WO2006129967A1 - Conversation system and method using conversational agent - Google Patents

Conversation system and method using conversational agent Download PDF

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Publication number
WO2006129967A1
WO2006129967A1 PCT/KR2006/002095 KR2006002095W WO2006129967A1 WO 2006129967 A1 WO2006129967 A1 WO 2006129967A1 KR 2006002095 W KR2006002095 W KR 2006002095W WO 2006129967 A1 WO2006129967 A1 WO 2006129967A1
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WO
WIPO (PCT)
Prior art keywords
conversation
question
conversational agent
transmitting
db
Prior art date
Application number
PCT/KR2006/002095
Other languages
French (fr)
Inventor
Kyeongseo Kim
Original Assignee
Daumsoft, Inc.
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 to KR10-2005-0045785 priority Critical
Priority to KR1020050045786A priority patent/KR20060117860A/en
Priority to KR1020050045793A priority patent/KR20060117861A/en
Priority to KR1020050045778A priority patent/KR20060113311A/en
Priority to KR10-2005-0045793 priority
Priority to KR1020050045785A priority patent/KR20060117859A/en
Priority to KR10-2005-0045786 priority
Priority to KR10-2005-0045778 priority
Priority to KR10-2005-0045841 priority
Priority to KR10-2005-0045840 priority
Priority to KR1020050045841A priority patent/KR20060113316A/en
Priority to KR10-2005-0045842 priority
Priority to KR1020050045842A priority patent/KR20060117862A/en
Priority to KR1020050045840A priority patent/KR20060113315A/en
Application filed by Daumsoft, Inc. filed Critical Daumsoft, Inc.
Publication of WO2006129967A1 publication Critical patent/WO2006129967A1/en

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Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • G06F17/28Processing or translating of natural language
    • G06F17/289Use of machine translation, e.g. multi-lingual retrieval, server side translation for client devices, real-time translation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33Querying
    • G06F16/332Query formulation
    • G06F16/3329Natural language query formulation or dialogue systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33Querying
    • G06F16/3331Query processing
    • G06F16/334Query execution
    • G06F16/3344Query execution using natural language analysis

Abstract

The present invention discloses a conversation system using a conversational agent which includes: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, and a conversation method using the same.

Description

Description

CONVERSATION SYSTEM AND METHOD USING CONVERSATIONAL AGENT

Technical Field

[1] The present invention relates to a conversation method and system using a conversational agent, and more particularly, to a conversation method and system using a conversational agent which provide various services by combining the conversational agent with a messenger, translation, short message, conversation pack, cartoon, image and advertisement. Background Art

[2] A conversational agent is a chatting robot which is a software agent having a conversation with a human user. It is called a chatterbot, chatbot or chatterbox (refer to the encyclopedia Wikipedia http://en.wikipedia.org/wiki/Chatterbot).

[3] Fig. 1 shows one example of a conventional conversational agent, Alice provided on the website www.alicebot.org by A.L.I.C.E Artificial Intelligence Foundation. The conversational agent Alice gives a preset answer to a question "What is a chatterbot?".

[4] Fig. 2 shows another example of the conventional conversational agent. The conversational agent Lingubot provided on the website www.elbot.com by kiwilogic.com presents a subject and leads a conversation.

[5] Fig. 3 shows yet another example of the conventional conversational agent. A user chats with the conversational agent (E-mail address: simsimi200@hotmail.com) on an msn messenger. This service is provided on the website www.simsimi.com by Ismaker.

[6] In addition, users can chat with various conversational agents through www.personalityforge.com and chat with a conversational agent Ella through www.ellaz.com. That is, various conversational agent services are provided on the web.

[7] Such a conversational agent service performs chatting between the user and the conversational agent, namely, the chatting robot, not between the users. Normally, the chatting robot accumulates expected pairs of questions and answers in advance (by pattern matching), and gives answers to questions of the user. For example, when the user asks "Did you have a meal?" the conversational agent takes an appropriate natural language processing procedure, finds an answer "Not yet" in a conversation DB for storing the pairs of questions and answers, and gives the answer to the user, thereby having a chat with the user. Disclosure of Invention Technical Problem

[8] An object of the present invention is to provide a communication method and system on a PC using a conversational agent which perform chatting even when a user does not sit in front of the PC, by applying a conversational agent service to a new area.

[9] Another object of the present invention is to provide a translation method and system for a real time conversation of different languages which achieve chatting between a user and a conversational agent, even when pairs of questions and answers have not been made in a language used by the user.

[10] Yet another object of the present invention is to provide a translation method and system for a real time conversation of different languages which can give an answer made in a language of preset pairs of questions and answers to a question made in a language different from the language.

[11] Yet another object of the present invention is to provide a base for expanding a conversational agent service to various services by combining the conversational agent service with communication technologies, by performing the conversational agent service between a cellular phone and a conversational agent.

[12] Yet another object of the present invention is to develop a general agent to a customized intelligence type by endowing conversation functions to the agent and expanding conversation knowledge of the agent by a user. The developed agent does not take an assistance role of another service, but has a chat as a substitute for the user or speaks to itself as a substitute for a bulletin board.

[13] Also, service providers can create a new profitable model by selling a conversation

DB and a conversation data editing function on the basis of the attractive agent service.

[14] Yet another object of the present invention is to provide a method and system for selling conversation data (conversation pack) prepared (taught) by a user (education).

[15] Yet another object of the present invention is to provide a method and system for providing a conversational agent service by using a cartoon which can present a conversation between a visitor and a conversational agent in the form of cartoon.

[16] Yet another object of the present invention is to provide a method and system for providing a conversational agent service by using a cartoon which can present a conversation between a visitor and a conversational agent at the same time.

[17] Yet another object of the present invention is to provide a method and system for providing a conversational agent service by using an image which can give a text and an image as an answer to a question of a visitor.

[18] Yet another object of the present invention is to provide a method and system for providing a conversational agent service by using an image which can expand limited pairs of questions and answers by enabling a conversational agent user to directly set up answers (texts and images) to questions. [19] Yet another object of the present invention is to provide a system and method for presenting an advertisement by obtaining an advertisement effect equivalent to an effect of word transmission which is the most effective advertisement method and minimizing rejection of a user to the advertisement, by mentioning an advertisement relating to a current conversation between the user and a conversational agent by the conversational agent in a conversational agent service for chatting, a conversation type mini homepage and a messenger service. [20] In order to achieve the above-described objects of the invention, there are provided a conversation method and system using a conversational agent as recited in Claims 1 to 19. [21] In accordance with the present invention, the user can have a conversation with another user during the absence by using the conversational agent. [22] In accordance with the present invention, the user can check the conversation between the conversational agent and another user and utilize the conversation in future communication with another user. [23] In accordance with the present invention, even if the language used by the user and the language used in the conversation DB are different, the user can use the conversational agent service. [24] In accordance with the present invention, even if the pairs of questions and answers have not been made in the language used by the user, the user and the conversational agent can have a conversation with each other. [25] In accordance with the present invention, the conversational agent service is carried out between the cellular phone and the conversational agent, and thus combined with the communication technologies, thereby providing the base for various services. [26] In accordance with the present invention, the conversation elements are added to the agent and developed into the customized intelligence type, so that the user can enjoy conversation and newly exchange opinions with another user of a community. [27] In accordance with the present invention, the service providers can obtain an additional profitable model by forming the sale service model for conversation data and conversation education functions. [28] In accordance with the present invention, the service method can be applied to portable terminals such as cellular phones through wireless internet. [29] In accordance with the present invention, the conversation pack prepared by the user can be sold. [30] In accordance with the present invention, the image can be provided with the text as the answer to the question of the visitor. [31] In accordance with the present invention, the conversational agent user directly sets up the answers (texts and images) to the questions, thereby complementing the limited pairs of questions and answers. Therefore, the pairs of questions and answers can be expanded, and the conversational agent service can be provided in a customized type.

[32] In accordance with the present invention, the advertisement effect can be improved by providing the advertisement information relating to the current conversation between the users. Also, the advertisement information is presented in the form of conversation, thereby obtaining the advertisement effect equivalent to the effect of word transmission which is one of the advertisement techniques, and minimizing a side effect such as rejection of the user. Brief Description of the Drawings

[33] The present invention will become better understood with reference to the accompanying drawings which are given only by way of illustration and thus are not limitative of the present invention, wherein:

[34] Figs. 1 to 3 illustrate examples of a conventional conversational agent service;

[35] Fig. 4 illustrates one example of a system in accordance with the present invention;

[36] Fig. 5 illustrates one example of a conversation between a user of PC 2 and a conversational agent of PC 1;

[37] Fig. 6 illustrates one example of an operation of a conversational agent program in accordance with the present invention;

[38] Fig. 7 illustrates another example of the system in accordance with the present invention;

[39] Fig. 8 illustrates one example of a conversation between a user and a conversational agent in accordance with the present invention;

[40] Fig. 9 illustrates one example of embodiment of a service in accordance with the present invention;

[41] Fig. 10 illustrates one example of a structure of a conversational agent service in accordance with the present invention;

[42] Fig. 11 is a network diagram in accordance with the present invention;

[43] Fig. 12 is a block diagram illustrating a structure of an agent server in accordance with the present invention;

[44] Figs. 13 to 15 are flowcharts showing sequential steps of a conversational agent service method in accordance with the present invention;

