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 .
Claim(s) 1-20 is/are pending and has/have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/08/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 1 is objected to because of the following informalities: the claim recites “a voice sample” in line 15. The Examiner suggests amending the claim(s) to recite –the voice sample-- in order to maintain clear antecedent basis. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites “the input”, which is lacking in antecedent basis.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 4-12, and 16-19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 6, 8, and 9 of U.S. Patent No. 12197409. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the issued patent/co-pending application anticipate the claims of the instant application. Please see below for the mapping in the table, where the bolded limitations indicate the corresponding limitations between the issued patent/co-pending application and instant application. With respect to the dependent claims, each of the claims map to a corresponding dependent claim of the issued patent/co-pending application or are found within the scope of the independent claim.
With respect to each of the dependent claims and independent claims, each claim corresponds numerically. Please see mapping that follows: Instant application claim (I), Issued Patent/Co-Pending App (P) - Claim 1 (I):Claim 1 (P), Claim 4 (I):Claim 6 (P), Claim 5 (I):Claim 8 (P), Claim 6 (I):Claim 1 (P), Claim 7 (I):Claim 1 (P), Claim 8 (I):Claim 9 (P), Claim 9 (I):Claim 1 (P), Claim 10 (I):Claim 2 (P), Claim 11 (I):Claim 6 (P), Claim 12 (I):Claim 9 (P), Claim 16 (I):Claim 1 (P), Claim 17 (I):Claim 6 (P), Claim 18 (I):Claim 9 (P), Claim 19 (I):Claim 2.
Instant Application: 19013423
Issued Patent: 12197409
Claim 1: An artificial intelligence (Al) system for interactive entertainment, comprising:
a software platform including a server including at least one processor and at least one memory including at least one database;
wherein the software platform implements a virtual assistant (VA) service;
wherein the VA service is operable to construct at least one user profile and at least one artificial personality profile, wherein the at least one user profile and the at least one artificial personality profile are stored on the at least one database;
wherein the artificial personality profile is based on a historical, public, fictional, or non- fictional figure;
wherein the VA service is operable to construct the at least one artificial personality profile from media inputs created by and/or about the historical, public, fictional, or non-fictional figure, including a video, an audio, and/or text;
wherein the VA service receives at least one video recording and/or at least one audio recording of a voice sample of the historical, public, fictional, or non-fictional figure,
wherein the at least one audio recording of a voice sample is used to create a voice model;
wherein the VA service stores the voice model in the at least one database;
wherein the VA service receives a stimulus, wherein the stimulus includes a movement, a sound, an image, or a second video;
wherein the VA service is operable to construct a response to the stimulus using the voice model, wherein the response is based on the at least one artificial personality profile; and
wherein the response is an audio response.
Claim 1: An artificial intelligence (AI) system for interactive entertainment and education, comprising:
a software platform including a server including at least one processor and at least one memory including at least one database;
wherein the software platform is constructed and configured for communication with a user device;
wherein the software platform implements a virtual assistant (VA) service;
wherein the VA service is operable to construct at least one user profile and at least one artificial personality profile, wherein the at least one user profile and the at least one artificial personality profile are stored on the at least one database;
wherein the at least one user profile includes a personality score including an estimated emotional intelligence
(EI), an estimated emotional quotient (EQ), and an estimated intelligence quotient (IQ) score;
wherein the VA service is operable to construct the at least one artificial personality profile from media inputs
including a video, an audio, and/or text;
wherein the VA service receives at least one video recording and/or at least one audio recording of a voice, wherein the at least one audio recording of a voice sample is used to create a voice model;
wherein the VA service stores the voice model on the at least one database;
wherein the software platform sends a selected story to the user device, wherein the selected story is selected or created based on inputs received via the user device,
wherein the inputs include an audio input, a touchscreen input, and/or a click select input;
wherein a text-to-speak (TTS) engine converts a text of the selected story into an audio output using the voice
model;
wherein the audio output is played through the user device;
wherein the VA service receives a stimulus, wherein the stimulus includes a movement, a sound, an image, a second video, or a measurement of a EQ, IQ, or EI score below or in excess of a predetermined threshold value;
wherein the VA service is operable to construct a response
to the stimulus using the voice model, wherein the response is based on the at least one artificial personality profile and the personality score; and
wherein the response is an audio response.
