DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. 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.
Information Disclosure Statement
3. The Information Disclosure Statement filed 25 April 2025 has been fully considered by examiner. An annotated copy is included herewith.
Claim Rejections - 35 USC § 101
4. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
5. Claims 22-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claims are directed to a “computer program product” comprising modules, which is non-statutory. “During patent examination, the pending claims must be ‘given their broadest reasonable interpretation consistent with the specification.’ The Federal Circuit’s en banc decision in Phillips v. AWH Corp., 415 F.3d 1303, 1316, 75 USPQ2d 1321, 1329 (Fed. Cir. 2005) expressly recognized that the USPTO employs the ‘broadest reasonable interpretation’ standard.” See MPEP § 2111. The “computer program product” of claims 22-24 can be interpreted to include computer software per se, which is non-statutory. See MPEP § 2106.03(I): “Non-limiting examples of claims that are not directed to any of the statutory categories include: • Products that do not have a physical or tangible form, such as information (often referred to as ‘data per se’) or a computer program per se (often referred to as ‘software per se’) when claimed as a product without any structural recitations.”
Claim Rejections - 35 USC § 103
6. 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
7. Claims 1-11, 13-15, and 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Galitsky (US-2020/0265195) in view of Fang (US-2022/0020360).
Regarding claim 1: Galitsky discloses a method of conducting a task-oriented, engaged conversation between a computer and a human subject (fig 1 and [0066]-[0067] of Galitsky), comprising: defining a task and one or more key performance indicators for the task (fig 1(131,1320 and [0087]-[0093] of Galitsky – determines whether complaint is resolved or the result of distributed incompetence); determining an outline of a conversation with the subject in accordance with the task and one or more key performance indicators (figs 2-4, fig 5, [0099], [0104], [0118], and [0122]-[0123] of Galitsky – node-link representation of the hierarchical binary tree, which is an outline of the conversation in accordance with the task and if the complaint is resolved or the result of distributed incompetence); performing a dialogue with the subject in a series of acts (figs 2-6 and [0122]-[0125] of Galitsky), wherein each act comprises: (i) determining a strategic goal for the act (fig 1(132) and [0084]-[0085] of Galitsky – strategic goal of resolving the user’s problem/issue); (ii) formulating a statement to present to the subject and a manner of presenting the statement to the subject, in accordance with the goal, (iii) presenting the statement to the subject; (iv) receiving a response from the subject (fig 1(131,132), figs 2-5, [0084], [0103]-[0104], [0118], and [0124] of Galitsky – algorithm formulates and presents a statement to the user trying to resolve the user’s problem, and user responds, elaborates, and/or otherwise explains), (v) analyzing the response based on the text generated by the subject; and (vi) determining a strategic goal for a subsequent act in accordance with the response and a cumulative state of the conversation (figs 2-4 and [0099]-[0122] of Galitsky – response based on analysis of text over multiple iterations, each determining the goal for the next step based on the current (cumulative) state of the conversation).
Galitsky does not disclose analyzing the response based on both the text and visual cues generated by the subject.
Fang discloses analyzing the response based on both the text and visual cues generated by the subject (fig 4C and [0061] of Fang – response analyzed based on both the text data and visual data, such as facial expressions or other context clues).
Galitsky and Fang are analogous art because they are from the same field of endeavor, namely human-machine dialogue management. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art analyze the response based on both the text and visual cues generated by the subject. The motivation for doing so would have been to increase accuracy by including contextual clues. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Galitsky according to the relied-upon teachings of Fang to obtain the invention as specified in claim 1.
Regarding claim 2: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), further comprising performing the step of defining a task and one or more key performance indicators autonomously with the computer based on
predetermined constraints (fig 1(132), figs 2-4, [0084], [0103]-[0104], and [0118] of Galitsky – computer autonomously defines the task and performance indicators (determining whether the problem is solved or if there is distributed incompetence) based on predetermined conditions/constraints).