[45] Fig. 16 is a flowchart showing a method for buying a new conversation and educating an agent;

[46] Figs. 17 and 18 illustrate examples of web pages created when the conversational agent is used for a community service; [47] Fig. 19 illustrates one example of a user obtaining the right of inputting conversation data and directly inputting the conversation data;

[48] Fig. 20 illustrates examples of predefined conversation data sold to users;

[49] Fig. 21 illustrates one example of a process for selling the conversation data

(conversation pack) of Fig. 20;

[50] Fig. 22 illustrates one example of a conversational agent service in accordance with the present invention;

[51] Fig. 23 illustrates one example of a system in accordance with the present invention;

[52] Fig. 24 illustrates a method for a user setting up cartoon cuts for his/her conversational agent in accordance with the present invention;

[53] Fig. 25 illustrates one example of information contents of the cartoon cut stored in a cartoon DB;

[54] Fig. 26 illustrates another example of the conversational agent service in accordance with the present invention;

[55] Fig. 27 illustrates one example of a conversational agent service server and a conversation cartoon server in accordance with the present invention;

[56] Fig. 28 illustrates one example of a process for storing information of a cartoon cut in a cartoon DB in the conversation cartoon server;

[57] Fig. 29 illustrates one example of a process for processing a conversation between a visitor computer and a conversational agent by the conversational agent service server in accordance with the present invention;

[58] Fig. 30 illustrates one example of the conversational agent service in accordance with the present invention;

[59] Fig. 31 illustrates one example of the system in accordance with the present invention;

[60] Figs. 32 and 33 illustrate one example of a method for a user designating a text and an image as an answer to a question in accordance with the present invention;

[61] Fig. 34 illustrates another example of the system in accordance with the present invention;

[62] Fig. 35 illustrates one example of an operation of a conversational agent service server;

[63] Fig. 36 illustrates one example of presenting a conversation type online advertisement in accordance with the present invention;

[64] Fig. 37 is a table showing advertisement information registration items in accordance with the present invention;

[65] Fig. 38 illustrates an online advertisement system in accordance with the present invention; [66] Fig. 39 is a flowchart showing a process for registering advertisement information in accordance with the present invention; and

[67] Fig. 40 is a flowchart showing a process for presenting advertisement information as an answer to a question of a user. Best Mode for Carrying Out the Invention

[68] A conversation system and method using a conversational agent in accordance with preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[69] Fig. 4 illustrates one example of the system in accordance with the present invention. The system includes a PC 1 on which a conversational agent program has been mounted, a PC 2 of another user, an internet 3 used as a network, a conversational agent service server 4, and a DB 5 for storing pairs of questions and answers.

[70] Basically, a messenger program such as an MSN messenger is mounted on the PC 1 and the PC 2. Therefore, the user of the PC 2 accesses the PC 1 by P2P and chats with the user of the PC 1 by the messenger.

[71] In the conventional art, when the user of the PC 2 intends to have a chat with the user of the PC 1 by the messenger, if the user of the PC 1 is not able to respond to the message from the user of the PC 2 due to the absence, the users cannot chat with each other. In accordance with the present invention, the users can have a chat in the above case.

[72] That is, the conversational agent created by the conversational agent program mounted on the PC 1 converses with the user of the PC 2.

[73] Fig. 5 illustrates one example of a conversation between the user of the PC 2 and the conversational agent of the PC 1. When the user of the PC 2 requests chatting, the conversational agent chats with the user of the PC 2 as a substitute for the user of the PC 1.

[74] When a message is transmitted from the PC 2 to the PC 1, the PC 1 transmits the message to the conversational agent service server 4 through the internet 3, the conversational agent service server 4 finds a response to the message in the conversation DB 5 and transmits the response to the PC 1 , and the PC 1 transmits the response to the PC 2 by the conversational agent. Accordingly, the user of the PC 2 can have a chat with the conversational agent of the PC 1.

[75] Fig. 6 illustrates one example of the operation of the conversational agent program in accordance with the present invention. At the initial stage, the PC 1 checks reception of a message (Sl). After receiving the message, the PC 1 transmits the message to the conversational agent service server 4 (S2), receives a response from the conversational agent service server 4 (S3), and transmits the response to the PC 2 (S4). When the PC 1 receives a new message from the PC 2, the PC 1 repeats the above procedure. If there is no new message, the routine is ended.

[76] The conversational agent service server 4 and the conversation DB 5 are used in the above example. However, if the pairs of questions and answers are simple, the PC 1 can process the above procedure. In addition, a mode for enabling the messenger to use the conversational agent can be formed as a button on the PC 1. If the PC 1 is not used for a predetermined time, the mode can be automatically selected.

[77] The conversation between the conversational agent of the PC 1 and the user of the

PC 2 is stored in a special DB (not shown) connected to the conversational agent service server 4 or the PC 1. The user of the PC 1 can check the conversation for future communication with the user of the PC 2.

[78] Fig. 7 illustrates another example of the system in accordance with the present invention. The system includes a user computer 1, an internet 2 used as a network, a conversational agent service server 3, a translation server 4, and a conversation DB 5 f or storing pairs of questions and answers.

[79] In the conventional art, when the user accesses the conversational agent service server 3 through the internet 2 by using the user computer 1 and transmits a message (or question) on the screen of Fig. 1 or 2, the conversational agent service server 3 finds an appropriate response in the conversation DB 5 and transmits the response to the user computer 1 , thereby performing chatting between the conversational agent and the user. However, if the language used by the user and the language used in the conversation DB 5 are different, the user and the conversational agent cannot have a chat. As shown in Fig. 7, the system of the present invention further includes the translation server 4. Even if the languages of the user and the conversation DB 5 are different, the user and the conversational agent can chat with each other.

[80] Fig. 8 illustrates one example of the conversation between the user and the conversational agent in accordance with the present invention. When the user says "Good morning" in English, the conversational agent service server 3 transmits the message to the translation server 4, and the translation server 4 translates the message into Korean and transmits the translated message to the conversational agent service server 3. The conversational agent service server 3 finds a response "DD(in Fig. 8, for english PCT publication, this Korean greeting word corresponding to Good morning is represented in english character as it sounds "An-nyoung")" to the translated message in the conversation DB 5 and transmits the response to the user computer 1, thereby performing chatting. On the other hand, the conversational agent service server 3 transmits the response "DD" found in the conversation DB 5 to the translation server 4, the translation server 4 translates the response into "Hi" and transmits the translated message to the conversational agent service server 3, and the conversational agent service server 3 transmits the message to the user computer 1, thereby performing chatting between the user and the conversational agent, Which language the conversational agent uses is determined without confusion by mode selection of the user.

[81] Fig. 9 illustrates one example of embodiment of a service in accordance with the present invention. When a user 'Marunal' transmits a short message (SMS) to a conversational agent of 1Mr. Pangto1 by using a cellular phone, a conversational agent service server receives the message, finds an appropriate response in a conversation DB, and transmits the response to the cellular phone of the user.

[82] Fig. 10 illustrates one example of a structure of a conversational agent service in accordance with the present invention. A short message of a cellular phone 1 is transmitted to a conversational agent service server 3 through a mobile communication company 2. The conversational agent service server 3 finds a response in a conversation DB 4 and transmits the response to the cellular phone 1 through the mobile communication company 2.

[83] Fig. 11 is a network diagram in accordance with the present invention. User computers 100 and 200 are connected to an internet to access an agent service providing server 300 or a log-in server 400. In a log-in operation of a conversational agent service provider, the log-in server 400 requests the agent server 500 to extract the agent of the conversational agent service provider. The extracted agent is combined with various community services used by the conversational agent service provider. Accordingly, the service providing server 300 provides various community services in connection with the agent server 500. Also, the conversational agent service provider buys conversation data or conversation input functions for growing the agent through the agent server 500, and educates the agent.

[84] Fig. 12 is a block diagram illustrating the structure of the agent server 500 in accordance with the present invention. The agent server 500 which is a system for generating and managing agents and performing a conversation processing function includes an agent generating module 200, an agent managing module 210, a conversation processing module 220, a conversation educating module 230, a conversation log managing module 240 and a conversation selling module 250. Each module extracts or stores various data from/in an agent DB 260, a common conversation DB 270 and an individual conversation DB 280.

[85] When the conversational agent service provider newly becomes a member, the agent generating module 200 generates an agent. In the newly-generated agent, basic conversation data are individually generated on the basis of the member information of the conversational agent service provider. Therefore, the agent provides the basic information of the conversational agent service provider without special education.

[86] The agent managing module 210 extracts an appropriate agent from the agent DB 260 according to the log-in information, and enables the conversational agent service provider to manage his/her agent. That is, the agent managing module 210 extracts and changes data of the agent DB 260.

[87] The conversation processing module 220 enables the agent to chat with the third party on the basis of the conversation DBs 270 and 280. The conversation processing module 220 processes conversation by using the general conversation information stored in the common conversation DB 270 and the conversation information customized for the conversational agent service provider and stored in the individual conversation DB 280. In regard to the conversation which is not stored in the conversation DBs 270 and 280, the conversation processing module 220 provides a predefined response, thereby continuously performing chatting.

