WO2019066110A1 - 자율 행동 로봇을 이용하여 대화 서비스를 제공하는 방법, 시스템 및 비일시성의 컴퓨터 판독 가능 기록 매체 - Google Patents
자율 행동 로봇을 이용하여 대화 서비스를 제공하는 방법, 시스템 및 비일시성의 컴퓨터 판독 가능 기록 매체 Download PDFInfo
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- 230000002452 interceptive effect Effects 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 2
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- 238000013135 deep learning Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/0005—Manipulators having means for high-level communication with users, e.g. speech generator, face recognition means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/50—Maintenance of biometric data or enrolment thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
- G10L2015/225—Feedback of the input speech
Definitions
- the present invention relates to a method, system and non-temporal computer-readable recording medium for providing an interactive service using an autonomous mobile robot.
- a robot for generating a conversation based on a user's voice, receiving and outputting a generated content dialogue based on the conversation, and a conversation input from the robot are converted into content sentences ,
- a conversation service device for transmitting a content dialogue including the converted content sentence and motion information of the robot to the robot has been introduced.
- Another object of the present invention is to provide an interactive service with a high degree of familiarity with a user on the basis of at least one of the personality attribute of the user and the reliability of the person attribute.
- a method of providing an interactive service using an autonomous mobile robot comprising the steps of: recognizing a user corresponding to acquired face information; determining a personality attribute of the recognized user and a reliability Determining at least one of the content of the conversation to be provided to the user based on at least one of the plurality of content and the reliability of the person attribute and the person attribute based on the feedback of the user to the content of the conversation / RTI >
- a system for providing an interactive service using an autonomous mobile robot comprising: a face information management unit for recognizing a user corresponding to obtained face information; And reliability of the person attribute and the reliability of the person attribute based on the feedback of the user to the content of the conversation, / RTI >
- non-transitory computer readable recording medium for recording another method for implementing the invention, another system, and a computer program for carrying out the method.
- FIG. 1 is a detailed diagram illustrating an internal configuration of a conversation service providing system according to an embodiment of the present invention.
- FIG. 2 is a diagram illustrating a situation in which a conversation service according to an exemplary embodiment of the present invention is provided.
- FIG. 3 is a diagram illustrating a process of providing a conversation service according to an exemplary embodiment of the present invention.
- FIG. 4 is a diagram illustrating an exemplary dialog template according to an embodiment of the present invention.
- FIG. 1 is a detailed diagram illustrating an internal configuration of a conversation service providing system 100 according to an embodiment of the present invention.
- the interactive service providing system 100 includes a face information managing unit 110, a dialogue managing unit 120, an update managing unit 130, a communication unit 140, (150).
- the face information management unit 110, the dialogue management unit 120, the update management unit 130, the communication unit 140, and the control unit 150 may be implemented by a program Module.
- a program module may be included in the conversation service providing system 100 in the form of an operating system, an application program module or other program module, and may be physically stored in various known memory devices.
- Such a program module may also be stored in a remote storage device capable of communicating with the conversation service providing system 100.
- Such program modules encompass but are not limited to routines, subroutines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types as described below in accordance with the present invention.
- conversation service providing system 100 Although described above with respect to the conversation service providing system 100, this description is exemplary and at least some of the components or functions of the conversation service providing system 100 may be provided in an external system (not shown) Or may be included in an external system.
- the face information managing unit 110 can perform a function of recognizing a user corresponding to the obtained face information.
- the face information managing unit 110 compares the face information obtained through the camera module (not shown) with the lookup table related to the face information of at least one user, The user corresponding to the obtained face information can be recognized.
- the face information managing unit 110 extracts main features from the obtained object image and compares the similarity with the main features of the object image of the lookup table (or database)
- a known face recognition algorithm such as an algorithm can be used.
- the dialogue management unit 120 determines whether or not the face to be provided to the user based on at least one of the personality attributes perceived by the face information management unit 110 and the reliability of the personality attributes
- the contents of conversation can be determined.