Regarding claim 3: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), further comprising: performing the step of defining a task and one or more key performance indicators by a human manager of the computer ([0005]-[0006] of Fang – can need a human manager to intervene). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 4: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), wherein, for at least one act in the series of acts, the steps of presenting and receiving the response comprise animating a digital human with at least one of a set of communication modes comprising audio, video, and text ([0040], [0049], [0051], and [0058] of Fang – digital human agent with audio, video, and text communication modes). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 5: Galitsky in view of Fang discloses the method of claim 4 (as rejected above), further comprising generating an appearance and speech mannerisms of the digital human in accordance with an expected preference of the human subject ([0051] and [0058] of Fang – speech mannerisms, facial expressions, and/or physical gestures). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 6: Galitsky in view of Fang discloses the method of claim 4 (as rejected above), further comprising selecting a personality type for the digital human in accordance with an expected preference of the human subject ([0051], [0058], and [0067] of Fang – intelligent agent engaging with user according to personalized type). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 7: Galitsky in view of Fang discloses the method of claim 4 (as rejected above), further comprising evaluating whether one or more key performance indicators may be better achieved with a person instead of the digital human, and, if the evaluating step results in a determination that said key performance indicators would be better achieved with the person, transitioning the conversation from the digital human to the person ([0058] and [0067] of Fang). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 8: Galitsky in view of Fang discloses the method of claim 4 (as rejected above), further comprising transitioning a delivery of the response during the conversation between different communication modes (figs 2-4 and [0117]-[0118] of Galitsky – transitions between the different modes shown in figs 2-4 (“elaboration”, “enablement”, etc.).
Regarding claim 9: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), further comprising: training the computer with a large-language model and logic regarding conducting of conversations derived from stored data ([0127]-[0128] of Galitsky – Natural Language Processing based on training and test text corpus).
Regarding claim 10: Galitsky in view of Fang discloses the method of claim 9 (as rejected above), wherein the training step further comprises performing a fine-tuning of the large language model based on the logic ([0126]-[0129] of Galitsky – training and updating of the NLP model).
Regarding claim 11: Galitsky in view of Fang discloses the method of claim 9 (as rejected above), wherein the stored data comprises one or more of: (1) previously recorded conversations involving the computer; (2) previously recorded conversations from other media; and (3) industry research ([0128]-[0129] of Galitsky – previous training and test text corpus; [0013], [0043], and [0054] of Fang – conversation history and flow). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 13: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), wherein the step of analyzing the response comprises analyzing the text and visual cues as they are received in real time (fig 4B, [0043], and [0059] of Fang). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 14: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), further comprising performing a post-conversation analysis, and using results of the post-conversation analysis to improve subsequent performance of the computer ([0094]-[0097] of Fang – uses analysis of dialogue history to improve later performance). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 15: Galitsky in view of Fang discloses the method of claim 14 (as rejected above), wherein the post-conversation analysis includes analysis regarding optimization of the outline, optimization of each statement that was presented, and achievement of the one or more key performance indicators ([0106]-[0111] of Fang). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Regarding claim 22: Galitsky in view of Fang discloses a computer program product (fig 1(101), fig 50, [0084]-[0085], and [0591]-[0592] of Galitsky) for conducting a task-oriented, engaged conversation between a computer and a human subject (fig 1 and [0066]-[0067] of Galitsky), comprising: a cognitor module for: defining a task and one or more key performance indicators for the task (fig 1(131,1320 and [0087]-[0093] of Galitsky – determines whether complaint is resolved or the result of distributed incompetence); determining an outline of a conversation with the subject in accordance with the key performance indicator (figs 2-4, fig 5, [0099], [0104], [0118], and [0122]-[0123] of Galitsky – node-link representation of the hierarchical binary tree, which is an outline of the conversation in accordance with the task and if the complaint is resolved or the result of distributed incompetence); and, during performance of a dialogue with the subject in a series of acts (figs 2-6 and [0122]-[0125] of Galitsky), analyzing responses by the subject based on text generated by the subject, and determining a strategic goal for each act in accordance with responses received from the subject and a cumulative state of the conversation (figs 2-4 and [0099]-[0122] of Galitsky – response based on analysis of text over multiple iterations, each determining the goal for the next step based on the current (cumulative) state of the conversation); and a communicator module for: formulating a statement to present to the subject and a manner of presenting the statement to the subject, in accordance with the goal, presenting the statement to the subject, and receiving a response from the subject (fig 1(131,132), figs 2-5, [0084], [0103]-[0104], [0118], and [0124] of Galitsky – algorithm formulates and presents a statement to the user trying to resolve the user’s problem, and user responds, elaborates, and/or otherwise explains).