[88] The conversation educating module 230 enables the conversational agent service provider to teach his/her agent. The conversational agent has basic conversation data, and basic customized conversation data generated on the basis of information inputted in member registration. In order to additionally educate the agent, the conversational agent service provider buys predefined conversation data or a use frequency of a function of inputting conversation data, and inputs the conversation. The conversation educating module 230 teaches the bought conversation data to the agent, or allows the user to directly input the conversation data to educate the agent.

[89] The conversation log managing module 240 inquires and manages the conversation contents between the conversational agent and the other users. The conversational agent service provider educates the conversational agent so that the conversational agent can chat with the other users as a substitute. By referring to the conversation log of the conversational agent, the conversational agent service provider checks insufficiency or utilization of the conversation information of the agent and efficiently educates the agent. The conversational agent service provider can efficiently check the level of the agent and the future education point by the function provided by the conversation log managing module 240.

[90] The conversation selling module 250 sells data used to educate the agent by the conversation educating module 230 or the right of inputting data. At first, the conversational agent has basic conversation data, and basic customized conversation data generated on the basis of information inputted in member registration. The conversational agent must learn additional conversation information to be grown to a customized intelligence type. A method for educating an agent is classified into a method for buying and teaching predefined conversation information and a method for educating an agent by inputting conversation data by a user. Accordingly, the conversation selling module 250 sells the predefined conversation data or the right and frequency of inputting the data by the conversational agent service provider. The detailed service functions of the conversation selling module 250 can be diversified according to business models of agent service providers. In case the conversation data and the function of inputting the conversation are provided for nothing, the conversation selling module 250 is not necessary.

[91] Figs. 13 to 15 are flowcharts showing sequential steps of a conversational agent service method in accordance with the present invention.

[92] Fig. 13 is a flowchart showing a method for newly generating an agent and setting up initial conversation data when a conversational agent service provider becomes a member. First, necessary user information for member registration is inputted by the conversational agent service provider through a member joining menu (S301).

[93] To generate the customized agent, the conversational agent service provider is required to select characteristics of the agent and input corresponding information (S302). Here, the characteristics of the agent include a gender, character shape and name.

[94] The initial conversation data of the agent are generated on the basis of the information inputted by the conversational agent service provider in member registration (S303). The generated data include an age, gender, address and phone number of the user. Such data are used for the conversation relating to basic questions about the user, for example, "How old are you?", "Are you a man or woman?" and "Give me a phone number, please". The new agent is generated according to the characteristics selected by the conversational agent service provider and stored in the agent DB 260, and the initial conversation data are stored in the individual conversation DB 280 (S304).

[95] Fig. 14 is a flowchart showing a method for utilizing the conversational agent when the conversational agent service provider logs in and uses a community service. First, the conversational agent service provider logs in to use his/her agent in the community service (S401).

[96] Here, the log-in server 400 requests the agent server 500 to extract the agent information of the conversational agent service provider (S402).

[97] The conversational agent service provider uses the community service (S403). Also, the conversational agent service provider can edit his/her agent with the help of the agent managing module 210. Exemplary community services using the conversational agent include a blog, mini homepage, bulletin board, mail, message and chatting.

[98] Fig. 15 is a flowchart showing a method for using the conversational agent service by the third party. First, the service providing server 300 receives a request for the community service providing the conversational agent service from the user computer 100 or 200 (S501).

[99] At the request of the user computer 100 or 200, the service providing server 300 checks whether the user (or user computer) making a visit request is the conversational agent service provider or the third party with the help of the log-in server 400 (S502). When the user making the visit request is the conversational agent service provider, the service providing server 300 does not provide a chatting mode or provides an editing mode. That is, it is meaningful when the service providing server 300 manages the conversational agent service. On the other hand, the checking step requires the log-in of the visitor. If the user making the visit request does not log in, the service providing server 300 requests the user to log in. If the service providing server 300 provides the conversational agent service without the log-in procedure, the above step S502 is not necessary. Also in this case, the service providing server 300 can request the visitor to log in to utilize the conversation log between the conversational agent and the visitor.

[100] When the user making the visit request is the third party, the service providing server 300 provides the user with the web page including the conversational agent service (S503). As shown in Fig. 17, the conversational agent 1 has a text balloon 2 to express its opinion, and transmits a message of welcoming a visitor through the text balloon 2. Preferably, the conversational agent 1 can transmit a message notifying that it is a conversational agent (not shown). Here, the initial value of the text balloon 2 is determined by the conversational agent service provider or the service providing server 300, and stored in the individual conversation DB 280.

[101] Thereafter, the service providing server 300 receives an input from the visitor through a conversation window 3. When the visitor inputs a message, the service providing server 300 gives a response to the input through the text balloon 2 of the conversational agent 1 with the help of the agent server 500, thereby performing chatting with the visitor (S504).

[102] For example, when the visitor inputs "Age" through the conversation window 3, the service providing server 300 transmits the input to the agent server 500, the agent server 500 finds a response (for example, 30) to the age of the conversational agent service provider in the individual conversation DB 280 and transmits the response to the service providing server 300, and the service providing server 300 provides the response through the text balloon 2.

[103] In addition, when the visitor inputs "What is the conversational agent?" through the conversation window 3, the service providing server 300 transmits the input to the agent server 500, the agent server 500 takes an appropriate natural language processing procedure, finds the explanation of the conversational agent (for example, the conversational agent means a virtual image chatting with you as a substitute of myself) in the common conversation DB 270, and transmits the explanation to the service providing server 300, and the service providing server 300 provides the explanation through the text balloon 2.

[104] Here, the agent server 500 firstly searches the individual conversation DB 280. If the response to the input exists in the individual conversation DB 280, the agent server 500 transmits the response to the service providing server 300. If the response to the input does not exist in the individual conversation DB 280, the agent server 500 searches the common conversation DB 270 for the response and transmits the response to the service providing server 300. It is because the conversational agent service is a customized service. Pursuant to the administration policy of the administrator of the service providing server 300 or selection of the conversational agent service provider, it is possible to search both the common conversation DB 270 and the individual conversation DB 280 and endow priority to any one of the DBs 270 and 280, if both DBs 270 and 280 have the response.

[105] On the other hand, if the response to the input of the visitor does not exist in the common conversation DB 270 and the individual conversation DB 280, the service providing server 300 provides a setup value such as "I don't know", "I'll study more and answer next time", "Another question, please" and "I don't know that word" through the text balloon 2, or provides a value upon the setup rule through the text balloon 2. The conversational agent service provider can check the conversation contents between the visitor and the conversational agent recorded by the following step S505. Therefore, the conversational agent service provider is informed of the question which his/her agent could not answer. The conversational agent service provider wants to answer the question, and thus wants to educate the conversational agent. The service providing server 300 sells the data for education to the conversational agent service provider, or makes the conversational agent service provider stay in the server 300 for the education time, thereby maintaining the conversational agent service.

[106] One of the problems which may occur during the conversation between the visitor and the conversational agent is that the conversational agent does not know whether the input of the visitor is a question or a return question. For example, when the visitor inputs "Age" through the conversation window 3, it is difficult for the conversational agent to know whether this input means a question for the age of the conversational agent service provider or a return question for the age of the visitor in relation to the previous conversation.

[107] In order to solve the foregoing problem, the service providing server 300 suggests various countermeasures. First, the service providing server 300 defines the conversation type between the visitor and the conversational agent. For example, when the visitor asks a question to the conversational agent, the visitor must clearly state the subject and the predicate. That is, when the visitor asks the age, the visitor clearly states the subject as in "How old are you?" or "What is your age?". Therefore, the conversational agent can understand the meaning of input of the visitor by an appropriate natural language processing procedure. In addition, when the visitor asks a question to the conversational agent, the visitor always uses a question mark '?', so that the conversational agent can understand that the input of the visitor is a question.

[108] Second, an additional button (not shown) is installed at one side of a check button 4 of Fig. 17. When the visitor asks a question to the conversational agent, the visitor clicks the button, so that the conversational agent can understand that the input of the visitor is a question.

[109] As described above, by predefining the rules, when the visitor inputs "What is your age?" or "Age?" the conversational agent can answer, for example, "I am thirty". In the case that the visitor inputs "My age" or "Age", the conversational agent can answer "Yes'Or "Yes, your age".

[110] However, although a few predictable conversation contents are assumed and the rules are predefined, there are still limits in the current natural language processing technique and unpredictable conversation situations. Accordingly, the conversational agent cannot properly respond to various inputs of the visitor merely by using the predefined rules or the additional button.

[I l l] So as to overcome the limits of the natural language processing technique and the predefined rules, the conversational agent service provider examines the conversation contents between the conversational agent and the visitor recorded in S505, prepares appropriate conversation data in regard to the questions which the conversational agent could not answer or improperly answered in the conversation with the visitor, stores the conversation data in the individual conversation DB 280. As a result, the conversational agent can provide more various responses. Also, the conversational agent can be educated by the above procedure.

[112] The method for educating the conversational agent originates in well understanding of an attribute of an internet. When the conversational agent service providing server 300 provides predefined forms and rules like knowledge search (which is a culture phenomenon and a knowledge providing tool on a world wide web. Differently from an encyclopedia, the knowledge search does not suggest standardized answers to questions. That is, a knowledge search service provider provides predefined forms and rules, internet users spontaneously suggest various answers, and a questioner selects the best answer. In regard to unexpected questions which are not included in the encyclopedia, the internet users suggest various answers.), the conversational agent service provider spontaneously expands responses to inputs in the forms and rules. That is, the present invention provides the conversational agent service which completes the intelligence type conversational agent by education.