System claim 9 of the instant application is rejected over system claim 1 of the issued patent/co-pending application using the same rationale as that provided in the table above for the system claims.
Method claim 16 of the instant application is rejected over system claim 1 of the issued patent/co-pending application using the same rationale as that provided in the table above for the system claims.
Regarding the differences between Claim 16 of the instant application and system claim 1 of the issued patent/co-pending application, it would have been obvious to one of ordinary skill in the art that the system limitation of the issued patent/co-pending application could be applied to performing the method as presented in the instant application.
As to claim(s) 2, this/these claim(s) are rejected over the issued patent/co-pending application in view of Murugeshan et al. (U.S. PG Pub No. 2018/0032884), as found in the IDS, hereinafter Murugeshan.
Please see the art rejections below for further detail.
As to claim(s) 3, 15, and 20, this/these claim(s) are provisionally rejected over the issued patent/co-pending application in view of Abramson et al. (U.S. PG Pub No. 2018/0293483), as found in the IDS, hereinafter Abramson.
Please see the art rejections below for further detail.
As to claim(s) 13 and 14, this/these claim(s) are rejected over the issued patent/co-pending application in view of Murugeshan, and further in view of Gabai et al. (U.S. Patent No. 6773344), as found in the IDS, hereinafter Gabai.
Please see the art rejections below for further detail.
Claims 1, 2, 5, 6-9, 11, 12, and 16-18 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 4 of U.S. Patent No. 11663182. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the issued patent/co-pending application anticipate the claims of the instant application. Please see below for the mapping in the table, where the bolded limitations indicate the corresponding limitations between the issued patent/co-pending application and instant application. With respect to the dependent claims, each of the claims map to a corresponding dependent claim of the issued patent/co-pending application or are found within the scope of the independent claim.
With respect to each of the dependent claims and independent claims, each claim corresponds numerically. Please see mapping that follows: Instant application claim (I), Issued Patent/Co-Pending App (P) - Claim 1 (I):Claim 1 (P), Claim 2 (I):Claim 1 (P), Claim 5 (I):Claim 1 (P), Claim 6 (I):Claim 1 (P), Claim 7 (I):Claim 1 (P), Claim 8 (I):Claim 4 (P), Claim 9 (I):Claim 1 (P), Claim 11 (I):Claim 1 (P), Claim 12 (I):Claim 4 (P), Claim 16 (I):Claim 1 (P), Claim 17 (I):Claim 1 (P), Claim 18 (I):Claim 1.
Instant Application: 19013423
Issued Patent: US 11663182
Claim 1: An artificial intelligence (Al) system for interactive entertainment, comprising:
a software platform including a server including at least one processor and at least one memory including at least one database;
wherein the software platform implements a virtual assistant (VA) service;
wherein the VA service receives a stimulus, wherein the stimulus includes a movement, a sound, an image, or a second video; (limitation moved for clarity)
wherein the VA service is operable to construct at least one user profile and at least one artificial personality profile, wherein the at least one user profile and the at least one artificial personality profile are stored on the at least one database;
wherein the artificial personality profile is based on a historical, public, fictional, or non- fictional figure;
wherein the VA service is operable to construct the at least one artificial personality profile from media inputs created by and/or about the historical, public, fictional, or non-fictional figure, including a video, an audio, and/or text;
wherein the VA service receives at least one video recording and/or at least one audio recording of a voice sample of the historical, public, fictional, or non-fictional figure,
wherein the at least one audio recording of a voice sample is used to create a voice model;
wherein the VA service stores the voice model in the at least one database;
wherein the VA service is operable to construct a response to the stimulus using the voice model, wherein the response is based on the at least one artificial personality profile; and
wherein the response is an audio response.