- the person attributes according to an embodiment of the present invention include a name, an age, a sex, an appearance (presence or absence of hair, presence or absence of glasses), an emotional state, a recent encounter date and time, a recent chat date and time, a hobby, .
- each of the person attributes may include reliability as to how reliable the person attribute is.
- the conversation management unit 120 can determine the type of conversation to be provided to the user based on at least one of the personality attribute of the user and the reliability of the person attribute, The content of the conversation associated with the type can be determined as the conversation content to be provided to the user.
- the dialogue management unit 120 may determine whether or not a person attribute that has not yet been acquired among the personality attributes, based on at least one of a personality attribute of a user who is a conversation partner and a reliability of the personality attribute At least one type of conversation among a type of conversation for acquiring the characteristic of the person, a type of conversation for updating the reliability of the person attribute, and a type of conversation in which the personality attribute having the reliability of a predetermined level or more is used, As the type of conversation to be applied to the conversation.
- the dialog management unit 120 refers to a dialog template grouped according to a person attribute, and determines a dialogue content associated with the determined dialogue type as a dialogue content to be provided to the user .
- the dialogue template may be a database in which words, phrases, paragraphs, etc. for generating conversation contents are classified based on at least one of a personality attribute and a conversation type.
- some person attributes for example, emotion states
- the dialogue management unit 120 can determine the conversation contents to be provided to the user corresponding to the interested person among the recognized users.
- the dialogue management unit 120 can calculate the energy of interest for the user based on at least one of the frequency, the number of times, and the period for which the face information is acquired, In the case where the energy is maintained for a predetermined period of time or longer, it is possible to determine that the user corresponds to a person of interest.
- the dialogue management unit 120 can determine the initial information of the person attribute of the user by estimating the person attribute related to the user from the face information of the user.
- the dialogue management unit 120 estimates various information that can be obtained from the external appearance of the face such as age, gender, presence or absence of glasses, It is possible to obtain the initial information of the person attribute. Meanwhile, the dialogue management unit 120 according to an exemplary embodiment of the present invention sets the reliability of the person attribute estimated through the face information of the user to a predetermined initial value (for example, 50% of the reliability 0 to 100% Intermediate value)).
- a predetermined initial value for example, 50% of the reliability 0 to 100% Intermediate value
- the update management unit 130 can update at least one of the person attribute related to the user and the reliability of the person attribute based on the user's feedback on the conversation content.
- the update management unit 130 can update the reliability of the user's person attribute associated with the feedback based on the type of the user's feedback on the conversation content.
- this type of feedback may include at least one of positive feedback, neutral feedback and negative feedback.
- the update management unit 130 determines the reliability of the first person attribute And if the feedback of the user is positive feedback on the first person attribute, the reliability of the first person attribute with respect to the user can be changed so as to be upward.
- the update management unit 130 can use known natural language processing techniques such as morphological analysis, syntax analysis, and semantic analysis to analyze user feedback on conversation contents.
- the update management unit 130 when feedback of a plurality of person attributes regarding the user is included in the user's feedback on the conversation contents, the update management unit 130 sets the feedback type for each of the person attributes The reliability of each person attribute can be updated with reference to the reference value.
- the conversation content provided to the user based on the fact that the sex attribute of the person attribute of the user is female and the age is thirty, is " .
- the update management unit 130 determines that the reliability of each of the person attributes whose sex is female and whose age is thirty is the same as that of the person Down.
- the update management unit 130 updates the reliability of the person attribute about the user, and when the reliability of the person attribute to be updated becomes lower than a predetermined level, have.
- the update management unit 130 when the reliability of the person attribute whose sex is female is 50% or less, based on the user's feedback on the conversation contents, It can be changed from female to male.
- the update management unit 130 sets the reliability of the changed person attribute to an initial value (for example, 50% (Or initialized).
- the update management unit 130 when the person attribute that is not estimated from the face information of the user among the person attributes about the user is acquired through the feedback of the user, The initial value of the reliability of the person attribute obtained from the feedback of the user can be set to be higher than the initial value of the reliability of the person attribute. That is, according to an embodiment of the present invention, the person attribute information obtained from the user's feedback generated in the conversation is explicitly specified by the user. Therefore, the user attribute information, which is estimated from the user's face information, The acquired person attribute information can be treated as more accurate information.