[113] In accordance with the present invention, instead of other internet users, the conversational agent service provider educates the conversational agent by using the con- versation data stored in the individual conversation DB 280. The conversational agent service provider sells, buys or shares the conversation data with the other conversational agent service providers, thereby more efficiently educating the conversational agent.

[114] Accordingly, the present invention only provides the agent server 400, the individual conversation DB 280 and the common conversation DB 270 as tools for educating the conversational agent. The education results of the conversational agents are dependent on the plurality of conversational agent service providers.

[115] When the visitor inputs a message through the conversation window 3, the service providing server 300 provides a response by the above procedure.

[116] When the service providing server 300 receives a request for ending visit of the web page providing the conversational agent service from the visitor, the service providing server 300 stores the conversation contents between the visitor and the conversational agent in the form of a log (S 505).

[117] On the other hand, the conversation contents between the visitor and the conversational agent are not always stored in the log-out operation of the visitor. Preferably, the service providing server 300 stores the conversation contents between the visitor and the conversational agent at predetermined intervals.

[118] Fig. 16 is a flowchart showing a method for buying a new conversation and educating an agent. The user buys predefined conversation data or the right of directly inputting conversation data to educate his/her agent (S601).

[119] If the user buys the predefined conversation data (N in S602), the data information is extracted from the common conversation DB 270 (S603). The right of using the conversation data of the common conversation DB 270 is stored in the individual conversation DB 280 (S604).

[120] If the user buys the right of directly inputting the conversation data (Y in S602), the remaining frequency of the right of inputting the data is checked (S 605). If the remaining frequency exists (Y in S606), the user directly inputs the conversation data. The corresponding data are stored in the individual conversation DB 280 (S607). If the remaining frequency does not exist (N in S606), the user buys the right again. After inputting one individual conversation data, the user can repeatedly input another conversation data (S608). Finally, the conversation bought and taught by the user or the conversation directly inputted by the user is stored and managed in the individual conversation DB 280 in the form of a log (S609).

[121] Figs. 17 and 18 illustrate examples of the web pages created when the conversational agent is used for the community service.

[122] Referring to Fig. 17, a conversational agent 1 is used in a mini homepage type community service, for chatting with the other users. A general agent substitutes for the user only with a shape. However, in the present invention, the conversational agent 1 has a text balloon 2 and a conversation window 3, for further providing an interactive conversation service to the other users.

[123] Fig. 18 shows a conversational agent 1 of a writer of a bulletin board. Another user has a conversation with the conversational agent 1 through a conversation window 2 of the conversational agent 1 and an input window 3. In this embodiment, the reply function of the bulletin board can be converted into a conversation type. The writer of the bulletin board obtains wanted information by referring to a conversation log.

[124] Fig. 19 illustrates one example of a user obtaining the right of inputting conversation data and directly inputting the conversation data. The conversation data consists of a pair of question and answer. The user appropriately inputs a question and an answer.

[125] Fig. 20 illustrates examples of the predefined conversation data (conversation pack) sold to users. The conversation data are not individually sold but sold as a package by types. That is, when the user buys a greeting package, the agent of the user processes greetings by using the greeting-related conversation data stored in the common conversation DB 270.

[126] Fig. 21 illustrates one example of a process for selling the conversation data

(conversation pack) of Fig. 20. A user who intends to sell the conversation pack accesses an agent service server or a conversation pack service server 1102 through a user computer 1101, and provides his/her conversation pack for sale. Another user accesses the agent service server or the conversation pack service server 1102 through a user computer 1103, and buys the conversation pack.

[127] The contents of the conversation pack can be conversation contents formed between the user and the conversational agent by conversation or education (conversation teaching), or contents prepared by the user in relation to a special subject (English conversation, cooking, etc.).

[128] The conversation pack consists of a set of pairs of questions and answers. For example, the pairs of questions and answers such as "Best baseball player? / Jeong-su, Sim" and "Highest annual salary in professional baseball? / Seven hundred and fifty million won" are made to compose the conversation pack. The user loads the conversation pack on the agent service server or the conversation pack sale service server 1102, and the third party buys or shares the conversation pack. Accordingly, when a visitor asks "Highest annual salary in professional baseball?" a conversational agent of the third party preferentially finds an answer in the conversation pack, and answers "Seven hundred and fifty million won".

[129] In this service, the agent service server or the conversation pack sale service server

1102 serves as a market site of the conversation packs. Also, the conversation packs can be shared between the users on the server.

[130] Fig. 14 shows one example of a physical space in which the conversation pack can be transferred between the users. Here, the physical space includes an individual conversation DB 5 allocated to an owner of a conversational agent as well as a common conversation DB 4 necessary for a conversation between the conversational agent and the user.

[131] Generally, when the user (visitor) asks something, the conversational agent finds an appropriate answer in the common conversation DB 4 predefined by the conversational agent service, and chats with the user. However, in case the individual conversation DB 5 is formed, the conversational agent preferentially searches the individual conversation DB 5 for an appropriate answer. If the answer exists in the individual conversation DB 5, the conversational agent chats with the user by using the DB 5.

[132] The user can make the conversation pack and store the conversation pack in the individual conversation DB 5, or get the conversation pack of another user and store the conversation pack in the individual conversation DB 5, thereby developing the conversation of the conversational agent.

[133] Fig. 22 illustrates one example of a conversational agent service in accordance with the present invention. In the conversational agent service, a conversation between a visitor and a conversational agent is not sequentially presented by a simple text or onesided operation of the conversational agent, but simultaneously presented by a cartoon. When the conversational agent gives an answer to a question of the visitor, the conversation is displayed in the form of cartoon. Therefore, the conversation can be si mul- taneously displayed.

[134] Fig. 23 illustrates one example of a system in accordance with the present invention. Identically to the conventional system, the system includes a user computer 1, a visitor computer 2, an internet 3 used as a network, a conversational agent service server 4, and a DB 5 for storing pairs of questions and answers. When a visitor accesses the conversational agent service server 4 through the internet 3 by using the visitor computer 2 and chats with a conversational agent of a specific user, the conversational agent service server 4 finds an appropriate answer to a question of the visitor in the DB 5 and gives the answer to the visitor, thereby providing the conversational agent service. On the other hand, the system of the present invention further includes a conversation cartoon server 6 engaged with the conversational agent service server 4, and a cartoon DB 7 attached to the conversation cartoon server 6, which will later be explained in detail.

[135] Fig. 24 illustrates a method for a user setting up cartoon cuts for his/her conversational agent in accordance with the present invention. When the user accesses the conversational agent service server 4 through the internet 3 by using the user computer 1 and intends to select cartoon cuts for the conversation between the conversational agent and the visitor, the conversational agent service server 4 requests the conversation cartoon server 6 to find the cartoon cuts in the cartoon DB 7, and transmits the screen of Fig. 24 to the user computer 1. The user selects the whole cartoon cuts, selects some of the cartoon cuts, or sets up the situations for the cartoon cuts as shown in Fig. 25.

[136] Fig. 25 illustrates one example of information contents of the cartoon cut stored in the cartoon DB 6. The information contents of the cartoon cut includes a file name and a copyright holder of the cartoon cut, and a license period for which the user can use the cartoon cut. In case a specific user uses the cartoon cut for his/her conversational agent, the information contents can include information on the specific user or the conversational agent of the user. If a plurality of cartoon cuts are used, the information contents include information on whether the cartoon cuts are used as an initial image. In addition, the information contents include information on whether the cartoon cut is used in relation to a special feeling or situation.

[137] Fig. 26 illustrates another example of the conversational agent service in accordance with the present invention. A conversational agent gives an answer (for example, "hi, what is your name?") to a question of a visitor (for example, "hi"). This conversation is displayed on text balloons of a cartoon cut set up at the initial stage and provided as one cut. The conversational agent gives an answer (for example, "really?") to a question (or answer) of the visitor (for example, "I don't know"). This conversation is also displayed on text balloons of another cartoon cut and provided as one cut. Preferably, the cartoon cut of Fig. 26 can be set up in the information contents of the cartoon cut of Fig. 25 and presented in relation to the expression relating to 'ignorance' such as "I don't know". If the cartoon cut is not set up in advance, a cartoon cut different from the initial cartoon cut is randomly displayed.

[138] Fig. 27 illustrates one example of the conversational agent service server and the conversation cartoon server in accordance with the present invention. The conversational agent service server 4 and the DB 5 for storing the pairs of questions and answers are formed. Preferably, the conversation cartoon server 6 includes a cartoon information managing unit 61, a conversation processing unit 62 and a cartoon information returning unit 63. hi addition, the cartoon DB 7 for storing the information of the cartoon cuts as shown in Fig. 25 is attached to the conversation cartoon server 6. The cartoon information managing unit 61 stores the information of the cartoon cuts in the cartoon DB 7, the conversation processing unit 62 finds an appropriate cartoon cut in the cartoon DB 7 according to the conversation contents, and the cartoon information returning unit 63 returns the found cartoon cut to the conversational agent service server 4. [139] Fig. 28 illustrates one example of a process for storing the information of the cartoon cut in the cartoon DB in the conversation cartoon server. When the user prepares the information of the cartoon cut as shown in Fig. 25 and transmits the information to the conversational agent service server 4 through the user computer 2, the conversational agent service server 4 transmits the information to the conversation cartoon server 6. The conversation cartoon server 6 starts a step (Sl) for registering the information of the cartoon cut by the cartoon information managing unit 61, takes an appropriate natural language processing procedure (S2), checks whether the information has been registered in relation to the same contents (S3), determines priority of the information (S4), and stores the result (S5). If the information has not been registered, the conversation cartoon server 6 directly stores the result. This procedure can be taken without the above steps S2, S3 and S4.