Claim 1: An artificial intelligence (AI) system for improved conversation and artificial personality development comprising:
a handheld toy, wherein the handheld toy includes at least one processor, at least one memory with at least one database, at least one motion sensor, at least one camera, at least one speaker, and at least one microphone;
a virtual assistant (VA) service hosted on at least one server, wherein the VA service includes at least one VA processor and at least one VA memory with at least one VA database;
wherein the at least one speaker and the at least one microphone are embedded in the handheld toy;
wherein the handheld toy is in network communication with the VA service;
wherein the handheld toy is operable to detect and record a stimulus and transmit the stimulus to the VA service via a network;
wherein the stimulus includes a movement of the handheld toy, a sound, an image, or a video;
wherein the VA service is operable to determine if the stimulus is a predefined movement, a speech input, a predefined face, or a gesture;
wherein the VA service is operable to extract user personality features from gestures, tones, keywords, and phrases of the stimulus and determine a user personality score based on the user personality features;
wherein the VA service is operable to construct at least one user profile, at least one user personality profile, and at least one artificial personality profile and store the at least one user profile, the at least one user personality profile, and the at least one artificial personality profile in the at least one VA database;
wherein the VA service is operable to construct the at least one artificial personality profile from media inputs including a video, an audio clip, and text;
wherein the VA service is operable to extract and correlate meanings, emotions, and ideas to the keywords of the media inputs, wherein the media inputs include media which is continuously imported from external data sources, analyzed using natural language processing (NLP), and matched to a predetermined semantic category, wherein the meanings, emotions, and ideas determined by the VA service to correlate to the keywords of the media inputs are stored on the VA database of the VA memory;
wherein constructing the at least one user profile includes matching the stimulus to personal data, including the user personality score, personally identifiable information, settings, and preferences;
wherein the at least one artificial personality profile includes a selection of characteristics and/or personality traits selected by a user, wherein the characteristics and/or personality traits are exhibited by the VA service,
wherein the VA service is operable to modify the artificial personality profile to include the selected characteristics and/or personality traits;
wherein constructing the at least one user personality profile and/or the at least one artificial personality profile includes:
receiving media inputs including a video, an audio clip, and text;
extracting personality features from gestures, tones, keywords, and phrases of the media inputs; and
determining a personality score based on the personality features of the media inputs, wherein the personality score includes an estimated emotional intelligence (EI), emotional quotient (EQ), and intelligence quotient (IQ) score, wherein the VA service is operable to receive a set goal EI, EQ, and/or IQ of the user and implement at least one exercise intended to achieve the set goal EI, EQ, and/or IQ of the user;
wherein the VA service is operable to determine an emotional state of the user from interaction data derived from interactions with the user and assign an emotional score to the emotion associated with the emotional state of the user;
wherein the VA service is operable to categorize words and phrases and correlate the words and phrases to the emotional state to determine the emotional state of the user;
wherein, upon determination that the emotional score exceeds or is below a predetermined threshold, the VA service sends an alert to a device connected to the VA service or calls the device connected to the VA service to allow the user to converse with a second party;
wherein at least one preconstructed artificial personality is purchased via connection to at least one external entity and downloaded to the at least one VA database, wherein the at least one preconstructed artificial personality is selected from a plurality of preconstructed artificial personalities available for purchase through the at least one external entity, wherein the at least one preconstructed artificial personality is configured to be selectively enabled on the handheld toy in real time upon download of the at least one preconstructed artificial personality;
wherein the at least one preconstructed artificial personality comprises at least one audio clip reciting a fact, quote, and/or catchphrase of a fictional character or a historical figure, wherein the VA service is operable to correlate the predefined movement, the speech input, the predefined face, or the gesture to the at least one audio clip using NLP, wherein the VA service is operable to play the at least one audio clip in response to the predefined movement, the speech input, the predefined face, or the gesture upon enabling of the at least one preconstructed artificial personality;
wherein the VA service is operable to construct a response, wherein the response is based on the personality score of the media inputs and the user personality score, and at least one recommendation for response to user interaction provided by a recommendation engine, and wherein the VA service is operable to transmit the response to the handheld toy;
wherein the response is a sound response and a movement response, an image response, and/or a video response;
wherein the sound response includes a voice, wherein the voice is derived from media clips or wherein the voice is simulated from analyzed speech patterns of the media clips;
wherein the handheld toy is operable to demonstrate the response;
wherein access to the at least one user profile, the at least one user personality profile, and the at least one artificial personality profile is restricted using facial analysis, wherein access to the at least one user profile, the at least one user personality profile, and the at least one artificial personality profile is granted upon recognition of facial features of at least one user associated with a user profile and verification of audio responses associated with an audio profile of at least one user associated with a user profile;
wherein the handheld toy is configured to change from a low-power mode to a normal-power mode upon recognition of the facial features of the at least one user associated with the user profile;
wherein the handheld toy is further configured to play an audio greeting upon recognition of the facial features of the at least one user associated with the user profile;
wherein the at least one speaker is embedded within an artificial mouth of the handheld toy;
wherein the at least one microphone is embedded within an artificial ear of the handheld toy; and
wherein the at least one camera is embedded within an artificial eye of the handheld toy.
