DETAILED ACTION
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 .
This is a non-final office action on merits. Claims 1-3 and 5-6 are currently pending and are addressed below.
The examiner notes that the fundamentals of the rejection are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Additionally, the examiner notes that the reference to page numbers refers to that inscribed on the reference rather than the total number of document pages.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/08/2026 has been entered.
Response to Arguments
Applicant's arguments, filed 04/08/2026, regarding the 35 U.S.C 102(a)(2) rejection of claims 1-3, 5, and 6 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1-3 and 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Melya Boukheddimi et al. (“Robot Dance Generation with Music Based Trajectory Optimization), hereinafter referred to as Boukheddimi, in view of Nakajima Takatomo et al. (JP20040066351A), hereinafter referred to as Takatomo.
Regarding claim 1, Boukheddimi discloses: an apparatus control device for controlling an apparatus, the apparatus control device comprising (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance, which discloses a general robot control system) , at least one processor configured to:
apply a first change to emotion data stored in a memory, wherein the emotion data represents a pseudo-emotion of the apparatus and the first change is based on a key of a
performance sound acquirable immediately after start of a performance, wherein the first change sets initial emotion data for the performance (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis, which discloses the process of mapping music features to various poses and states via an optimization method; spectral information is extracted from an audio signal that includes melody (pitch) and beat structures which are then mapped to corresponding pose and states of a dance choreography, this means that a first change to emotion data (the music features used to determine the robot’s behavior) which represents an initial pseudo-emotion of the apparatus (robot’s internal state or pose) and the first change is based on a key (pitch or beat) of a performance sound (audio signal) in a performance)
determine a predetermined time has lapsed from a start of the performance and in response to a lapse of the predetermined time from the start of the performance: determine a constancy of a performance speed of the performance sound (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis which discloses determining time sequences (a feature space within a window of time) in the form of beat timing used in response to tie a sequence of choreography configurations, this means that a constancy (averaging between beat times and global tempo) of performance speed is determined in response to a lapse of the predetermined time from the start of the performance)
based on the emotion data with the first change and the second change applied determine a control coefficient of an action of the apparatus that causes the apparatus to coordinate with the performance (see at least Boukheddimi, pg.3071-3072, A. Music Analysis, which discloses the process of mapping music features to various poses and states via an optimization method; spectral information is extracted from an audio signal that includes melody (pitch) and beat structures which are then mapped to corresponding pose and states of a dance choreography, this means that a change to emotion data (the music features used to determine the robot’s behavior) which represents a pseudo-emotion of the apparatus (robot’s internal state or pose) and the change is based on a key (pitch or beat) of a performance sound (audio signal) in a performance; Fig.3 discloses the cycle through updated extracted features which maps them to poses throughout the continuous choreography, this means a second change is implied; pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame)
control an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame; B. Method 2: Initiate Choreography, discloses an example where the optimal controller’s determined control coefficient (trajectories based on predetermined choreography) is initiated to cause the robot to perform the predetermined choreography, this means control an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance)
Boukheddimi is silent on, however, in the same field of endeavor, Takatomo teaches: compare the determined constancy with a threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
It would have been obvious to a person of ordinary skill in the art to modify Boukheddimi to include compare the determined constancy with a threshold, based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed, and wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold as taught by Takatomo. Incorporating the teachings of Takatomo would allow for an improvement to the base device of Boukheddimi which controls the operation of the operation, further, using sensibility data with a relative threshold, allowing for more fine-tuned poses and determinations.
Regarding claim 2, Boukheddimi discloses: the apparatus control device according to claim 1, wherein the at least one processor changes a pseudo-personality of the apparatus in accordance with at least one of the key of the performance and the constancy of the performance (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis, which discloses the process of mapping music features to various poses and states via an optimization method; spectral information is extracted from an audio signal that includes melody (pitch) and beat structures which are then mapped to corresponding pose and states of a dance choreography, this means that a first change to emotion data (the music features used to determine the robot’s behavior) which represents a pseudo-emotion of the apparatus (robot’s internal state or pose) and the first change is based on a key (pitch or beat) of a performance sound (audio signal) in a performance)
Regarding claim 3, Boukheddimi discloses: the apparatus control device according to claim 2, wherein the at least one processor is further configured to control the actuator in accordance with the changed pseudo-personality of the apparatus (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame; B. Method 2: Initiate Choreography, discloses an example where the optimal controller’s determined control coefficient (trajectories based on predetermined choreography) is initiated to cause the robot to perform the predetermined choreography, this means control an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance)
Regarding claim 5, Boukheddimi discloses: An apparatus control method (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance, which discloses a general robot control system) for controlling an apparatus, the apparatus control method comprising:
applying, by at least one processor, a first change to emotion data stored in a memory, wherein the emotion data represents a pseudo-emotion of the apparatus and the first change is based on a key of a performance sound acquirable immediately after start of a performance, wherein the first change sets initial emotion data for the performance (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis, which discloses the process of mapping music features to various poses and states via an optimization method; spectral information is extracted from an audio signal that includes melody (pitch) and beat structures which are then mapped to corresponding pose and states of a dance choreography, this means that a first change to emotion data (the music features used to determine the robot’s behavior) which represents a pseudo-emotion of the apparatus (robot’s internal state or pose) and the first change is based on a key (pitch or beat) of a performance sound (audio signal) in a performance)