[140] Fig. 29 illustrates one example of a process for processing the conversation between the visitor computer and the conversational agent by the conversational agent service server in accordance with the present invention. When a question is inputted from the visitor computer 2 (SI l), the conversational agent service server 4 preferably takes the natural language processing procedure on the question (S 12), finds an answer to the question in the conversation DB 5 (S 13), checks whether an appropriate cartoon cut exists with the help of the conversation cartoon server 6 (S 14), receives information if the appropriate cartoon cut exists (S 15), and presents the answer of the conversational agent as shown in Fig. 26 (S 17) (and transmits the screen to be displayed on the visitor computer 2). If the appropriate cartoon cut does not exist, the conversational agent service server 4 provides only the text of the left side of Fig. 26 as the answer of the conversational agent (S 17).

[141] Fig. 30 illustrates one example of the conversational agent service in accordance with the present invention. A conversational agent gives an answer to a question of a visitor with a preset image.

[142] Fig. 31 illustrates one example of the system in accordance with the present invention. The system includes a visitor computer 1, a user computer 2, an internet 3 used as a network, a conversational agent service server 4, and a DB 5 for storing pairs of questions and answers. A visitor accesses the conversational agent service server 4 through the internet 3 by using the visitor computer 1, and chats with a conversational agent provided by the conversational agent service server 4. Here, the conversational agent service server 4 finds an appropriate answer to a question of the visitor in the DB 5 for storing the pairs of questions and answers, and transmits the answer to the visitor computer 1.

[143] In accordance with the present invention, as shown in Fig. 30, the text and the image are provided as the answer. [144] Figs. 32 and 33 illustrate one example of a method for a user designating a text and an image as an answer to a question in accordance with the present invention. When the conversational agent service server 4 receives a request for setting up an answer to a question from the user computer 2, the conversational agent service server 4 provides the screen of Fig. 32 to the user computer 2. The user sets up a question (for example, "Do you have a mobile phone?" on the screen by using the user computer 2, inputs a text answer (for example, "Yes, I have a smart mobile phone"), and clicks a search button 6. Then, a special window for enabling the user to find and input an image file is provided as shown in Fig. 33. When the user selects a target image and clicks a teach button 7, the text and the image are transmitted to the conversational agent service server 4 as the pair of question and answer and stored in the DB 5.

[145] Fig. 34 illustrates another example of the system in accordance with the present invention. Preferably, a conversational agent service server 4 includes a DB 8 for storing pairs of questions and answers (texts and images) directly inputted by a user. When a visitor asks a question (for example, "Do you have a mobile phone?") to a conversational agent through a visitor computer 3, the conversational agent service server 4 firstly searches the DB 8 for storing the pairs of questions and answers (texts and images) directly inputted by the user for the answer to the question of the visitor. If the answer exists, the conversational agent service server 4 transmits the answer to the visitor computer 2. If the answer does not exist, the conversational agent service server 4 finds the answer in a DB 5 and transmits the answer to the visitor computer 2.

[146] Fig. 35 illustrates one example of the operation of the conversational agent service server. First, the conversational agent service server 4 checks whether a question of the visitor has been inputted from the visitor computer 2 (Sl), and searches the DB 8 for an answer if the question has been inputted (S2). If the answer to the question exists in the DB 8, the conversational agent service server 4 transmits the answer (text and image) to the visitor computer 2 (S3), and if the answer does not exist in the DB 8, the conversational agent service server 4 searches the DB 5 for the answer and transmits the answer to the visitor computer 2 (S4). If a new question exists, the above procedure is repeated (S5), and if a new question does not exist, the routine is ended.

[147] In the above embodiments, the conversational agent service has been carried out between the user computer and the conversational agent on the web. However, it must be recognized that the conversational agent service is applicable to the conversational agent on the messenger of Fig. 3.

[148] As depicted in Figs. 36a and 36b, when a user inputs a conversation, a conversational agent says an advertisement expression of an advertiser suitable for the conversation. Here, [I] is the user chatting with the conversational agent, and [c?Ribero$] is the conversational agent. Referring to Figs. 36a and 36b, the user inputs "Did you have a dessert?", and the conversational agent provides the advertisement expression "I had a dessert. Dalgona ice cream newly produced by XY confectionary company. It was delicious", and the image. In order to obtain the conversation result having the advertisement information of Fig. 36b from the conversation of Fig. 36a, the advertiser must register information of Fig. 37 in advance. Fig. 37 is a table showing one example of registering advertiser information (XY confectionary company), advertiser URL (http://www.xyice.com), an advertisement keyword (dessert), a conversation expression (Did you have a dessert?), an advertisement expression (I had a dessert. Dalgona ice cream newly produced by XY confectionary company. It was delicious.), and an advertisement image (xy_icecream.jpg).

[149] Fig. 38 illustrates an online advertisement system in accordance with the present invention. The online advertisement system includes a DB 1 for storing advertisement information, a conversation advertisement server 2 for processing a conversation type advertisement, a conversational agent server 3 for providing a conversation service with a user, and a DB 4 for storing conversation information.

[150] The conversation advertisement server 2 includes an advertisement information managing unit 311 for managing advertisement information inputted by an advertiser, a conversation processing unit 312 for preprocessing conversation information from a conversational agent to find an appropriate advertisement, and an advertisement information returning unit 313 for transmitting the appropriate advertisement to the conversational agent server 3. If the appropriate advertisement does not exist, the advertisement information returning unit 313 returns information notifying the absence of the advertisement, so that the conversational agent can keep chatting with the user.

[151] Fig. 39 is a flowchart showing a process for registering the advertisement information in accordance with the present invention. The advertiser accesses the conversation advertisement server 2 and registers a conversation expression, an advertisement keyword, an advertisement expression, an advertisement image, and URL information of a web page to be linked (S701). A natural language processing procedure is taken on the conversation expression of the registered advertisement information. The original conversation expression and the standardized conversation expression are stored together (S702). Because the conversation expression is converted into a standard type by the natural language processing procedure, various variations of the conversation expression can be processed. For example, when the conversation expression registered by the advertiser is "Did you have a dessert?", various conversation expressions similar to the registered conversation expression, such as "Did you eat a dessert?" and "What did you have for dessert?" can be processed by standardization using the natural language processing procedure. After the conversation expression is processed, whether advertisement information having similar contents exists is checked to examine whether the advertisement overlaps with a previously-registered advertisement of another advertiser (S703). If the similar advertisement information exists, priority information of the advertisement expression suggested by the conversational agent is adjusted by a priority processing procedure (S704). If the similar advertisement information does not exist, the advertisement information and the conversation expression information standardized by the natural language processing procedure is stored (S705). As another application example, when the advertisement is presented not by the conversation expression inputted by the user but by a simple keyword, the step (S702) for standardizing the conversation expression by the natural language processing procedure is not necessary. In this case, if the keyword registered by the advertiser is "Dessert", the advertisement is presented in all conversations including the keyword "Dessert".

[152] Fig. 40 is a flowchart showing a process for presenting the advertisement information as an answer to a question of the user. The conversational agent receives a conversation from the user (S801). The natural language processing procedure is taken on the inputted conversation expression (S802). The conversation inputted by the user is converted into a standard type expression by the analysis and processing procedure, so that an advertisement expression suitable for the conversation can be searched for. The advertisement information suitable for the conversation expression is searched for (S803). The search operation is carried out on the basis of similarity between the conversation expression information analyzed by the natural language processing procedure and the conversation expression information of the advertiser stored after the natural language processing procedure. Whether the appropriate advertisement information exists is checked (S804). If the appropriate advertisement information exists, the advertisement type conversation inputted by the advertiser is provided to the conversational agent (S805). If the appropriate advertisement information does not exist, information notifying the absence of appropriate advertisement information is returned (S806). According to the returned information, the conversational agent provides the advertisement information or the general conversation to the user as the response to the conversation inputted by the user (S807).

[153] Although the preferred embodiments of the present invention have been described, it is understood that the present invention should not be limited to these preferred embodiments but various changes and modifications can be made by one skilled in the art within the spirit and scope of the present invention as hereinafter claimed.