System claim 9 of the instant application is rejected over system claim 1 of the issued patent/co-pending application using the same rationale as that provided in the table above for the system claims.
Method claim 16 of the instant application is rejected over system claim 1 of the issued patent/co-pending application using the same rationale as that provided in the table above for the system claims.
Regarding the differences between Claim 16 of the instant application and system claim 1 of the issued patent/co-pending application, it would have been obvious to one of ordinary skill in the art that the system limitation of the issued patent/co-pending application could be applied to performing the method as presented in the instant application.
As to claim(s) 3, 15, and 20, this/these claim(s) are rejected over the issued patent/co-pending application in view of Abramson.
Please see the art rejections below for further detail.
As to claim(s) 4, 10, 19, this/these claim(s) are rejected over the issued patent/co-pending application in view of Killalea et al. (US Patent No. 9418654), as found in the IDS, hereinafter Killalea.
Please see the art rejections below for further detail.
As to claim(s) 13, this/these claim(s) are rejected over the issued patent/co-pending application in view of Murugeshan.
Please see the art rejections below for further detail.
As to claim(s) 14, this/these claim(s) are rejected over the issued patent/co-pending application in view of Murugeshan, and further in view of Gabai.
Please see the art rejections below for further detail.
Claim Rejections - 35 USC § 101
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.
Claims 1-3 and 5-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim(s) 1, the limitation(s) of implement, construct, construct, receive, store, receive, and construct, as drafted, are processes that, under broadest reasonable interpretation, covers performance of the limitation in the mind and/or with pen and paper but for the recitation of generic computer components. More specifically, the mental process of a human performing a response service, writing down mannerisms and vocal characteristics of different individuals based on observed information, setting aside the written characteristics for later use, seeing and hearing another person ask a question, determining an answer where the delivery uses the mannerisms and vocal characteristics of a specific individual, and speaking the answer aloud using the mannerisms and vocal characteristics. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or with pen and paper but for the recitation of generic computer components, then it falls within the --Mental Processes-- grouping of abstract ideas. Accordingly, the claim(s) recite(s) an abstract idea.
This judicial exception is not integrated into a practical application because the recitation of system, server, and database reads to generalized computer components, based upon the claim interpretation wherein the structure is interpreted using [0111-116] in the specification. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) is/are directed to an abstract idea.
The claim(s) do(es) not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using generalized computer components to implement, construct, construct, receive, store, receive, and construct, amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim(s) is/are not patent eligible.
With respect to claim(s) 2, the claim(s) recite(s) determine an emotional state, which reads on a human using natural language cues to recognize what mood the other person is in. No additional limitations are present.
With respect to claim(s) 3, the claim(s) recite(s) combine, which reads on a human taking the mannerisms and vocal characteristics of different individuals and mixing them together to create a new set of mannerisms and vocal characteristics that are a blend of multiple people. No additional limitations are present.
With respect to claim(s) 5, the claim(s) recite(s) process, which reads on a human using natural language cues to evaluate the question being asked. No additional limitations are present.
With respect to claim(s) 6, the claim(s) recite(s) connect, load, and hold, which reads on a human storing written information in different files, and going to the files to retrieve the papers as needed. No additional limitations are present.
With respect to claim(s) 7, the claim(s) recite(s) offer and converse, which reads on a human letting a person choose which individual they’d like the human to impersonate when answering, and using the mannerisms and vocal characteristics of that individual when providing the answer. No additional limitations are present.
With respect to claim(s) 8, the claim(s) recite(s) create, store, receive, and enable, which reads on a human writing down the vocal characteristics for different people and putting them in respective files, having a person choose which voice they’d like to hear, and using the vocal characteristics of the chosen voice when responding. No additional limitations are present.
These claims further do not remedy the judicial exception being integrated into a practical application and further fail to include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3, and 5-7 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Abramson.