determining, by the at least one processor, a predetermined time has lapsed from a start of the performance and in response to a lapse of the predetermined time from the start of the performance determining, by at least one processor, a constancy of a performance speed of the performance sound (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis which discloses determining time sequences (a feature space within a window of time) in the form of beat timing used in response to tie a sequence of choreography configurations, this means that a constancy (averaging between beat times and global tempo) of performance speed is determined in response to a lapse of the predetermined time from the start of the performance)
based on the emotion data with the first change and second change applied, determining, by the at least one processor, a control coefficient of an action of the apparatus that causes the apparatus to coordinate with the performance (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame)
controlling, by the at least one processor, an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame; B. Method 2: Initiate Choreography, discloses an example where the optimal controller’s determined control coefficient (trajectories based on predetermined choreography) is initiated to cause the robot to perform the predetermined choreography, this means control an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance)
Boukheddimi is silent on, however, in the same field of endeavor, Takatomo teaches: compare the determined constancy with a threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
It would have been obvious to a person of ordinary skill in the art to modify Boukheddimi to include compare the determined constancy with a threshold, based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed, and wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold as taught by Takatomo. Incorporating the teachings of Takatomo would allow for an improvement to the base device of Boukheddimi which controls the operation of the operation, further, using sensibility data with a relative threshold, allowing for more fine-tuned poses and determinations.
Regarding claim 6, Boukheddimi discloses: A non-transitory recording medium storing a program (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance, which discloses a general robot control system), the program causing a computer to execute processing comprising:
applying, by at least one processor, a first change to emotion data stored in a memory, wherein the emotion data represents a pseudo-emotion of the apparatus and the first change is based on a key of a performance sound acquirable immediately after start of a performance, wherein the first change sets initial emotion data for the performance (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis, which discloses the process of mapping music features to various poses and states via an optimization method; spectral information is extracted from an audio signal that includes melody (pitch) and beat structures which are then mapped to corresponding pose and states of a dance choreography, this means that a first change to emotion data (the music features used to determine the robot’s behavior) which represents a pseudo-emotion of the apparatus (robot’s internal state or pose) and the first change is based on a key (pitch or beat) of a performance sound (audio signal) in a performance)
determining, by the at least one processor, a predetermined time has lapsed from a start of the performance and in response to a lapse of the predetermined time from the start of the performance determining, by at least one processor, a constancy of a performance speed of the performance sound (see at least Boukheddimi, pg.3070, II. Mathematical Formulation of Dance; pg.3071-3072, A. Music Analysis which discloses determining time sequences (a feature space within a window of time) in the form of beat timing used in response to tie a sequence of choreography configurations, this means that a constancy (averaging between beat times and global tempo) of performance speed is determined in response to a lapse of the predetermined time from the start of the performance)
based on the emotion data with the first change and the second change applied, determining, by the at least one processor, a control coefficient of an action of the apparatus that causes the apparatus to coordinate with the performance (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame)
controlling, by the at least one processor, an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance (see at least Boukheddimi, pg.3072-3073, C. Choreography Timing Optimization, which discloses the determination of a control coefficient (optimal trajectories) based on the predetermined choreography, that causes the apparatus (robot) to coordinate with the performance; A. Method 1: Expert Choreography discloses an example of the beat extraction and control coefficient determined to coordinate a choreography performance based within a time frame; B. Method 2: Initiate Choreography, discloses an example where the optimal controller’s determined control coefficient (trajectories based on predetermined choreography) is initiated to cause the robot to perform the predetermined choreography, this means control an actuator according to the control coefficient to cause the apparatus to execute the action that coordinates with the performance)
Boukheddimi is silent on, however, in the same field of endeavor, Takatomo teaches: compare the determined constancy with a threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold (see at least Takatomo, pg.19, par.8-9, which discloses how the constancy is compared against a threshold, an example of the second change increasing the initial emotion data when the constancy is determined larger than or equal to the compared threshold and a scenario indicative of decreasing the initial emotion data when the constancy is less than the threshold; pg.20, which discloses various conditions of comparison results from the determined constancy against the threshold, where changes (second change) to the initial emotion data is based on the constancy of the performance speed and emotion parameter, indicative of various movements)
It would have been obvious to a person of ordinary skill in the art to modify Boukheddimi to include compare the determined constancy with a threshold, based on a result of comparison between the determined constancy and the threshold, apply a second change to the initial emotion data set by the first change and stored in the memory, wherein the second change is based on the constancy of the performance speed, and wherein the second change increases the initial emotion data when the constancy is greater than or equal to the threshold, and decreases the initial emotion data when the constancy is less than the threshold as taught by Takatomo. Incorporating the teachings of Takatomo would allow for an improvement to the base device of Boukheddimi which controls the operation of the operation, further, using sensibility data with a relative threshold, allowing for more fine-tuned poses and determinations.
Conclusion
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/KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664
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