Claims

Claims
[1] A conversation system using a conversational agent, comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server.
[2] The conversation system of claim 1, wherein the transmitting means is a first terminal having a messenger function and transmitting a question inputted through a messenger to the conversational agent server, the conversation system comprising a second terminal for transmitting the question to the first terminal through the messenger.
[3] The conversation system of claim 1, wherein the transmitting means is a user terminal for transmitting a first language question to the conversational agent server, the conversation system comprising a translation server for receiving the first language question from the conversational agent server, translating the question into a second language, and transmitting the second language question to the con versational agent server.
[4] The conversation system of claim 1, wherein the transmitting means is a mobile communication company for transmitting a question to the conversational agent server, the conversation system comprising a user terminal for transmitting the question to the mobile communication company in the form of a short message.
[5] The conversation system of claim 1, comprising: a user terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server; and a conversation pack DB for storing a conversation pack consisting of the pairs of questions and answers transmitted from the user terminal.
[6] The conversation system of claim 1, comprising: a cartoon DB for storing cartoon cuts; and a cartoon server for managing the cartoon DB, and transmitting, to the conversational agent server, a cartoon cut corresponding to the question from the conversational agent server.
[7] The conversation system of claim 1, comprising: a user terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server, the answers comprising image type answers; and an image DB for storing images from the user terminal.
[8] The conversation system of claim 1, comprising: an advertisement DB for storing advertisement information; and an advertisement server for receiving the question from the conversational agent server, finding the advertisement information corresponding to the question in the advertisement DB, and transmitting the search result to the conversational agent server.
[9] A conversation system using a conversational agent, comprising: a conversation
DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, wherein the transmitting means comprises: a first terminal having a messenger function and transmitting a question inputted through a messenger to the conversational agent server; a user terminal for transmitting a first language question to the conversational agent server; and a mobile communication company for transmitting a question to the conversational agent server, the conversation system comprising: a second terminal for transmitting the question to the first terminal through the messenger; a translation server for receiving the first language question from the conversational agent server, translating the question into a second language, and transmitting the second language question to the conversational agent server; a user terminal for transmitting the question to the mobile communication company in the form of a short message; a terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server; a conversation pack DB for storing a conversation pack consisting of the pairs of questions and answers transmitted from the terminal; a cartoon DB for storing cartoon cuts; a cartoon server for managing the cartoon DB, and transmitting, to the conversational agent server, a cartoon cut corresponding to the question from the conversational agent server; a preparation terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server, the answers comprising image type answers; an image DB for storing images from the preparation terminal; an advertisement DB for storing advertisement information; and an advertisement server for receiving the question from the conversational agent server, finding the advertisement information corresponding to the question in the advertisement DB, and transmitting the search result to the conversational agent server.
[10] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, the conversation method comprising: a first step for receiving a question from the transmitting means; a second step for finding an answer to the question in the conversation DB; and a third step for transmitting the answer to the transmitting means.
[11] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, the transmitting means being a first terminal having a messenger function and transmitting a question inputted through a messenger to the conversational agent server, the conversation system comprising a second terminal for transmitting the question to the first terminal through the messenger; the conversation method comprising: a first step for receiving, at the second terminal, a question from the first terminal; a second step for transmitting, at the second terminal, the question to the conversational agent server; a third step for finding, at the conversational agent server, an answer to the question in the conversation DB; a fourth step for transmitting, at the conversational agent server, the answer to the second terminal; and a fifth step for transmitting, at the second terminal, the answer to the first terminal.
[12] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, the conversation method, comprising: a first step for receiving a first language question from the transmitting means; a second step for translating the first language question into a second language which is a language used in the conversation DB; a third step for finding an answer to the second language question in the conversation DB; and a fourth step for transmitting the answer to the transmitting means.
[13] The conversation method of claim 12, further comprising a step for translating the answer into the first language prior to the fourth step.
[14] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; and a transmitting means for transmitting the question to the conversational agent server, the transmitting means being a mobile communication company for transmitting a question to the conversational agent server, the conversation system comprising a user terminal for transmitting the question to the mobile communication company in the form of a short message; the conversation method comprising: a first step for receiving, at the mobile communication company, a short message type question from the user terminal; a second step for transmitting, at the mobile communication company, the question to the conversational agent server; a third step for finding, at the conversational agent server, an answer to the question in the conversation DB; a fourth step for transmitting, at the conversational agent server, the answer to the mobile communication company; and a fifth step for transmitting, at the mobile communication company, the answer to the user terminal.
[15] The conversation method of claim 14, wherein, in the first step, the user terminal transmits a phone number of a conversational agent user with the short message type question.
[16] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; a user terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server; and a conversation pack DB for storing a conversation pack consisting of the pairs of questions and answers transmitted from the user terminal; the conversation method comprising: a first step for receiving a sale request for the conversation pack stored in the conversation pack DB from a conversational agent user; a second step for selling the corresponding conversation pack to the conversational agent user; and a third step for storing the conversation pack to be used by the conversational agent user.
[17] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; a transmitting means for transmitting the question to the conversational agent server; a cartoon DB for storing cartoon cuts; and a cartoon server for managing the cartoon DB, and transmitting, to the conversational agent server, a cartoon cut corresponding to the question from the conversational agent server; the conversation method comprising: a first step for receiving a question from the transmitting means; a second step for finding an answer to the question in the conversation DB, transmitting the question to the cartoon server, and receiving a cartoon cut found in the cartoon DB by the cartoon server at the same time; and a third step for transmitting the answer from the conversation DB and the cartoon cut from the cartoon DB to the transmitting means.
[18] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; a transmitting means for transmitting the question to the conversational agent server; a user terminal for preparing the pairs of questions and answers and transmitting the pairs of questions and answers to the conversational agent server, the answers comprising image type answers; and an image DB for storing images from the user terminal; the conversation method, comprising: a first step for receiving a pair of question and image type answer from the user terminal; a second step for storing the pair of question and image type answer; a third step for receiving a question from the transmitting means; and a fourth step for transmitting an image type answer corresponding to the question to the transmitting means.
[19] A conversation method using a conversational agent which employs a conversation system using the conversational agent, the conversation system comprising: a conversation DB for storing pairs of questions and answers; a conversational agent server for receiving a question, transmitting the question to the conversation DB, and finding an answer in the conversation DB; a transmitting means for transmitting the question to the conversational agent server; an advertisement DB for storing advertisement information; and an advertisement server for receiving the question from the conversational agent server, finding the advertisement information corresponding to the question in the advertisement DB, and transmitting the search result to the conversational agent server, the conversation method comprising: a first step for receiving a question from the transmitting means; a second step for transmitting the question to the advertisement server; a third step for finding, at the advertisement server, advertisement information corresponding to the question in the advertisement DB; a fourth step for receiving the advertisement information from the advertisement server; and a fifth step for transmitting the advertisement information to the transmitting means.
PCT/KR2006/002095 2005-05-30 2006-05-30 Conversation system and method using conversational agent WO2006129967A1 (en)

Priority Applications (14)

Application Number Priority Date Filing Date Title
KR1020050045786A KR20060117860A (en) 2005-05-30 2005-05-30 Method and system of providing conversational agent service using images
KR1020050045793A KR20060117861A (en) 2005-05-30 2005-05-30 Online advertisement method and system using conversational agent
KR1020050045778A KR20060113311A (en) 2005-05-30 2005-05-30 Communication method and system using conversational agent in personal computer
KR10-2005-0045793 2005-05-30
KR1020050045785A KR20060117859A (en) 2005-05-30 2005-05-30 Method and system of providing conversational agent service using cartoon
KR10-2005-0045786 2005-05-30
KR10-2005-0045778 2005-05-30
KR10-2005-0045785 2005-05-30
KR10-2005-0045840 2005-05-31
KR1020050045841A KR20060113316A (en) 2005-05-31 2005-05-31 Method and system of telecommunication with conversational agent using short message service
KR10-2005-0045842 2005-05-31
KR1020050045842A KR20060117862A (en) 2005-05-31 2005-05-31 Method and system for selling pack including conversation data used for conversational agent
KR1020050045840A KR20060113315A (en) 2005-05-31 2005-05-31 Translation method and system in conversational agent service using different languages between user and the agent
KR10-2005-0045841 2005-05-31

