Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-3, 5-9, 13-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Soki (JP 6053847 B2, IDS) in view of Yokoyama (Wo 2020202862, IDS).
Regarding claim 1:
Soki (JP 6053847, IDS) discloses an action control system (Robot, 100, Fig. 1) comprising:
a memory (420); and
at least one processor (418) coupled to the memory; the at least one processor being configured to:
robot 100 has a conversation with the user 10 and provides video to the user 10 and representing the state of the user 10. Here, the information representing the state of the user 10 may include information representing the emotion of the user 10);
in FIG. 6 schematically shows information perceived by the perception processing unit 416. User recognition information 603 by the face recognition unit 414 are input; when smile detection information 604 is input from the facial expression recognition unit 413, the smile detection information 604 is converted to generate perceptual information 614. Further, the perception processing unit 416 perceives “Dad or lonely?” Based on the high probability of not smiling as perceived by the perception information 614 (perception information 615) of a question in a case in which the action of the user is recognized as the question (the behavior control unit 450 may control the utterance; understanding unit 412 to recognize the 3tterance content with higher accuracy. Further, the voice emotion recognition unit 411 may be controlled to recognize emotions with higher accuracy. Further, the facial expression recognition unit 413 may be controlled to recognize the facial expression with higher accuracy. The label generation unit 478 determines a situation and the response content recognized by the user reaction recognition unit 432 in response to the question to the user 10 see Fig. 1, 6, pg 3 and 9-10),
determine an action of enjoying being questioned by the user and an action of answering the question (Yes or positive), as an action to be executed, (For example, when the user 10 replies “Thank you, I am happy!”, The user reaction recognition unit 432 at robot 100,recognizes that the reaction of the user 10 is positive).
However, Soki does not specifically disclose an action of answering the question, as an action to be executed, in a case in which a score corresponding to the difficulty level is equal to or more than a threshold value.
Yokoyama, (US 2020202862) discloses an action of answering the question, as an action to be executed, in a case in which a score (value) corresponding to the difficulty level (i.e. name recognition answer by utterance) is equal to or more than a threshold value (predetermined value) (In the example of FIG. 1, the response generation device 10 executes response processing for information (hereinafter, referred to as “input information”) that triggers the generation of a response, such as a collected voice and a user’s action. For example, the response generator 10 recognizes the question posed by the user, outputs the answer to the question by voice, and displays the information about the question on the screen. Various known techniques may be used for the voice recognition process, the output process, and the like executed by the response generator 10. For example, when the user’s name recognition is equal to or less than a predetermined threshold value, the response generation unit 50 performs a process of not generating an operation such as content playback as a response even if the user’s utterance and the content name match).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Soki with the teaching of Yokoyama, thereby probability of generating a response can be increased according to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved. According to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved.
Regarding claim 6:
Soki (JP 6053847 B2) discloses an action control system (in Fig. 1) comprising:
a memory (420): and at least one processor (418) coupled to the memory (see Figs. 1, 3-4, page 7-9): the at least one processor being configured to: recognize an action of a user (10) (unit 418 performs processing for understanding the meaning of the perceptual information generated by the perception processing unit 416 using the meaning understanding rules 419 of the storage unit 420. For example, information representing the state of the user 10. Here, the information representing the state of the user 10 may include information representing the emotion of the user 10);
determine an action of enjoying being questioned by the user (i.e. ) and an action of answering the question, as an action to be executed (For example, when the user 10 replies “Thank you, I am happy!”, The user reaction recognition unit 432 at robot 100,recognizes that the reaction of the user 10 is positive).
Estimate a difficulty level (i.e. user’s utterance) of a question in a case in which the action of the user is recognized as the question (the response generation device 10 can accurately estimate the user’s intention by capturing the user’s behavior even when it is difficult to identify the user’s intention only by utterance); and
Soki does not specifically disclose in a case in which a score corresponding to the difficulty level is equal to or more than a threshold value, wherein the at least one processor
Yokoyama, (Wo 2020202862) discloses an action of answering the question, as an action to be executed, in a case in which a score (value) corresponding to the difficulty level (i.e. name recognition answer by utterance) is equal to or more than a threshold value (predetermined value) wherein the at least one processorthe response generation device 10 determines whether or not the same content has been uttered by the user a predetermined number of times or more before the user utters the activation word. Then, when the response generation device 10 determines that the same content has been uttered a predetermined number of times or more, it determines that the user wants to activate the response generation device 10 with the utterance, and changes the activation word. In the example of FIG. 1, the response generation device 10 executes response processing for information (hereinafter, referred to as “input information”) that triggers the generation of a response, such as a collected voice and a user’s action. For example, the response generator 10 recognizes the question posed by the user, outputs the answer to the question by voice, and displays the information about the question on the screen. Various known techniques may be used for the voice recognition process, the output process, and the like executed by the response generator 10. For example, when the user’s name recognition is equal to or less than a predetermined threshold value, the response generation unit 50 performs a process of not generating an operation such as content playback as a response even if the user’s utterance and the content name match, see Fig. 1, page 13-14).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Soki with the teaching of Yokoyama, thereby probability of generating a response can be increased according to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved. According to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved.
