FIG. 8 represents the processing steps applied to a request sent by a boiler connected to the weather station.
• the boiler can for example be programmed to request information from the weather station 6 at regular intervals in order to perform an automatic adjustment of its operating parameters by adapting its power to the measured temperature.
• the boiler and the weather station exchange the messages by means of their respective communication and data processing assemblies 85 shown in FIG. 5.
• the boiler 400 transmits to the media adaptation unit and protocol MPA-0 52 a query in the built language and using the media and the protocols it implements: "GET: http: // xxxx / api / gettemperature? ".
• step 404 the unit MPA-0 52 transmits the request in the boiler built-up language to the NLAC language conversion unit 54 in charge of the boiler and automatically converts it to step 406, in a previously selected target natural language message, for example English: "what is the temperature now? And then transmits the target natural language query to the LARC 56 ambiguity and relevance control and resolution unit.
• step 408 the LARC unit 56 transmits the target natural language message "what is the temperature now? Without modification to the LUTA unit 58 for natural language conversion in charge of the boiler 400.
• step 410 the LUTA unit 58 transmits the target natural language message "what is the temperature now? Without modification to the bidirectional interface IF-NLX 60 in charge of boiler 400.
• the bidirectional interface IF-NLX 60 transmits the target natural language message to the NLXS unit 50 to be delivered to the email client of address my_weatherstation@messagerie.com, "mail" being the name of the service mail used by the weather station.
• step 414 the natural language exchange unit NLXS 50 receives the target natural language message and transmits it to the bidirectional interface IF-NLX 60 in charge of the weather station 6.
• the bidirectional interface IF-NLX 60 receives the message on the email client my_weatherstation@messagerie.com and transmits it, at step 416, to the LUTA unit 58 installed on the weather station 60.
• the LUTA unit 58 transmits the target natural language message "what is the temperature now? Without modification to the LARC 56 unit in charge of the weather station 6.
• step 420 said LARC unit 56 performs an ambiguity analysis of the message received in the target natural language.
• the LARC unit 56 judges that the received message is not ambiguous and is consistent with the role and the capabilities of the object it is responsible for, it transmits it without modification to the NLAC unit 54 of the weather station. .
• step 422 the NLAC unit 54 of the weather station 6 converts the received message to the target natural language "what is the temperature now? To the built-up language of the weather station, in this case an order
• [TOKEN] & device_id- [DEVICEID] & type-Temperature "and transmits the message obtained to the media adaptation unit and protocol MPA-0 52 in charge of the weather station 6.
• the unit MPA-0 52 transfers the command in constructed language to the weather station 6 using the protocols and the media used by the weather station 6.
• the weather station 6 Upon receipt of this command, the weather station 6 generates a response to the request.
• FIG. 9 represents the processing steps applied to the response to be sent by the weather station 6 to the boiler.
• step 500 the weather station sends the temperature measured by the response to the "getmeasure" command, expressed in the associated API language, to its MPA-0 unit 52, using the protocols and the media used by the weather station 6.
• step 502 the unit MPA-0 52 transmits the message received in the built-up language of the weather station to the NLAC language conversion unit 54 in charge of the weather station 6.
• step 504 the NLAC unit 54 automatically converts the message into a constructed language into English text which is the previously selected target natural language: "the current temperature is 69.8 ° F", and transmits the response, in English, at the LARC 56 unit in charge of the weather station 6.
• step 506 the LARC unit 56 in charge of the weather station 6 transmits the target language message "the current temperature is 69.8 ° F" without modification to the LUTA unit 58.
• the bidirectional unit LUTA 58 receives the target language message "the current temperature is 69.8 ° F", preserves the message in English since it is the natural language used by the boiler, then performs, if this is necessary, a conversion of the unit of measurement from degrees Fahrenheit to degrees Celsius to obtain the target natural language message "the current temperature is 21 ° C”, and then transmits this message to the bidirectional interface IF-NLX 60 in charge of the weather station 6.
• step 510 the bidirectional interface IF-NLX 60 of the weather station 6 transmits this target natural language message to the NLXS 50 language exchange unit. natural for delivery to the email address heather@heatheraddress.com (email address assigned to the boiler)
• step 512 the NLXS unit 50 receives the target natural language message and retransmits it to the bidirectional interface IF-NLX 60 in charge of the boiler. It transmits it, in step 514, LUTA unit 58 in charge of the boiler.