Regarding claim 1, Abramson teaches
An artificial intelligence (Al) system for interactive entertainment (a system of creating a conversational chat bot of a specific person including personality using a neural network, i.e. AI system [0014-5]), comprising:
a software platform including a server including at least one processor and at least one memory including at least one database (the system, which may include program modules for running software applications, i.e. software platform, creates a conversational chat bot, where components of a system may occur remotely, such as one or more server devices, i.e. hosted on a server, where the server can store data for one or more entities, i.e. database, on a system memory, i.e. memory, and has a processing unit, i.e. processor [0014],[0018-20],[0036]);
wherein the software platform implements a virtual assistant (VA) service (the system, i.e. software platform, creates and implements a conversational chatbot through an input processing unit, i.e. implements a virtual assistant (VA) service [0014-5],[0023-4]));
wherein the VA service is operable to construct at least one user profile and at least one artificial personality profile (the input processing unit, i.e. VA service, may store data by user identification, including social data of the user that includes characteristics of the user, as well as traits, attributes, and psychographic data, i.e. construct at least one user profile, the index engine of the input processing unit generates personality indices, where each index may be associated with a specific person or entity, and the person or entity may be a celebrity, historical figure, or fictional character, i.e. at least one artificial personality profile [0023-5],[0053]), wherein the at least one user profile and the at least one artificial personality profile are stored on the at least one database (data, i.e. at least one user profile and the at least one artificial personality profile, may be stored by the system in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stored on the at least one database [0014],[0019-20],[0024],[0036]);
wherein the artificial personality profile is based on a historical, public, fictional, or non- fictional figure (each index may be associated with a specific person or entity, and the person or entity may be a celebrity, historical figure, or fictional character, i.e. at least one artificial personality profile, i.e. based on a historical, public, fictional, or non-fictional figure [0023-5],[0053]);
wherein the VA service is operable to construct the at least one artificial personality profile from media inputs created by and/or about the historical, public, fictional, or non-fictional figure, including a video, an audio, and/or text (the index engine of the input processing unit, i.e. VA service, generates, i.e. operable to construct, personality indices, where each index may be associated with a specific person or entity, and the person or entity may be a celebrity, historical figure, or fictional character, i.e. at least one artificial personality profile, using social data that includes voice and image data, movies/television shows, and electronic news and articles, social media posts, and books or letters, i.e. media inputs created by and/or about the historical, public, fictional, or non-fictional figure, including a video, an audio, and/or text [0023-6],[0031],[0053]);
wherein the VA service receives at least one video recording and/or at least one audio recording of a voice sample of the historical, public, fictional, or non-fictional figure (the index engine of the input processing unit, i.e. VA service, accesses social data, i.e. receives, that includes voice and image data, such as recordings of interviews, and other audio and video data, i.e. at least one video recording and/or at least one audio recording of a voice sample of the historical, public, fictional, or non-fictional figure, where the voice recordings are used to generate a voice font of a specific person, i.e. voice sample of the historical, public, fictional, or non-fictional figure [0016:1-8],[0023-6],[0031],[0053]),
wherein the at least one audio recording of a voice sample is used to create a voice model (the voice recordings are used to generate a voice font of a specific person, i.e. the at least one audio recording of the voice sample is used to create a voice model [0016:1-8],[0023-6],[0031],[0053]);
wherein the VA service stores the voice model in the at least one database (data including the voice font data, i.e. voice model, may be stored by the input processing unit, i.e. VA service, in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stores…on the at least one database Fig. 2,[0014],[0019-20],[0024],[0036]);
wherein the VA service receives a stimulus, wherein the stimulus includes a movement, a sound, an image, or a second video (the chat bot, i.e. VA service, receives submitted dialogue from a user via an interface, i.e. receives a stimulus, where a device is able to receive audible signals from that user, i.e. a sound, as well as still images, i.e. an image, and a video stream, i.e. or a second video [0047],[0054]);
wherein the VA service is operable to construct a response to the stimulus using the voice model, wherein the response is based on the at least one artificial personality profile (the chat bot, i.e. VA service, generates a response to the received user dialogue, i.e. operable to construct a response to the stimulus, where the chat bot provides a response using the personality of the specific entity, i.e. based on the at least one artificial personality profile, as well as the voice font, i.e. using the voice model [0029],[0054]); and
wherein the response is an audio response (the chat bot generates a response to the received user dialogue, where a voice font is applied to the chat bot, and audible signals can be provided to the user, i.e. the response is an audio response [0029],[0047],[0054]).
