EP2691885A1 - Architecture de compréhension conversationnelle augmentée - Google Patents

Architecture de compréhension conversationnelle augmentée

Info

Publication number
EP2691885A1
EP2691885A1 EP20120763913 EP12763913A EP2691885A1 EP 2691885 A1 EP2691885 A1 EP 2691885A1 EP 20120763913 EP20120763913 EP 20120763913 EP 12763913 A EP12763913 A EP 12763913A EP 2691885 A1 EP2691885 A1 EP 2691885A1
Authority
EP
European Patent Office
Prior art keywords
user
action
natural language
search
language phrase
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP20120763913
Other languages
German (de)
English (en)
Other versions
EP2691885A4 (fr
Inventor
Larry Paul Heck
Madhusudan Chinthakunta
David Mitby
Lisa Stifelman
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Microsoft Technology Licensing LLC
Original Assignee
Microsoft Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US13/076,862 external-priority patent/US9760566B2/en
Priority claimed from US13/077,431 external-priority patent/US10642934B2/en
Priority claimed from US13/077,368 external-priority patent/US9298287B2/en
Priority claimed from US13/077,303 external-priority patent/US9858343B2/en
Priority claimed from US13/077,233 external-priority patent/US20120253789A1/en
Priority claimed from US13/077,396 external-priority patent/US9842168B2/en
Priority claimed from US13/077,455 external-priority patent/US9244984B2/en
Application filed by Microsoft Corp filed Critical Microsoft Corp
Publication of EP2691885A1 publication Critical patent/EP2691885A1/fr
Publication of EP2691885A4 publication Critical patent/EP2691885A4/fr
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • 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
    • G06F16/332—Query formulation
    • G06F16/3329—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90332—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/26—Speech to text systems