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Cited By (121)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8296383B2 (en) 2008-10-02 2012-10-23 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US8311838B2 (en) 2010-01-13 2012-11-13 Apple Inc. Devices and methods for identifying a prompt corresponding to a voice input in a sequence of prompts
US8345665B2 (en) 2001-10-22 2013-01-01 Apple Inc. Text to speech conversion of text messages from mobile communication devices
US8352272B2 (en) 2008-09-29 2013-01-08 Apple Inc. Systems and methods for text to speech synthesis
US8352268B2 (en) 2008-09-29 2013-01-08 Apple Inc. Systems and methods for selective rate of speech and speech preferences for text to speech synthesis
US8355919B2 (en) 2008-09-29 2013-01-15 Apple Inc. Systems and methods for text normalization for text to speech synthesis
US8380507B2 (en) 2009-03-09 2013-02-19 Apple Inc. Systems and methods for determining the language to use for speech generated by a text to speech engine
US8396714B2 (en) 2008-09-29 2013-03-12 Apple Inc. Systems and methods for concatenation of words in text to speech synthesis
US8458278B2 (en) 2003-05-02 2013-06-04 Apple Inc. Method and apparatus for displaying information during an instant messaging session
US8527861B2 (en) 1999-08-13 2013-09-03 Apple Inc. Methods and apparatuses for display and traversing of links in page character array
US8543407B1 (en) 2007-10-04 2013-09-24 Great Northern Research, LLC Speech interface system and method for control and interaction with applications on a computing system
US8583418B2 (en) 2008-09-29 2013-11-12 Apple Inc. Systems and methods of detecting language and natural language strings for text to speech synthesis
US8600743B2 (en) 2010-01-06 2013-12-03 Apple Inc. Noise profile determination for voice-related feature
US8614431B2 (en) 2005-09-30 2013-12-24 Apple Inc. Automated response to and sensing of user activity in portable devices
US8620662B2 (en) 2007-11-20 2013-12-31 Apple Inc. Context-aware unit selection
US8639516B2 (en) 2010-06-04 2014-01-28 Apple Inc. User-specific noise suppression for voice quality improvements
WO2014018794A1 (en) * 2012-07-25 2014-01-30 Toytalk, Inc. Artificial intelligence script tool
US8645137B2 (en) 2000-03-16 2014-02-04 Apple Inc. Fast, language-independent method for user authentication by voice
US8660849B2 (en) 2010-01-18 2014-02-25 Apple Inc. Prioritizing selection criteria by automated assistant
US8677377B2 (en) 2005-09-08 2014-03-18 Apple Inc. Method and apparatus for building an intelligent automated assistant
US8682667B2 (en) 2010-02-25 2014-03-25 Apple Inc. User profiling for selecting user specific voice input processing information
US8682649B2 (en) 2009-11-12 2014-03-25 Apple Inc. Sentiment prediction from textual data
US8688446B2 (en) 2008-02-22 2014-04-01 Apple Inc. Providing text input using speech data and non-speech data
US8706472B2 (en) 2011-08-11 2014-04-22 Apple Inc. Method for disambiguating multiple readings in language conversion
US8712776B2 (en) 2008-09-29 2014-04-29 Apple Inc. Systems and methods for selective text to speech synthesis
US8713021B2 (en) 2010-07-07 2014-04-29 Apple Inc. Unsupervised document clustering using latent semantic density analysis
US8719014B2 (en) 2010-09-27 2014-05-06 Apple Inc. Electronic device with text error correction based on voice recognition data
US8719006B2 (en) 2010-08-27 2014-05-06 Apple Inc. Combined statistical and rule-based part-of-speech tagging for text-to-speech synthesis
US8762156B2 (en) 2011-09-28 2014-06-24 Apple Inc. Speech recognition repair using contextual information
US8768702B2 (en) 2008-09-05 2014-07-01 Apple Inc. Multi-tiered voice feedback in an electronic device
US8775442B2 (en) 2012-05-15 2014-07-08 Apple Inc. Semantic search using a single-source semantic model
US8781836B2 (en) 2011-02-22 2014-07-15 Apple Inc. Hearing assistance system for providing consistent human speech
US8812294B2 (en) 2011-06-21 2014-08-19 Apple Inc. Translating phrases from one language into another using an order-based set of declarative rules
WO2014143163A1 (en) * 2012-06-06 2014-09-18 Olabinri Babatunde O O System and process for communicating between two vehicles
US8862252B2 (en) 2009-01-30 2014-10-14 Apple Inc. Audio user interface for displayless electronic device
US8898568B2 (en) 2008-09-09 2014-11-25 Apple Inc. Audio user interface
US8935167B2 (en) 2012-09-25 2015-01-13 Apple Inc. Exemplar-based latent perceptual modeling for automatic speech recognition
US8972324B2 (en) 2012-07-25 2015-03-03 Toytalk, Inc. Systems and methods for artificial intelligence script modification
US8977255B2 (en) 2007-04-03 2015-03-10 Apple Inc. Method and system for operating a multi-function portable electronic device using voice-activation
US8996376B2 (en) 2008-04-05 2015-03-31 Apple Inc. Intelligent text-to-speech conversion
WO2015064903A1 (en) * 2013-10-31 2015-05-07 Samsung Electronics Co., Ltd. Displaying messages in an electronic device
US9053089B2 (en) 2007-10-02 2015-06-09 Apple Inc. Part-of-speech tagging using latent analogy
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US9280610B2 (en) 2012-05-14 2016-03-08 Apple Inc. Crowd sourcing information to fulfill user requests
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
US9311043B2 (en) 2010-01-13 2016-04-12 Apple Inc. Adaptive audio feedback system and method
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9330381B2 (en) 2008-01-06 2016-05-03 Apple Inc. Portable multifunction device, method, and graphical user interface for viewing and managing electronic calendars
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US9431006B2 (en) 2009-07-02 2016-08-30 Apple Inc. Methods and apparatuses for automatic speech recognition
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US9547647B2 (en) 2012-09-19 2017-01-17 Apple Inc. Voice-based media searching
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9721563B2 (en) 2012-06-08 2017-08-01 Apple Inc. Name recognition system
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US9733821B2 (en) 2013-03-14 2017-08-15 Apple Inc. Voice control to diagnose inadvertent activation of accessibility features
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9946706B2 (en) 2008-06-07 2018-04-17 Apple Inc. Automatic language identification for dynamic text processing
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US9977779B2 (en) 2013-03-14 2018-05-22 Apple Inc. Automatic supplementation of word correction dictionaries
US10002189B2 (en) 2007-12-20 2018-06-19 Apple Inc. Method and apparatus for searching using an active ontology
US10019994B2 (en) 2012-06-08 2018-07-10 Apple Inc. Systems and methods for recognizing textual identifiers within a plurality of words
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US10078487B2 (en) 2013-03-15 2018-09-18 Apple Inc. Context-sensitive handling of interruptions
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US10255566B2 (en) 2011-06-03 2019-04-09 Apple Inc. Generating and processing task items that represent tasks to perform
US10269345B2 (en) 2016-09-19 2019-04-23 Apple Inc. Intelligent task discovery

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR19990078566A (en) * 1999-05-18 1999-11-05 이학준 Character storing device linked with computer system and control method thereof
KR20020084003A (en) * 2002-10-10 2002-11-04 김지훈 Instant Messenger auto-response robot
WO2004012151A1 (en) * 2002-07-31 2004-02-05 Inchain Pty Limited Animated messaging
KR20050007058A (en) * 2003-07-11 2005-01-17 임정빈 Method For Providing An Online Marketing Service Using Messenger Robot

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR19990078566A (en) * 1999-05-18 1999-11-05 이학준 Character storing device linked with computer system and control method thereof
WO2004012151A1 (en) * 2002-07-31 2004-02-05 Inchain Pty Limited Animated messaging
KR20020084003A (en) * 2002-10-10 2002-11-04 김지훈 Instant Messenger auto-response robot
KR20050007058A (en) * 2003-07-11 2005-01-17 임정빈 Method For Providing An Online Marketing Service Using Messenger Robot