• the LUTA unit 58 transmits the target natural language message "the current temperature is 21 ° C" without modification to the LARC unit 56.
• step 518 said LARC unit 56 performs an ambiguity analysis of the received message.
• the LARC unit 56 judges that the message received in the target natural language is unambiguous and consistent, it transmits it without modification to the NLAC unit 54 in charge of the boiler.
• the NLAC unit 54 in charge of the boiler 400 converts the target natural language response "the current temperature is 21 ° C" to the boiler's built-in language, in this case the response to the command.
• body”: [ ⁇ "beg_time”.-123456500, "value”: [21.0] ⁇ ] ⁇ and transmits the converted response to the adaptation unit of media and protocol MPA-0 52 in charge of the boiler.
• step 522 the MPA-0 unit 52 transmits this message to the boiler using the protocols and media used by the boiler 400.
• FIG. 10A illustrates the essential steps of the processes applied by the LUTA unit 58 to a message transmitted in natural language by a remote source to a recipient via the IF-NLX unit 60 in charge of the source.
• step 598 the message from the remote source is transmitted in natural language to the LUTA unit 58 via the IF-NLX unit 60.
• step 600 the LUTA unit 58 converts the natural language of the remote source to the selected target natural language.
• step 602 the LUTA unit 58 aligns the units used by the remote source with those used by the recipient.
• step 606 the LUTA 58 transmits the message processed by steps 598-604 to the recipient's LARC 56.
• FIG. 10B illustrates the essential steps of the processes applied by the LUTA unit 58 to the target natural language message transmitted from a local source to a recipient.
• step 610 the target natural language message is transmitted to the LUTA unit 58 via the LARC unit 56 in charge of the local connected object.
• step 612 LUTA 58 aligns the date, time, and duration references used in the message with those used by the remote party.
• step 614 the LUTA unit 58 aligns the units used in the message with those used by the remote party.
• step 616 the LUTA unit 58 converts the target natural language message to the natural language used by the remote party.
• step 620 the LUTA unit 58 transmits the natural language message used by the remote party to the IF-NLX unit 60.
• Fig. 11 is a detailed flowchart of step 600 of converting natural language from the remote source to the selected target natural language.
• the recipient's LUTA unit 58 Upon receiving the natural language message transmitted by the remote source, in step 700, the recipient's LUTA unit 58 examines the message text to determine the natural language of the remote source.
• the recipient's LUTA unit 58 checks whether the recognized language is the same as the previously selected target natural language.
• step 704 the LUTA unit 58 in charge of the recipient 6 checks whether it is possible to locally, automatically, convert the natural language message from the remote source to the target natural language.
• step 706 the LUTA unit 58 in charge of the recipient performs the conversion.
• the processing of FIG. 10A then continues from step 602.
• step 708 the recipient's LUTA unit 58 checks whether the conversion can be delegated to a remote translation server.
• step 710 the remote translation server performs the conversion.
• the processing of FIG. 10A then continues from step 602
• step 712 the LUTA 58 in charge of the recipient 6 generates a failure message and transmits this message to the remote source, to the control unit 40, and to the management unit 42.
• step 714 the LUTA unit 58 checks whether the language the remote source is indicated in its registration file on platform 1.
• step 716 the LUTA 58 in charge of the recipient 6 checks whether the natural language of the remote source is indicated in an external directory.
• step 718 the LUTA unit 58 in charge of the recipient 6 checks whether the natural language of the remote source 2 could be learned by examining the previous messages.
• step 712 the LUTA 58 in charge of the recipient generates a failure message and transmits this message to the remote source, to the control unit 40, and to the management unit 42.
• Figure 12 is a detailed flowchart of step 602 of Figure 10 for aligning units used by the remote source with those used by the recipient.
• step 720 the recipient's LUTA unit 58 checks whether the length, area, and volume units present in the message received from the remote user are identical to the units used by the local user receiving the message. .
• the recipient's LUTA unit 58 converts the length, area, and volume units of the received message into units of length used by the recipient's local user of the message.
• step 724 the recipient LUTA 58 unit checks whether the mass and weight units are identical to the units used by the local user receiving the message.
• the recipient's LUTA 58 unit converts the mass and weight units of the received message into units used by the local user receiving the message. .
• LUTA 58 in charge of the recipient checks if the temperature units are identical to the units used by the local user receiving the message.
• the recipient's LUTA 58 unit converts the temperature units of the received message into temperature units used by the receiver. local user receiving the message.