Definitions

  • An augmented conversational understanding architecture may provide a mechanism for facilitating natural language understanding of user queries and conversations.
  • personal assistant programs and/or search engines often require specialized formatting and syntax. For example, a user's query of "I want to go see 'Inception' around 7" may be ineffective at communicating the user's true intentions when provided to a conventional system.
  • Such systems may generally be incapable of deriving the context that the user is referring to a movie, and that the user desires results informing them of local theatres showing that movie around 7:00.
  • An augmented conversational understanding architecture may be provided. Upon receiving a natural language phrase from a user, the phrase may be translated into a search phrase and a search action may be performed on the search phrase.
  • FIG. 1 is a block diagram of an operating environment
  • FIGs. 2A-2B are block diagrams illustrating an interface for providing an augmented conversational understanding architecture
  • FIG. 3 is a block diagram illustrating an interface for providing feedback to an augmented conversational understanding architecture
  • FIG. 4 is a flow chart of a method for providing an augmented
  • FIG. 5 is a block diagram of a system including a computing device.
  • An augmented conversational understanding architecture may facilitate natural language understanding of user queries and conversations.
  • the architecture may allow for determining the context of the query and for inferring the user's intentions.
  • the architecture may use the words of the natural language query to determine the context of the conversation, to estimate the user intents, and to form appropriate additional queries using a suitable search agent.
  • Spoken dialog systems enable people to interact with computers with their voice.
  • the primary component that drives the SDS may comprise a dialog manager: this component manages the dialog-based conversation with the user.
  • the dialog manager may determine the intention of the user through a combination of multiple sources of input, such as speech recognition and natural language understanding component outputs, context from the prior dialog turns, user context, and/or results returned from a knowledge base (e.g., search engine). After determining the intention, the dialog manager may take an action, such as displaying the final results to the user and/or continuing in a dialog with the user to satisfy their intent.
  • FIG. 1 is a block diagram of an operating environment 100 comprising a server 105.
  • Server 105 may comprise assorted computing resources and/or software modules such as a spoken dialog system (SDS) 110 comprising a dialog manager 1 11, a personal assistant program 112, a context database 1 16, and/or a search agent 118.
  • SDS 1 10 may receive queries and/or action requests from users over network 120. Such queries may be transmitted, for example, from a user device 130 such as a computer and/or cellular phone.
  • Network 120 may comprise, for example, a private network, a cellular data network, and/or a public network such as the Internet.
  • FIG. 2 A is a block diagram of an interface 200 for providing an augmented conversational understanding architecture.
  • Interface 200 may comprise a user input panel 210 and a personal assistant panel 220.
  • User input panel 210 may display translated user queries and/or action request such as a user statement 230.
  • User statement 230 may comprise, for example, a result from a speech-to-text conversion received from a user of user device 130.
  • Personal assistant panel 220 may comprise a plurality of action suggestions 240(A)-(C) derived from a context state associated with the user and user statement 230.
  • FIG. 2B is a further illustration of interface 200 comprising an updated display after a user selects one of plurality of action suggestions 240(A).
  • plurality of action suggestions 240(A)-(C) may comprise suggested activities in response to a user's expressed intent to "go out tonight."
  • personal assistant panel 220 may be updated with a second plurality of action suggestions 250(A)-(C) associated with further defining the user's intent.
  • second plurality of action suggestions 250(A)-(C) may comprise different suggested cuisines that the user may want to eat.
  • a context state associated with the user may be used to provide and/or order second plurality of action suggestions 250(A)- (C).
  • the context state may comprise a history of previous restaurants visited and/or liked by the user, and the types of cuisine may be ordered according to those preferences.
  • FIG. 3 is a block diagram of interface 200 illustrating the provision of feedback to an augmented conversational understanding architecture.
  • the user may change all and/or a portion of user statement 230 into a modified user statement 310.
  • the user may use a mouse, stylus, keyboard, voice command, and/or other input mechanism to select the previously translated word "out” and modify that word to "outside.”
  • Personal assistant panel 220 may then be updated with an updated plurality of suggested actions 320(A)-(B) according to modified user statement 310.
  • FIG. 4 is a flow chart setting forth the general stages involved in a method 400 consistent with an embodiment of the invention for providing an augmented conversational understanding architecture.
  • Method 400 may be implemented using a computing device 400 as described in more detail below with respect to FIG. 4. Ways to implement the stages of method 400 will be described in greater detail below.
  • Method 400 may begin at starting block 405 and proceed to stage 410 where computing device 500 may receive an action request.
  • SDS 110 may receive a request from user device 130 comprising a user's spoken query to "find a place to eat.”
  • Method 400 may then advance to stage 415 where computing device 500 may gather a context state associated with the user.
  • the context state may comprise, for example, a role associated with the user, at least one previous user objective, at least one previous user action request, a location of the user, a time, a date, a category associated with the first action request from the user, a data type associated with the first action request from the user, and/or a data category associated with previous user action requests.
  • Such information may be stored in context database 1 16 of SDS 110.
  • Method 400 may then advance to stage 420 where computing device 500 may create a plurality of objectives according to the context state. For example, SDS may identify "dining" as a domain associated with the query "find a place to eat.” Objectives such as finding a nearby restaurant according to the user's location and/or creating reservations according to a number of users involved in a conversation may thus be generated.