- the communication unit 140 can perform a function of enabling data transmission / reception to / from the face information management unit 110, the dialogue management unit 120, and the update management unit 130 .
- the control unit 150 controls the flow of data between the face information management unit 110, the dialogue management unit 120, the update management unit 130, and the communication unit 140 . That is, the control unit 150 according to the present invention controls the flow of data from / to the outside of the conversation service providing system 100 or the data flow between the respective components of the conversation service providing system 100, ), The dialogue management unit 120, the update management unit 130, and the communication unit 140, respectively.
- FIG. 2 is a diagram illustrating a situation in which a conversation service according to an exemplary embodiment of the present invention is provided.
- FIG. 3 is a diagram illustrating a process of providing a conversation service according to an exemplary embodiment of the present invention.
- FIG. 4 is a diagram illustrating an exemplary dialog template according to an embodiment of the present invention.
- the autonomic behavior robot 300 including the conversation service providing system 100 provides a conversation service to the user 200 .
- the autonomic behavior robot 300 may acquire the face information of the user 200 from the user 200.
- the autonomic robot 300 may recognize the user 200 corresponding to the obtained face information (310).
- the autonomic behavior robot 300 may be a known machine learning (or deep learning) robot such as a CNN (Convolution Neural Network) ) Algorithm to obtain information on the user 200 corresponding to the face information, and recognize the user 200 by referring to the obtained information (320).
- the autonomic behavior robot 300 can use a known clustering technique such as DBSCAN (Density Based Spatial Clustering of Application with Noise) algorithm to specify the face of the user 200 320).
- DBSCAN Density Based Spatial Clustering of Application with Noise
- the autonomic mobile robot 300 may store face information for storing, managing, or learning the face information that the obtained face information is the first recognized face information or the face information for which the user 200 is not specified And may further include a database (not shown).
- the autonomic behavior robot 300 estimates the person attribute of the user 200 from the face information of the user 200 to determine the initial information of the person attribute (330).
- the autonomic behavior robot 300 determines whether the recognized user 200 is a person of interest (320) Based on at least one of the reliability of the person attribute and the reliability of the person attribute.
- the autonomic behavior robot 300 may include a type of conversation (e.g., a name, a name, etc.) necessary for acquiring a person attribute called a name 331 that has not yet been acquired among various person attributes related to the user, Type 1) is determined to be a type of conversation to be provided to the user 200, and the determined conversation type 411 (i.e., type 1) among the plurality of conversation templates 360 grouped according to the person attribute or conversation type, Extracts the dialogue content to be provided to the user 200 from the target dialogue template corresponding to the person attribute 410 (i.e., name) of the corresponding user, or generates the dialogue content to be provided to the user 200 based on the target dialogue template can do.
- the autonomic behavior robot 300 according to the embodiment of the present invention can provide the user 200 with a dialogue message " What is your name often?
- the autonomic behavior robot 300 may include a dialog 332 for updating the reliability 333 of the person attribute, which is the age 332 among the plurality of person attributes related to the user 200, (E.g., type 2) as the type of conversation to be provided to the user 200 and determines the type of conversation 421, (E.g., Type 2) and the personality attribute 420 (i.e., age) of the user, or extracts the conversation content to be provided to the user 200 based on the target conversation template (340). ≪ / RTI >
- the autonomic behavior robot 300 according to the embodiment of the present invention may provide the user 200 with a dialogue entitled " Thorough skin care is required for thirty generations " (340).
- the autonomic behavior robot 300 may include a personality attribute such as a hobby (334) in which the reliability among the plurality of person attributes related to the user 200 is more than a predetermined level (335) (E.g., type 3) that attempts to engage in a friendly conversation with the user 200 is determined to be a type of conversation to be provided to the user 200, and the top of the plurality of conversation templates 360 grouped according to the character attribute or conversation type Extracts the conversation contents to be provided to the user 200 from the target conversation template corresponding to the determined conversation type 431 (i.e., type 3) and the person attribute (430, i.e., hobby) of the user, And may generate the conversation contents to be provided to the user 200 (340).