Fang discloses analyzing responses based on both the text and visual cues generated by the subject (fig 4C and [0061] of Fang – response analyzed based on both the text data and visual data, such as facial expressions or other context clues).
Galitsky and Fang are analogous art because they are from the same field of endeavor, namely human-machine dialogue management. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art analyze responses based on both the text and visual cues generated by the subject. The motivation for doing so would have been to increase accuracy by including contextual clues. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Galitsky according to the relied-upon teachings of Fang to obtain the invention as specified in claim 22.
Regarding claim 23: Galitsky in view of Fang discloses the computer program product of claim 22 (as rejected above), wherein the communicator is configured to present the statement by animating a digital human with at least one of audio, video, and text ([0040], [0049], [0051], and [0058] of Fang – digital human agent with audio, video, and text communication modes). Galitsky and Fang are combined for the reasons set forth above with respect to claim 22.
Regarding claim 24: Galitsky in view of Fang discloses the computer program product of claim 23 (as rejected above), wherein the communicator is configured to generate an appearance and speech mannerisms of the digital human in accordance with an expected preference of the human subject ([0051] and [0058] of Fang – speech mannerisms, facial expressions, and/or physical gestures). Galitsky and Fang are combined for the reasons set forth above with respect to claim 22.
8. Claims 12, 16, 20 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Galitsky (US-2020/0265195) in view of Fang (US-2022/0020360), and in further view of obvious engineering design choice.
Regarding claim 12: Galitsky in view of Fang discloses the method of claim 1 (as rejected above), further comprising commencing each act within a computer processing level time period of completion of a previous act (fig 12 and [0117] of Fang – look-ahead built in in time frame of computer processing). Galitsky and Fang are combined for the reasons set forth above with respect to claim 1.
Galitsky in view of Fang does not expressly disclose commencing each act within approximately 200 milliseconds of completion of a previous act. However, it would have been an obvious engineering design choice to commence each act within approximately 200 milliseconds of completion of a previous act, since the specific time depends on the processing power of the computing device used. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Galitsky further according to the obvious engineering design choice to obtain the invention as specified in claim 12.
Regarding claim 16: Galitsky in view of Fang discloses the method of claim 1 (as rejected above). Galitsky in view of Fang does not disclose wherein the task is interviewing the subject for an employment position. However, it would have been an obvious engineering design choice to have the task be interviewing the subject for an employment position, since this is merely an intended use of the method.
Regarding claim 20: Galitsky in view of Fang discloses the method of claim 1 (as rejected above). Galitsky in view of Fang does not disclose wherein the task is selling a service or product to the subject. However, it would have been an obvious engineering design choice to have the task be selling a service or product to the subject, since this is merely an intended use of the method.
Regarding claim 21: Galitsky in view of Fang, and in further view of obvious engineering design choice, discloses the method of claim 20 (as rejected above), wherein the one or more key performance indicators comprise one or more of: classifying a lead, developing a lead, closing a sale, conducting a follow-up conversation after a sale, or conducting a full sales conversation (again, obvious engineering design choice since these are merely intended uses of the method).
Allowable Subject Matter
9. Claims 17-19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James A Thompson whose telephone number is (571)272-7441. The examiner can normally be reached M-F 8am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alicia Harrington can be reached at 571-272-2330. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES A THOMPSON/Primary Examiner, Art Unit 2615