  • Method 400 may then advance to stage 425 where computing device 500 may execute the requested action according to the context state. For example, in response to the user query "find a place to eat", translator module 1 14 may command search agent 118 to search for nearby restaurants to the user. The results of this search my be transmitted back to user device 130 by personal assistant program 112 and displayed, for example, in personal assistant panel 220 of interface 200.
  • Method 400 may then advance to stage 430 where computing device 500 may update the context state.
  • the current selection of choices comprising plurality of action suggestions 240(A)-(C) may each be associated with a predicted probability in the user's context state.
  • the user's next action may be used to adjust these predicted probabilities for application to future queries.
  • Method 400 may then advance to stage 435 where computing device 500 may determine whether the next requested action is associated with accomplishing the current objective. For example, SDS 1 10 may compare the user's context state to a plurality of user context states each associated with the current objective. Previous users who issued the same action/query request may have taken similar next actions, and a different action by the user at this stage may indicate that an incorrect objective has been predicted. If the user's next action does not comport with the predicted objective, method 400 may return to stage 420 where a new set of objectives may be generated.
  • method 400 may advance to stage 440 where computing device 500 may determine if the predicted objective is completed. For example, if SDS 1 10 receives a requested action to finalize a dinner reservation and arrange a taxi, the objective of making dinner plans may be determined to be complete and method 400 may end at stage 442. If the action comprises selecting a restaurant to make reservations at, but a time has not been selected, the predicted objective may be determined not to be complete.
  • method 400 may then advance to stage 445 where computing device 500 may provide a next suggested action. For example, where a restaurant is selected but a time is not, personal assistant program 112 may request a reservation time from the user.
  • Method 400 may then advance to stage 450 where computing device 500 may receive a next action from the user. For example, the user may input a selection of 7:00 for the reservation time and transmit it to SDS 110. Method 400 may then return to stage 425 and execute the next requested action as described above.
  • An embodiment consistent with the invention may comprise a system for providing a context-aware environment.
  • the system may comprise a memory storage and a processing unit coupled to the memory storage.
  • the processing unit may be operative to receive a natural language phrase from a user, translate the natural language phrase into a search phrase, and perform a search action according to the search phrase.
  • the natural language phrase may be received, for example, as a plurality of text words and/or as an audio stream.
  • the search phrase may comprise at least one contextual semantic concept not contained in the natural language phrase.
  • the processing unit may be further operative to receive a plurality of search results according to the search action and provide the plurality of search results to the user.
  • the processing unit may be further operative to provide the plurality of results to a plurality of users.
  • the natural language phrase may be derived, for example, from a conversation among the plurality of users.
  • the processing unit may be further operative to analyze a plurality of application programming interfaces (APIs) and identify at least one required parameter for each of the plurality of APIs.
  • APIs application programming interfaces
  • Each of the plurality of APIs may be associated with a website search function.
  • Being operative to translate the natural language phrase into the search phrase may comprise the processing unit being operative to identify a context associated with the natural language phrase, determine whether at least one of the plurality of APIs is associated with the identified context, and, if so, translate at least one word of the natural language phrase into the at least one required parameter associated with the at least one of the plurality of APIs.
  • Being operative to perform the search action may comprise the processing unit being operative to call the at least one of the plurality of APIs with the at least one required parameter.
  • Another embodiment consistent with the invention may comprise a system for providing a context-aware environment.
  • the system may comprise a memory storage and a processing unit coupled to the memory storage.
  • the processing unit may be operative to receive a natural language phrase from a user, create a context state associated with the natural language phrase, translate the natural language phrase into an executable action, identify a domain associated with the executable action according to the identified context, and performing the executable action within the identified domain.
  • the executable action may comprise, for example, a search action, a data creation action, a data modification action, and a communication action.
  • the processing unit may be further operative to provide at least one suggested next action to the user.
  • the processing unit may be further operative to receive a second natural language phrase from the user, determine whether the second natural language phrase is associated with the at least one suggested next action, and, if so, perform the at least one suggested next action. In response to determining that the second natural language phrase is not associated with the at least one suggested next action, the processing unit may be operative to providing at least one second suggested next action to the user. The processing unit may be further operative to update the context state according to the second natural language phrase.
  • Yet another embodiment consistent with the invention may comprise a system for providing a context-aware environment.
  • the system may comprise a memory storage and a processing unit coupled to the memory storage.
  • the processing unit may be operative to create a plurality of objectives, gather a context state associated with a user, provide a suggested action associated with at least one of the plurality of objectives according to the context state, receive an action request from the user, execute the requested action according to the context state, and determine whether the action is associated with accomplishing the at least one of the plurality of objectives.