- the autonomic behavior robot 300 according to the embodiment of the present invention can provide the user 200 with a dialogue message " Kim 00 is really the best golf player ".
- the autonomic behavior robot 300 may be configured such that, for a person attribute whose reliability is higher than a predetermined level among the plurality of person attributes, a conversation type That is, only the above type 3) can determine the content of the conversation to be provided to the user. That is, a person attribute whose reliability is higher than a predetermined level is treated as correct information, and is not changed any more.
- the autonomic mobile robot 300 may further refer to the dialog database 350 that has been established with respect to the conversation contents associated with the conversation type.
- the autonomic behavior robot 300 updates at least one of the person attribute and the reliability of the person attribute based on the feedback of the user 200 on the provided conversation contents can do.
- the autonomic behavior robot 300 may be configured such that the feedback of the user 200 is " I am Kim OO " to the conversation contents provided "
- the personality attribute 331 of the personality attribute can be obtained from the feedback, and the reliability of the personality attribute 331 is determined by the initial value 50% of the reliability of the personality attribute obtained from the face information,
- the initial value can be set to a higher value of 75%.
- the autonomic behavior robot 300 may be configured such that the feedback of the user 200 to the conversation contents provided " 30 years requires thorough skin care & In the case of negative feedback such as " not so, ", the reliability of the person attribute of age 332 in the person attribute can be adjusted to be lower than 50% (333).
- the autonomic behavior robot 300 may be configured such that the feedback of the user 200 is " yes " to the conversation contents provided that " Kim 00 is really the best golf player & (334) of the personality attribute because there is no negative feedback of the user 200 and the type of the personality attribute of the personality attribute 334 is " The reliability 335 of the first and second memory units can be kept unchanged.
- the dialogue template 360 may include trigger information for analyzing the feedback of the user 200.
- the trigger information includes information about at least one of a recognition trigger for acquiring a person attribute, an affirmative trigger for a person attribute, a negative trigger for a person attribute, and a progress trigger for continuing the conversation .
- the dialog template corresponding to the dialog type (that is, the above type 1) 200 may include information on a trigger for recognizing the personality attribute from the feedback of the person. More specifically, if the conversation content associated with the conversation type is "What is your name?" And the feedback of the user 200 is "My name is kim oo" May be a recognition trigger for acquiring a person attribute.
- Information about a positive or negative trigger may be included. More specifically, the conversation associated with the conversation type is " a really cool male ", and the feedback of the user 200 is " I am a female? Or “I am a woman", the portion corresponding to " woman” may be a trigger for recognizing the negative of the person attribute.
- conversations matching the dialogue type may include a progress trigger to continue the conversation.
- conversations are associated with the dialog type is an "IU really'm the best singer", “think I do,” that the feedback of the users (200) "Yes” or “Yes” or “ I think so too "may be a progressive trigger to continue the conversation.
- the embodiments of the present invention described above can be implemented in the form of program instructions that can be executed through various computer components and recorded in a computer-readable recording medium.
- the computer-readable recording medium may include program commands, data files, data structures, and the like, alone or in combination.
- the program instructions recorded on the computer-readable recording medium may be those specifically designed and configured for the present invention or may be those known and used by those skilled in the computer software arts.
- Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CD-ROM and DVD, magneto-optical media such as floptical disks, medium, and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like.
- program instructions include machine language code, such as those generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like.
- the hardware device may be modified into one or more software modules for performing the processing according to the present invention, and vice versa.
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Description
Claims (10)
- 자율 행동 로봇을 이용하여 대화 서비스를 제공하는 방법으로서,획득되는 얼굴 정보에 대응하는 사용자를 인식하는 단계,상기 인식되는 사용자에 관한 인물 속성 및 상기 인물 속성의 신뢰도 중 적어도 하나에 기초하여 상기 사용자에게 제공될 대화 내용을 결정하는 단계, 및상기 대화 내용에 대한 상기 사용자의 피드백에 기초하여 상기 인물 속성 및 상기 인물 속성의 신뢰도 중 적어도 하나를 갱신하는 단계를 포함하는 방법.