• the recipient LUTA 58 unit checks whether the date, time, and duration units are the same as the units used by the local user receiving the message. If the date, time, and duration units are not aligned, in step 734, the recipient LUTA 58 transforms the date, time, and duration units into units used by the recipient. local user receiving the message.
• step 736 the procedure for aligning the natural language of the remote source to the selected target natural language continues from step 604 of the Figure 10A.
• Fig. 13 is a detailed flowchart of step 604 for aligning the date, time, and duration references used by the remote source with those used by a connected object or a digital service.
• step 740 the LUTA 58 in charge of the recipient 6 checks whether the date references used by the connected object or the digital service providing the message are identical to the references used by the local user receiving the message.
• step 742 the recipient's LUTA 58 in charge of the recipient transforms the received date references into date references used by the local user receiving the message.
• step 744 the recipient's LUTA unit 58 checks whether the time references used by the connected object or the digital service are aligned with that of the local user receiving the message.
• the recipient's LUTA unit 58 transforms the received time references into time references used by the receiving local user of the message.
• step 748 the recipient LUTA 58 unit checks whether the duration references are identical to the references used by the local user receiving the message.
• the recipient's LUTA unit 58 transforms the duration references of the received message into time references used by the local user receiving the message.
• the recipient's LUTA unit 58 transmits the message to the LARC unit 56 installed in the receiver of the message receiver to analyze the ambiguity of the received information.
• Fig. 14 is a detailed flowchart of step 612 for aligning the date, time, and duration references used by a local source sending a target natural language message with those used by the recipient.
• step 760 the source LUTA unit 58 checks whether the date references used by the recipient user of the received message are identical to the references used by the local source.
• step 762 the source LUTA 58 in charge of the source transforms the date references of the message into date references used by the recipient.
• step 764 the source LUTA 58 in charge of the source checks whether the time references are identical to the time references used by the remote source.
• step 766 the source LUTA 58 in charge of the source transforms the message's clock references into time references used by the recipient.
• step 768 the source LUTA 58 in charge of the source checks whether the message duration references are identical to the duration references used by the recipient.
• step 770 the LUTA 58 in charge of the source transforms the message duration references into time references used by the recipient.
• step 772 the source-supporting LUTA 58 transmits the target NAT message from the recipient to the function for performing alignment to the recipient's preferred units.
• Fig. 15 is a detailed flowchart of step 614 of aligning the units used by a local source, transmitting a target natural language message, with those used by the recipient.
• step 780 the LUTA unit 58 in charge of the local source checks whether the units of length, area and volume are identical to the units used by the recipient of the message. Otherwise, in step 782, the local source LUTA 58 transforms the length, area, and volume units of the message into a length unit used by the destination user.
• step 784 the LUTA unit 58 in charge of the local source checks whether the mass and weight units are identical to the units used by the user receiving the message.
• step 786 the LUTA unit 58 in charge of the local source transforms the mass and weight units of the message into units used by the recipient user of the message.
• step 788 the LUTA unit 58 in charge of the local source checks whether the temperature units are identical to those used by the user receiving the message.
• step 790 the LUTA unit 58 in charge of the local source transforms the temperature units of the message into units used by the recipient 6.
• step 792 the local source LUTA 58 checks whether the date, time, and duration units are the same as those used by the recipient user of the message.
• the local source LUTA 58 converts the date, time, and duration units of the message into units used by the message recipient user.
• the local source LUTA unit 58 transmits the received target natural language message to the function for performing alignment to the remote user's natural language.
• Fig. 16 is a detailed flowchart of step 616 of source alignment of the target natural language to the natural language of the remote user.
• step 800 the LUTA unit 58 in charge of the local source checks whether the natural language of the remote user is indicated in his registration file on the platform 1.
• step 802 the local source LUTA 58 checks whether the natural language of the indicated remote user is identical to the target natural language. Otherwise, in step 804, the LUTA unit 58 in charge of the local source checks whether a local automatic conversion to the remote user's language is possible.
• step 806 the local source LUTA unit 58 performs the local automatic translation of the target natural language to the remote user's language and transmits, in step 808, the natural language message. the remote user to the IF-NLX module 60 of this remote user.
• step 814 the LUTA unit 58 in charge of the local source checks whether the natural language of this user remote is indicated in an external directory.
• the LUTA unit 58 in charge of the local source transmits, in step 816, the target natural language message to the IF-NLX module 60 in charge of the local source for transmission to the remote user.