  • the processing unit may be operative to update the context state, update a probability associated with the suggested action, and determine whether the context state comprises a completed objective of the plurality of objectives. In response to determining that the context state does not comprise the completed objective, the processing unit may be operative to provide at least one second suggested action.
  • the context state may comprise, for example, a role associated with the user, at least one previous user objective, at least one previous user action request, a location of the user, a time, a date, a category associated with the first action request from the user, a data type associated with the first action request from the user, and a data category associated with previous user action requests.
  • Being operative to determine whether the context state is associated with accomplishing the at least one predicted objective may comprise the processing unit being operative to compare the context state to a plurality of user context states each associated with the at least one of the plurality of objectives.
  • FIG. 5 is a block diagram of a system including computing device 500.
  • the aforementioned memory storage and processing unit may be implemented in a computing device, such as computing device 500 of FIG. 5. Any suitable combination of hardware, software, or firmware may be used to implement the memory storage and processing unit.
  • the memory storage and processing unit may be implemented with computing device 500 or any of other computing devices 518, in combination with computing device 500.
  • the aforementioned system, device, and processors are examples and other systems, devices, and processors may comprise the aforementioned memory storage and processing unit, consistent with embodiments of the invention.
  • computing device 500 may comprise an operating environment for system 100 as described above. System 100 may operate in other environments and is not limited to computing device 500.
  • a system consistent with an embodiment of the invention may include a computing device, such as computing device 500.
  • computing device 500 may include at least one processing unit 502 and a system memory 504.
  • system memory 504 may comprise, but is not limited to, volatile (e.g., random access memory (RAM)), non- volatile (e.g., read-only memory (ROM)), flash memory, or any combination.
  • System memory 504 may include operating system 505, one or more programming modules 506, and may include personal assistant program 112. Operating system 505, for example, may be suitable for controlling computing device 400's operation.
  • embodiments of the invention may be practiced in conjunction with a graphics library, other operating systems, or any other application program and is not limited to any particular application or system. This basic configuration is illustrated in FIG. 5 by those components within a dashed line 508.
  • Computing device 500 may have additional features or functionality.
  • computing device 500 may also include additional data storage devices
  • Computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.
  • System memory 504, removable storage 509, and non-removable storage 510 are all computer storage media examples (i.e., memory storage).
  • Computer storage media may include, but is not limited to, RAM, ROM, electrically erasable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store information and which can be accessed by computing device 500. Any such computer storage media may be part of device 500.
  • Computing device 500 may also have input device(s) 512 such as a keyboard, a mouse, a pen, a sound input device, a touch input device, etc.
  • Output device(s) 514 such as a display, speakers, a printer, etc. may also be included. The aforementioned devices are examples and others may be used.
  • Computing device 500 may also contain a communication connection 516 that may allow device 500 to communicate with other computing devices 518, such as over a network in a distributed computing environment, for example, an intranet or the Internet.
  • Communication connection 516 is one example of communication media.
  • Communication media may typically be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media.
  • modulated data signal may describe a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal.
  • communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.
  • RF radio frequency
  • the term computer readable media as used herein may include both storage media and communication media.
  • programming modules 506 may perform processes including, for example, one or more of method 500's stages as described above.
  • processing unit 502 may perform other processes.
  • Other programming modules that may be used in accordance with
  • embodiments of the present invention may include electronic mail and contacts applications, word processing applications, spreadsheet applications, database
  • program modules may include routines, programs, components, data structures, and other types of structures that may perform particular tasks or that may implement particular abstract data types.
  • embodiments of the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor- based or programmable consumer electronics, minicomputers, mainframe computers, and the like.
  • Embodiments of the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
  • program modules may be located in both local and remote memory storage devices.
  • embodiments of the invention may be practiced in an electrical circuit comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit utilizing a microprocessor, or on a single chip containing electronic elements or microprocessors.
  • Embodiments of the invention may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to mechanical, optical, fluidic, and quantum technologies.
  • embodiments of the invention may be practiced within a general purpose computer or in any other circuits or systems.
  • Embodiments of the invention may be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media.
  • the computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process.
  • the computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.
  • the present invention may be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.).
  • embodiments of the present invention may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system.
  • a computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
  • the computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific computer-readable medium examples (a non-exhaustive list), the computer-readable medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CD-ROM).
  • RAM random access memory
  • ROM read-only memory
  • EPROM or Flash memory erasable programmable read-only memory
  • CD-ROM portable compact disc read-only memory
  • the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