Cited By (167)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8527861B2 (en) 1999-08-13 2013-09-03 Apple Inc. Methods and apparatuses for display and traversing of links in page character array
US8645137B2 (en) 2000-03-16 2014-02-04 Apple Inc. Fast, language-independent method for user authentication by voice
US9646614B2 (en) 2000-03-16 2017-05-09 Apple Inc. Fast, language-independent method for user authentication by voice
US8345665B2 (en) 2001-10-22 2013-01-01 Apple Inc. Text to speech conversion of text messages from mobile communication devices
US8718047B2 (en) 2001-10-22 2014-05-06 Apple Inc. Text to speech conversion of text messages from mobile communication devices
US8458278B2 (en) 2003-05-02 2013-06-04 Apple Inc. Method and apparatus for displaying information during an instant messaging session
US9501741B2 (en) 2005-09-08 2016-11-22 Apple Inc. Method and apparatus for building an intelligent automated assistant
US8677377B2 (en) 2005-09-08 2014-03-18 Apple Inc. Method and apparatus for building an intelligent automated assistant
US8614431B2 (en) 2005-09-30 2013-12-24 Apple Inc. Automated response to and sensing of user activity in portable devices
US9958987B2 (en) 2005-09-30 2018-05-01 Apple Inc. Automated response to and sensing of user activity in portable devices
US9389729B2 (en) 2005-09-30 2016-07-12 Apple Inc. Automated response to and sensing of user activity in portable devices
US9619079B2 (en) 2005-09-30 2017-04-11 Apple Inc. Automated response to and sensing of user activity in portable devices
US8930191B2 (en) 2006-09-08 2015-01-06 Apple Inc. Paraphrasing of user requests and results by automated digital assistant
US8942986B2 (en) 2006-09-08 2015-01-27 Apple Inc. Determining user intent based on ontologies of domains
US9117447B2 (en) 2006-09-08 2015-08-25 Apple Inc. Using event alert text as input to an automated assistant
US8977255B2 (en) 2007-04-03 2015-03-10 Apple Inc. Method and system for operating a multi-function portable electronic device using voice-activation
US9053089B2 (en) 2007-10-02 2015-06-09 Apple Inc. Part-of-speech tagging using latent analogy
US8543407B1 (en) 2007-10-04 2013-09-24 Great Northern Research, LLC Speech interface system and method for control and interaction with applications on a computing system
US8620662B2 (en) 2007-11-20 2013-12-31 Apple Inc. Context-aware unit selection
US10002189B2 (en) 2007-12-20 2018-06-19 Apple Inc. Method and apparatus for searching using an active ontology
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9330381B2 (en) 2008-01-06 2016-05-03 Apple Inc. Portable multifunction device, method, and graphical user interface for viewing and managing electronic calendars
US8688446B2 (en) 2008-02-22 2014-04-01 Apple Inc. Providing text input using speech data and non-speech data
US9361886B2 (en) 2008-02-22 2016-06-07 Apple Inc. Providing text input using speech data and non-speech data
US9865248B2 (en) 2008-04-05 2018-01-09 Apple Inc. Intelligent text-to-speech conversion
US9626955B2 (en) 2008-04-05 2017-04-18 Apple Inc. Intelligent text-to-speech conversion
US8996376B2 (en) 2008-04-05 2015-03-31 Apple Inc. Intelligent text-to-speech conversion
US9946706B2 (en) 2008-06-07 2018-04-17 Apple Inc. Automatic language identification for dynamic text processing
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US10108612B2 (en) 2008-07-31 2018-10-23 Apple Inc. Mobile device having human language translation capability with positional feedback
US8768702B2 (en) 2008-09-05 2014-07-01 Apple Inc. Multi-tiered voice feedback in an electronic device
US9691383B2 (en) 2008-09-05 2017-06-27 Apple Inc. Multi-tiered voice feedback in an electronic device
US8898568B2 (en) 2008-09-09 2014-11-25 Apple Inc. Audio user interface
US8352272B2 (en) 2008-09-29 2013-01-08 Apple Inc. Systems and methods for text to speech synthesis
US8355919B2 (en) 2008-09-29 2013-01-15 Apple Inc. Systems and methods for text normalization for text to speech synthesis
US8712776B2 (en) 2008-09-29 2014-04-29 Apple Inc. Systems and methods for selective text to speech synthesis
US8583418B2 (en) 2008-09-29 2013-11-12 Apple Inc. Systems and methods of detecting language and natural language strings for text to speech synthesis
US8396714B2 (en) 2008-09-29 2013-03-12 Apple Inc. Systems and methods for concatenation of words in text to speech synthesis
US8352268B2 (en) 2008-09-29 2013-01-08 Apple Inc. Systems and methods for selective rate of speech and speech preferences for text to speech synthesis
US8296383B2 (en) 2008-10-02 2012-10-23 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US8762469B2 (en) 2008-10-02 2014-06-24 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US8713119B2 (en) 2008-10-02 2014-04-29 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US8676904B2 (en) 2008-10-02 2014-03-18 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US9412392B2 (en) 2008-10-02 2016-08-09 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US8862252B2 (en) 2009-01-30 2014-10-14 Apple Inc. Audio user interface for displayless electronic device
US8751238B2 (en) 2009-03-09 2014-06-10 Apple Inc. Systems and methods for determining the language to use for speech generated by a text to speech engine
US8380507B2 (en) 2009-03-09 2013-02-19 Apple Inc. Systems and methods for determining the language to use for speech generated by a text to speech engine
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US9431006B2 (en) 2009-07-02 2016-08-30 Apple Inc. Methods and apparatuses for automatic speech recognition
US8682649B2 (en) 2009-11-12 2014-03-25 Apple Inc. Sentiment prediction from textual data
US8600743B2 (en) 2010-01-06 2013-12-03 Apple Inc. Noise profile determination for voice-related feature
US8670985B2 (en) 2010-01-13 2014-03-11 Apple Inc. Devices and methods for identifying a prompt corresponding to a voice input in a sequence of prompts
US8311838B2 (en) 2010-01-13 2012-11-13 Apple Inc. Devices and methods for identifying a prompt corresponding to a voice input in a sequence of prompts
US9311043B2 (en) 2010-01-13 2016-04-12 Apple Inc. Adaptive audio feedback system and method
US8660849B2 (en) 2010-01-18 2014-02-25 Apple Inc. Prioritizing selection criteria by automated assistant
US9548050B2 (en) 2010-01-18 2017-01-17 Apple Inc. Intelligent automated assistant
US8892446B2 (en) 2010-01-18 2014-11-18 Apple Inc. Service orchestration for intelligent automated assistant
US8670979B2 (en) 2010-01-18 2014-03-11 Apple Inc. Active input elicitation by intelligent automated assistant
US8731942B2 (en) 2010-01-18 2014-05-20 Apple Inc. Maintaining context information between user interactions with a voice assistant
US8903716B2 (en) 2010-01-18 2014-12-02 Apple Inc. Personalized vocabulary for digital assistant
US9318108B2 (en) 2010-01-18 2016-04-19 Apple Inc. Intelligent automated assistant
US8706503B2 (en) 2010-01-18 2014-04-22 Apple Inc. Intent deduction based on previous user interactions with voice assistant
US8799000B2 (en) 2010-01-18 2014-08-05 Apple Inc. Disambiguation based on active input elicitation by intelligent automated assistant
US9190062B2 (en) 2010-02-25 2015-11-17 Apple Inc. User profiling for voice input processing
US8682667B2 (en) 2010-02-25 2014-03-25 Apple Inc. User profiling for selecting user specific voice input processing information
US9633660B2 (en) 2010-02-25 2017-04-25 Apple Inc. User profiling for voice input processing
US10049675B2 (en) 2010-02-25 2018-08-14 Apple Inc. User profiling for voice input processing
US8639516B2 (en) 2010-06-04 2014-01-28 Apple Inc. User-specific noise suppression for voice quality improvements
US8713021B2 (en) 2010-07-07 2014-04-29 Apple Inc. Unsupervised document clustering using latent semantic density analysis
US8719006B2 (en) 2010-08-27 2014-05-06 Apple Inc. Combined statistical and rule-based part-of-speech tagging for text-to-speech synthesis
US9075783B2 (en) 2010-09-27 2015-07-07 Apple Inc. Electronic device with text error correction based on voice recognition data
US8719014B2 (en) 2010-09-27 2014-05-06 Apple Inc. Electronic device with text error correction based on voice recognition data
US8781836B2 (en) 2011-02-22 2014-07-15 Apple Inc. Hearing assistance system for providing consistent human speech
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US10102359B2 (en) 2011-03-21 2018-10-16 Apple Inc. Device access using voice authentication
US10255566B2 (en) 2011-06-03 2019-04-09 Apple Inc. Generating and processing task items that represent tasks to perform
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US8812294B2 (en) 2011-06-21 2014-08-19 Apple Inc. Translating phrases from one language into another using an order-based set of declarative rules
US8706472B2 (en) 2011-08-11 2014-04-22 Apple Inc. Method for disambiguating multiple readings in language conversion
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US8762156B2 (en) 2011-09-28 2014-06-24 Apple Inc. Speech recognition repair using contextual information
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9953088B2 (en) 2012-05-14 2018-04-24 Apple Inc. Crowd sourcing information to fulfill user requests
US9280610B2 (en) 2012-05-14 2016-03-08 Apple Inc. Crowd sourcing information to fulfill user requests
US8775442B2 (en) 2012-05-15 2014-07-08 Apple Inc. Semantic search using a single-source semantic model
US9154576B2 (en) 2012-06-06 2015-10-06 Babatunde O. O. Olabinri System and process for communicating between two vehicles
WO2014143163A1 (en) * 2012-06-06 2014-09-18 Olabinri Babatunde O O System and process for communicating between two vehicles
US10019994B2 (en) 2012-06-08 2018-07-10 Apple Inc. Systems and methods for recognizing textual identifiers within a plurality of words
US10079014B2 (en) 2012-06-08 2018-09-18 Apple Inc. Name recognition system
US9721563B2 (en) 2012-06-08 2017-08-01 Apple Inc. Name recognition system
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US10223636B2 (en) 2012-07-25 2019-03-05 Pullstring, Inc. Artificial intelligence script tool
WO2014018794A1 (en) * 2012-07-25 2014-01-30 Toytalk, Inc. Artificial intelligence script tool
US8972324B2 (en) 2012-07-25 2015-03-03 Toytalk, Inc. Systems and methods for artificial intelligence script modification
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9971774B2 (en) 2012-09-19 2018-05-15 Apple Inc. Voice-based media searching
US9547647B2 (en) 2012-09-19 2017-01-17 Apple Inc. Voice-based media searching
US8935167B2 (en) 2012-09-25 2015-01-13 Apple Inc. Exemplar-based latent perceptual modeling for automatic speech recognition
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US9977779B2 (en) 2013-03-14 2018-05-22 Apple Inc. Automatic supplementation of word correction dictionaries
US9733821B2 (en) 2013-03-14 2017-08-15 Apple Inc. Voice control to diagnose inadvertent activation of accessibility features
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US10078487B2 (en) 2013-03-15 2018-09-18 Apple Inc. Context-sensitive handling of interruptions
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9966060B2 (en) 2013-06-07 2018-05-08 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US10276170B2 (en) 2013-06-07 2019-04-30 Apple Inc. Intelligent automated assistant
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
WO2015064903A1 (en) * 2013-10-31 2015-05-07 Samsung Electronics Co., Ltd. Displaying messages in an electronic device
EP2869162A3 (en) * 2013-10-31 2015-11-04 Samsung Electronics Co., Ltd Displaying messages with cartoon cut images in an electronic device
US9641471B2 (en) 2013-10-31 2017-05-02 Samsung Electronics Co., Ltd. Electronic device, and method and computer-readable recording medium for displaying message in electronic device
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US10169329B2 (en) 2014-05-30 2019-01-01 Apple Inc. Exemplar-based natural language processing
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US10083690B2 (en) 2014-05-30 2018-09-25 Apple Inc. Better resolution when referencing to concepts
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9668024B2 (en) 2014-06-30 2017-05-30 Apple Inc. Intelligent automated assistant for TV user interactions
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US9986419B2 (en) 2014-09-30 2018-05-29 Apple Inc. Social reminders
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10269345B2 (en) 2016-09-19 2019-04-23 Apple Inc. Intelligent task discovery
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant

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