• the messages in a target natural language exchanged between the bidirectional interfaces IF-NLX 60 implemented respectively on the side of a source and the side of a recipient may include grammatical or syntactic ambiguities. These messages are transmitted to the LARC ambiguity and relevance control and resolution units 56 respectively from the LUTA bidirectional units 58 and from the NLAC language conversion units 54 respectively installed on the source side and the recipient side to determine the level of ambiguity of the messages exchanged and to ensure that the NLAC 54 units will be able to correctly perform the desired language conversion.
• FIG. 17 represents a detailed view of an LARC 56 ambiguity and relevance resolution unit. It comprises a transmission block 820, a resolution block 822 and a reception block 824.
• the transmission block 820 comprises a first multiplexer 826 intended to keep a copy of the messages sent by the local user and a second multiplexer 828 for transmitting messages to the remote user through the LUTA module 58.
• the resolution block 822 includes a grammatical ambiguity resolution module 830, an inconsistency resolution module 832, a resolution message response module 834, and a user assistance module 836.
• the reception block 824 comprises a message parsing module 840, an ambiguities resolution message intercepting module, confirmations and inconsistencies 842, a user assistance request message interception module 844. , and a message coherence analysis module 846.
• FIG. 18 is a flowchart of the steps of controlling, by the LARC unit 56, ambiguity and relevance of a target natural language message from a remote user, and received from a bidirectional LUTA unit. 58 in charge of the recipient.
• step 850 the message grammar parsing module 840 of the LARC unit 56 in charge of the recipient checks whether the received message is sufficiently compliant with the grammar (lexicon, syntax, etc.) of the target natural language.
• the module 840 transmits the message to the grammatical ambiguity resolution module 830 which generates a grammar ambiguity request message in the target natural language and transmits it. to the remote user through the bidirectional unit LUTA 58 in charge of the recipient.
• step 854 the module for intercepting the messages for resolving ambiguities, confirmations and inconsistencies 842 checks whether the message received is a request message for resolving grammatical ambiguities, confirmations or inconsistencies.
• the module 842 transmits the message to the resolution message response module 834 which generates a response message to the request for resolution of grammatical ambiguity in the target natural language and transmits it to the remote user through the LUTA unit 58.
• a user assistance request message interception module 844 checks whether the message is a support request from the remote user.
• the module 844 transmits the message to the user assistance module 836 which generates a response message to the assistance request. in the target natural language and transmits it to the remote user through the LUTA unit 58.
• the message coherence analysis module 846 checks whether the received message is consistent with the nature and capabilities of the connected local user, object, or service.
• the message is sufficiently coherent, it is transmitted to the NLAC 54 language conversion unit.
• the module 846 transmits the message to the inconsistency resolution module 832 which generates a request message for resolving confirmations and inconsistencies and transmits the message to the remote user through the LUTA module 58.
• the natural language messages exchanged between a source 2 and a recipient 6 transit via the NLAC language conversion units 54 which are responsible for performing the transformation between on one side the target natural language information to a constructed language used by a user. connected object or a digital service and on the other the messages in constructed language (digital format for managing connected objects or digital format for piloting digital services) in target natural language.
• Figures 19 and 20 illustrate the steps to perform these transformations respectively in the first case and in the second case.
• the NLAC unit 54 upon receipt of a target natural language message transmitted to a connected object or digital service by a remote user, stores the message received at step 870 to improve the elaboration of the possible target natural language response.
• step 872 the natural language used in the stored message is converted to the constructed language of the connected object or service. A check of this conversion is performed at step 874.
• step 876 the NLAC unit 54 transmits the constructed language message of the connected object or service to the supported media adaptation and protocol adaptation module MPA-0. connected object or digital service.
• step 878 the NLAC unit 54 transmits a circumstantial error message to the target natural language remote user through the LARC module 56, and to the CTRL 40 and management control units 42.
• the NLAC 54 in charge of the remote user upon receipt of a constructed language message transmitted by a connected object or digital service, at step 880, the NLAC 54 in charge of the remote user checks whether the received message is an error message or not.
• said NLAC unit 54 issues a circumstantial error message to the target natural language remote user through the LARC unit 56, and to the CTRL 40 and management 42 control units.
• step 884 the NLAC unit 54 converts the received message into the constructed language into the target natural language. A check of this conversion is performed at step 886.
• step 888 the NLAC module 54 transmits the target natural language message to the recipient user through the LARC module 56.