Regarding claims 2 and 7:
Soki (JP 6053847 B2) in view of Yokoyama discloses wherein the at least one processor determines an action of enjoying being questioned by the user and an action of answering the question (see Soki Fig. 3-4, pg ) and Yokoyama (Fig. 1, Pg )
Soki in view of Yokoyama discloses the action to be executed, in a case in which an accumulated value of the score (i.e. value ) is equal to or more than a threshold value (the perception processing unit 416 counts among users whose smile level exceeds a predetermined value, see Soki Fig. 1, 3-4, pg ).
, or in a case in which a number of times of the score corresponding to the difficulty level being equal to or more than the threshold value is equal to or more than a predetermined number of times (see Soki Figs. 3-4 and Yokoyama Fig. 1, pg. ). Same motivation as applied to claim 1.
Regarding claim 3:
Soki (JP 6053847 B2) discloses wherein the at least one processor estimates a difficulty level (i.e. utter in situation) of a question in consideration of an age (birthday) of the user (the meaning understanding unit 418 recognizes that the situation is different from the usual situation, the behavior determination unit 440 determines to ask the user 10 a question to confirm the situation. For example, in a case where the label “Yoshiko-chan’s birthday” is determined, if it is determined that many people are recognized, the behavior control unit 450 determines “Yoshiko-chan ’s birthday party? ”Is output from the speaker of the control target 452).
Regarding claim 8:
Soki in view of Yokoyama discloses wherein the at least one processor discloses the response generation device 10 determines whether or not the same content has been uttered by the user a predetermined number of times or more before the user utters the activation word. Then, when the response generation device 10 determines that the same content has been uttered a predetermined number of times or more, it determines that the user wants to activate the response generation device 10 with the utterance, and changes the activation word. In the example of FIG. 1, the response generation device 10 executes response processing for information (hereinafter, referred to as “input information”) that triggers the generation of a response, such as a collected voice and a user’s action). Same motivation as applied to claim 6.
Regarding claim 9:
Soki in view of Yokoyama discloses wherein the at least one processor on an age or gender of the user as the attribute of the user (acquisition unit 40 may acquire attribute information such as the age and gender of the user (speaker). For example, the acquisition unit 40 may acquire the attribute information of the user registered in advance by the user. The acquisition unit 40 acquires information such as the user’s gender, age, and place of residence, for example. The acquisition unit 40 may acquire the attribute information of the user by recognizing the image captured by the sensor 20). Same motivation as applied to claim 6.
10 – 12. (Cancelled).
Regarding claim 13:
Soki (JP 6053847, IDS) discloses an action control system (Robot, 100, Fig. 1) comprising:
a memory (420); and
at least one processor (418) coupled to the memory; the at least one processor being configured to:
robot 100 has a conversation with the user 10 and provides video to the user 10 and representing the state of the user 10. Here, the information representing the state of the user 10 may include information representing the emotion of the user 10);
in FIG. 6 schematically shows information perceived by the perception processing unit 416. User recognition information 603 by the face recognition unit 414 are input; when smile detection information 604 is input from the facial expression recognition unit 413, the smile detection information 604 is converted to generate perceptual information 614. Further, the perception processing unit 416 perceives “Dad or lonely?” Based on the high probability of not smiling as perceived by the perception information 614 (perception information 615) of a question in a case in which the action of the user is recognized as the question (the behavior control unit 450 may control the utterance; understanding unit 412 to recognize the 8tterance content with higher accuracy. Further, the voice emotion recognition unit 411 may be controlled to recognize emotions with higher accuracy. Further, the facial expression recognition unit 413 may be controlled to recognize the facial expression with higher accuracy. The label generation unit 478 determines a situation and the response content recognized by the user reaction recognition unit 432 in response to the question to the user 10 see Fig. 1, 6), and as an action to be executed by a robot.
Soki does not specifically disclose select one answer mode from a plurality of answer modes based on a content of the question.