Abstract

L'invention concerne une architecture de compréhension conversationnelle augmentée. Dès réception d'une expression en langage naturel provenant d'un utilisateur, l'expression peut être traduite en expression de recherche et une action de recherche peut être exécutée sur l'expression de recherche.
EP12763913.6A 2011-03-31 2012-03-27 Architecture de compréhension conversationnelle augmentée Ceased EP2691885A4 (fr)

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
US13/076,862 US9760566B2 (en) 2011-03-31 2011-03-31 Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof
US13/077,431 US10642934B2 (en) 2011-03-31 2011-03-31 Augmented conversational understanding architecture
US13/077,368 US9298287B2 (en) 2011-03-31 2011-03-31 Combined activation for natural user interface systems
US13/077,303 US9858343B2 (en) 2011-03-31 2011-03-31 Personalization of queries, conversations, and searches
US13/077,233 US20120253789A1 (en) 2011-03-31 2011-03-31 Conversational Dialog Learning and Correction
US13/077,396 US9842168B2 (en) 2011-03-31 2011-03-31 Task driven user intents
US13/077,455 US9244984B2 (en) 2011-03-31 2011-03-31 Location based conversational understanding
PCT/US2012/030751 WO2012135226A1 (fr) 2011-03-31 2012-03-27 Architecture de compréhension conversationnelle augmentée

Publications (2)

Publication Number Publication Date
EP2691885A1 true EP2691885A1 (fr) 2014-02-05
EP2691885A4 EP2691885A4 (fr) 2015-09-30

Family

ID=46931884

Family Applications (6)

Application Number Title Priority Date Filing Date
EP12765896.1A Withdrawn EP2691877A4 (fr) 2011-03-31 2012-03-27 Apprentissage et correction d'un dialogue conversationnel
EP12764494.6A Ceased EP2691870A4 (fr) 2011-03-31 2012-03-27 Intentions d'utilisateurs orientées sur les tâches
EP12763913.6A Ceased EP2691885A4 (fr) 2011-03-31 2012-03-27 Architecture de compréhension conversationnelle augmentée
EP12763866.6A Ceased EP2691949A4 (fr) 2011-03-31 2012-03-27 Compréhension conversationnelle basée sur l'emplacement
EP12765100.8A Ceased EP2691876A4 (fr) 2011-03-31 2012-03-30 Personnalisation de requêtes, de conversations et de recherches
EP12764853.3A Ceased EP2691875A4 (fr) 2011-03-31 2012-03-30 Agent augmenté de compréhension de la conversation

Family Applications Before (2)

Application Number Title Priority Date Filing Date
EP12765896.1A Withdrawn EP2691877A4 (fr) 2011-03-31 2012-03-27 Apprentissage et correction d'un dialogue conversationnel
EP12764494.6A Ceased EP2691870A4 (fr) 2011-03-31 2012-03-27 Intentions d'utilisateurs orientées sur les tâches

Family Applications After (3)

Application Number Title Priority Date Filing Date
EP12763866.6A Ceased EP2691949A4 (fr) 2011-03-31 2012-03-27 Compréhension conversationnelle basée sur l'emplacement
EP12765100.8A Ceased EP2691876A4 (fr) 2011-03-31 2012-03-30 Personnalisation de requêtes, de conversations et de recherches
EP12764853.3A Ceased EP2691875A4 (fr) 2011-03-31 2012-03-30 Agent augmenté de compréhension de la conversation

Country Status (5)

Country Link
EP (6) EP2691877A4 (fr)
JP (4) JP2014512046A (fr)
KR (3) KR20140014200A (fr)
CN (8) CN102737096B (fr)
WO (7) WO2012135210A2 (fr)

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