- 제1항에 있어서,상기 결정 단계는,상기 인식되는 사용자가 관심 인물에 해당하는지 여부를 판단하는 단계를 더 포함하고,상기 관심 인물은, 얼굴 정보가 획득되는 빈도, 횟수 및 기간 중 적어도 하나를 참조하여 결정되는 관심 에너지가 소정 수준 이상으로 소정 기간 동안 유지되는 사용자인방법.
- 제1항에 있어서,상기 결정 단계는,상기 인물 속성 및 상기 인물 속성의 신뢰도에 기초하여 상기 사용자에게 제공될 대화 유형을 결정하는 단계, 및상기 인물 속성에 따라 그룹화되어 있는 대화 템플릿을 참조하여 상기 대화 유형에 연관되는 대화 내용을 결정하는 단계를 더 포함하는방법.
- 제1항에 있어서,상기 갱신 단계에서, 상기 피드백의 유형을 참조하여 상기 피드백과 연관된 상기 사용자의 인물 속성의 신뢰도를 갱신하는방법.
- 제1항에 있어서,상기 갱신 단계에서, 상기 인물 속성의 신뢰도가 소정 수준 이하로 갱신되는 경우에, 상기 인물 속성을 변경하는방법.
- 제5항에 있어서,상기 인물 속성이 변경되는 경우에, 상기 갱신되는 인물 속성의 신뢰도가 초기화되는방법.
- 제1항에 있어서,상기 인물 속성의 초기 정보는, 상기 사용자의 얼굴 정보로부터 추정되거나 상기 사용자의 피드백으로부터 획득되는방법.
- 제7항에 있어서,상기 사용자의 피드백으로부터 획득되는 인물 속성의 신뢰도의 초기값이 상기 사용자의 얼굴 정보로부터 추정되는 인물 속성의 신뢰도의 초기값보다 높게 설정되는방법.
- 제1항에 따른 방법을 실행하기 위한 컴퓨터 프로그램을 기록하는 비일시성의 컴퓨터 판독 가능 기록 매체.
- 자율 행동 로봇을 이용하여 대화 서비스를 제공하는 시스템으로서,획득되는 얼굴 정보에 대응하는 사용자를 인식하는 얼굴 정보 관리부,상기 인식되는 사용자에 관한 인물 속성 및 상기 인물 속성의 신뢰도 중 적어도 하나에 기초하여 상기 사용자에게 제공될 대화 내용을 결정하는 대화 관리부, 및상기 대화 내용에 대한 상기 사용자의 피드백에 기초하여 상기 인물 속성 및 상기 인물 속성의 신뢰도 중 적어도 하나를 갱신하는 갱신 관리부를 포함하는 시스템.
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JP2020518485A JP2021503112A (ja) | 2017-09-29 | 2017-09-29 | 自律行動ロボットを利用して対話サービスを提供する方法、システム、及び非一時的なコンピュータ読み取り可能な記録媒体 |
PCT/KR2017/011020 WO2019066110A1 (ko) | 2017-09-29 | 2017-09-29 | 자율 행동 로봇을 이용하여 대화 서비스를 제공하는 방법, 시스템 및 비일시성의 컴퓨터 판독 가능 기록 매체 |
US16/652,034 US20200251105A1 (en) | 2017-09-29 | 2017-09-29 | Method and system for providing conversation service by using autonomous behavior robot, and non-transitory computer-readable recording medium |
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- 2017-09-29 JP JP2020518485A patent/JP2021503112A/ja active Pending
- 2017-09-29 US US16/652,034 patent/US20200251105A1/en not_active Abandoned
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JP2003117866A (ja) * | 2001-10-16 | 2003-04-23 | Nec Corp | ロボット装置及びその制御方法 |
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