Yokoyama disclose select one answer mode from a plurality of answer modes based on a content of the question, and as an action to be executed by a robot (interactive processing via text data, such as chatting with a user using a robot response generative device 10, see Fig 1. For example, the response generation device 10 may perform a conversation domain estimation process based on the contents of conversations by other plurality of surrounding users before the user speaks. For example, when a plurality of other users around the user are having a conversation related to going out, the response generator 10 determines that the conversation is a domain related to “going out” from the analysis result of words included in the conversation. After that, when there is an utterance from the user such as “What is tomorrow?”, The response generation device 10 extracts the operation related to “going out” and generates a response to the user. As an example, the response generator 10 extracts “weather information” as an operation related to “going out” and generates a response such as “it will be fine tomorrow”. Alternatively, the response generator 10 extracts “schedule information” as an operation related to “going out” and generates a response such as “the schedule is open tomorrow”.
In this way, the response generation device 10 can perform a natural response for the user who has spoken by estimating the intention of the user’s incomplete utterance by using the dialogue history of another user or the like. The response generation device 10 may generate a response as the dialogue history of another user based on the dialogue history acquired from the other device via the cloud as well as the user located on the spot).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Soki with the teaching of Yokoyama, thereby probability of generating a response can be increased according to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved. According to the user’s intention, so that the user’s satisfaction in the dialogue processing can be improved.
Regarding claim 14:
Soki (JP 6053847) discloses wherein the answer mode includes a conversation mode in which the user (10) mainly has a conversation with the robot (100, Fig. 12), and the at least one processor output voice of utterance content in greater mode, thank you I am happy ) than a reaction in other answer modes (FIG. 12 schematically shows actions performed by the 100 to determined that the date is the date of birth and the user’s 10 attribute information, the behavior determination unit 440 of robot 100 asks the user 10 to confirm whether the date is the birthday. To decide. In this case, for example, the behavior control unit 450 of robot 100 causes the speaker of the control target 452 to output the voice of the utterance content “Mr. XX, today is a birthday. Happy birthday!”. Thereafter, the user reaction recognition unit 432 recognizes whether the reaction of the user 10 is positive or negative from the utterance content of the user 10. For example, when the user 10 replies “Thank you, I am happy!”, The user reaction recognition unit 432 recognizes that the reaction of the user 10 is positive; in this case robot 100 being happy.
Regarding claim 15:
Soki discloses wherein the answer mode includes a study mode in which the user is taught by the robot, and the at least one processor sets a reaction of the robot being happy in the study mode to be less than a reaction in other answer modes ( thereafter, the user reaction recognition unit 432 recognizes whether the reaction of the user 10 is positive or negative from the utterance content of the user 10. For example, when the user 10 replies “Thank you, I am happy!”, The user reaction recognition unit 432 recognizes that the reaction of the user 10 is positive; in this case robot 100 being happy).
Regarding claim 16:
Soki discloses wherein the answer mode includes a consultation mode in which the user gives consultation to the robot, and the at least one processor suppresses a reaction of the robot being happy in the consultation mode (the user reaction recognition unit 432 recognizes whether the reaction of the user 10 is positive or negative from the utterance content of the user 10. For example, when the user 10 replies “Thank you, I am happy!”, The user reaction recognition unit 432 recognizes that the reaction of the user 10 is positive).
Claim(s) 4-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Soki (JP 6053847 B2) in view of Yokoyama (Wo 2020202862) and further in view of Ishizaki (JP 2006061632 A).
Regarding claim 4:
Soki (JP 6053847 B2) does not specifically disclose wherein the at least one processor reduces the difficulty level of the question to be estimated as the age of the user decreases.
Ishizaki (JP 2006061632 A) discloses at least one processor reduces the difficulty level of the question (i.e. less difficulties voiceprint) to be estimated as the age of the user decreases (young age) (Age can also be estimated to some extent from the voiceprint. Human voice begins to deteriorate after age 25. For example, if you pronounce the word “A” for a long time, the waveform of the young person has less fluctuation, but this fluctuation tends to increase with age, pg 16-18 ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Soki with the teaching of Yokoyama and Ishizaki, thereby determining individual emotions and personalities with higher accuracy.
Regarding claim 5:
Soki (JP 6053847 B2) in view of Kokoyams and Ishizaki discloses wherein the at least one processor sets the difficulty level of the question to be estimated to be constant (deteriorate) in a case in which the age of the user exceeds a predetermined threshold value (i.e. after age 25, page 16-18)
Pertinent art of record
Pertinent art of record US 20030101151 A1 discloses an interactive device.
Inquiry
4. Any inquiry concerning this communication or earlier communication from the examiner should be directed to Shaheda Abdin whose telephone number is (571) 270-1673.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ke Xiao could be reached at (571) 272-7776. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHAHEDA A ABDIN/Primary Examiner, Art Unit 2627
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