• the NLAC unit 54 transmits a target natural language error message to the remote user through the LARC module 56 as well as to the CTRL 40 and management control units 42.
• the resolution of ambiguities is done according to a strategy of which depends on the level of problem. Thus, it can consist in asking the remote user to:
• the units for controlling and resolving the ambiguity and relevance of the exchanged information are configured to use sufficiently diverse natural language expressions to not tire a human user. These expressions will also be simple enough to be understood by both a remote user of human type as well as the interception modules of ambiguities resolution messages, confirmations and inconsistencies 842 equipping LARC units connected objects and services.
• the strategy for resolving ambiguities can evolve either if the previous strategy did not provide a satisfactory solution or to avoid boring a human distant user
• the ambiguity resolution function may declare the abandonment of the transaction by signaling it to the remote user as well as to the CTRL 40 and management control units 42.
• All or part of the data (steps, messages, strategies, etc.) used and generated by the ambiguity resolution function are stored to be used later, in particular by the Management Unit Improvement Function 42.
• the response to ambiguity resolution messages, confirmations and inconsistencies is activated by the function of intercepting ambiguity messages, confirmations and inconsistencies of the reception block, for example when receiving a message. a request for repetition, confirmation, etc. It also has a copy of the original message that has been sent from the transmit block and that seeks to eliminate ambiguities or inconsistencies.
• the answer function will consist, for example, in:
• the response function to the resolution messages may change if it finds that the previous attitude has not brought a satisfactory solution or to avoid boring a human remote user.
• the resolution message response function may declare the abandonment of the transaction by signaling it to the remote user as well as the CTRL 40 and management control units 42.
• All or some of the data (steps, messages, attitudes, etc.) used and generated by the resolution message response function are stored for later use, in particular by the management unit of the management unit improvements. . User assistance.
• the user assistance function is activated by the interception function of the assistance request messages from the reception block.
• These requests for assistance can be of various kinds, for example:
• the user assistance interface 836 receives and processes support requests according to their nature. It responds in natural language, possibly adding additional data (detailed documentation files, web links to tutorials, etc.).
• Figure 21 schematically illustrates an exchange related to a request for assistance between two communicating objects, a boiler and a weather station.
• the target natural language selected is English.
• the exchanges are between the receiving blocks 824 equipping the respective LARC units 56 of each connected object.
• the boiler sends the target language message to the weather station "Can you tell me what are your capacities? ".
• the weather station On receipt of this message via its LARC unit 56, the weather station generates, for example, automatically the message in natural language target "the m able to measure the current temperature and humidity "and returns it to the boiler via the LARC 56 unit of the latter.
• the invention thus takes into account the constraints related to the environment of each type of communication and exploits the fact that the natural language is the most adapted to convey rich information (pure data, contextual data, emotions, etc.) at the price of a certain ambiguity.
• Connected objects and digital services are configured to accept lexical and syntactic variations of messages, and to exchange between supporting ambiguity tolerance in order to simplify and expand their communication capability.
• the invention thus takes advantage of the relative simplicity of communicating objects and digital services to move the constraint from humans to objects and services by means of natural language processing (NLP) insofar as these objects and communicating services most often perform a limited number of simple tasks (or at least specialized enough to be expressed simply). This is exploited by the invention to perform natural language comprehension functions restricted to the missions assigned to these objects and services. We thus realize the displacement of the constraint from the human persons (who must adapt to the artificial languages of the objects and services) towards the objects and services (which must adapt to the natural language of the humans).
• NLP natural language processing
• FIG. 22 schematically represents an embodiment of the architecture of a communication system between a plurality of objects or services. connected 4, 6, 30 each having a clean built language and being able to be source or recipient of information exchanged via an intelligent platform 1..
• This system comprises a connected gateway 900 connected, on the one hand, to a network 902 dedicated to the connected objects 4, 6, 30, and on the other hand, to the distributed data processing units 85 via the units. software and / or hardware for media adaptation and protocol 52.
• the connected gateway 900 has a clean built language and is capable of being source or recipient of the information exchanged and is intended to ensure at least one of the following functions:
• the media and protocol adaptation units 52 implement the communication protocols supported by the gateway 900, and the language conversion units 54 then support the built languages specific to the gateway 900 and ensure the conversion of these clean languages from / to the target natural language used within platform 1.

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• 2016
  • 2016-04-29 FR FR1653900A patent/FR3050843B1/fr active Active
• 2017
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