Regarding claim 3, Abramson teaches claim 1, and further teaches
the at least one database is configured to store a plurality of artificial personalities, wherein the VA service is further configured to combine the plurality of artificial personalities to create a merged personality, wherein the merged personality includes one voice model (data stored on the server, i.e. at least one VA database is configured to store, may include multiple personality indexes, i.e. plurality of artificial personalities, such as a personalized personality index, and a generic personality index, where a personality index may include interaction rules that will govern how a personality index accesses multiple datasets, such as datasets from a specific person through their personality index and data from other users who also have personality indexes, where each personality index comprises social data, i.e. combine the custom personality with the at least one additional personality to create a merged personality, where the personality index contains voice font data, i.e. merged personality includes one voice model [0020],[0024],[0033:1-14],[0034:1-12]).
Regarding claim 5, Abramson teaches claim 1, and further teaches
the VA service processes the audio input using natural language processing (NLP) (the social data may be analyzed by the index engine, i.e. VA service processes, using natural language processing techniques, i.e. using natural language processing (NLP), where the social data includes voice recordings, i.e. the audio input [0024-6]).
Regarding claim 6, Abramson teaches claim 1, and further teaches
the system is operable to connect to an external server and database and load information from the external server, wherein the external server is operable to hold personality profiles, user profiles, and raw data corresponding to a specific user, or extracted data from the raw data corresponding to the specific user (data stored on the server and accessible to the interface, i.e. the system is operable to connect to an external server and database and load information from the external server, can include user profile data, i.e. user profiles, data stored by user identification including social data, i.e. raw data corresponding to a specific user, personality indexes, i.e. personality profiles, and voice font data, i.e. extracted data from the raw data corresponding to the specific user [0014],[0019-20],[0024-5]).
Regarding claim 7, Abramson teaches claim 6, and further teaches
the system is operable to offer a plurality of different specific personalities, wherein when selected, the system is further operable to converse with a user in the voice and personality of the specific personality selected (the conversational program may have access to one or more personality indexes, i.e. the system is operable to offer a plurality of different specific personalities, where the chat bot is operable to interact conversationally in the personality and with the voice font and image of the specific person associated with the personalized personality index, i.e. system is further operable to converse with a user in the voice and personality of the specific personality selected, where the request to generate the personality and modify a chat bot is received directly from a client, i.e. when selected [0025],[00031],[0034]).
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) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Abramson, in view of Murugeshan.
Regarding claim 2, Abramson teaches claim 1.
While Abramson provides receiving and generating a response to received user dialogue, Abramson does not specifically teach determining the emotional state of the user, and thus does not teach
the VA service is operable to determine an emotional state of a user based on the input using a natural language processing (NLP) engine.
Murugeshan, however, teaches the VA service is operable to determine an emotional state of a user based on the input using a natural language processing (NLP) engine (user interactions may be received in data formats including text, audio, and video, where the user is using a user device, and characteristics including emotions, keywords, expressions, and topics are extracted, i.e. determine an emotional state of a user based on the input [0022],[0036],[0084-5], where the system, i.e. VA service, may perform part-of-speech tagging, stop-word removal, and word sense disambiguation, i.e. using a natural language processing (NLP) engine, as well as mapping using a domain ontology using meaningful n-grams and synonyms, to determine the domain, and meaning of the keywords, as well as the mood of the user, i.e. determine an emotional state [0023],[0063]).
Abramson and Murugeshan are analogous art because they are from a similar field of endeavor in enabling dialog between a user and a device with an intelligent dialog system. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the receiving and generating a response to received user dialogue teachings of Abramson with the use of natural language processing functions to determine a user mood in the user interactions as taught by Murugeshan. It would have been obvious to combine the references to enable a system to provide adaptive responses to user interactions based on user personality (Murugeshan [0024]).
Claim(s) 4, 8-12, and 15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Abramson, in view of Killalea.
Regarding claim 4, Abramson teaches claim 1, and further teaches
the software platform is implemented on a smart home device, a toy, and/or a vessel… (the computing device may be a smart phone or other computer, i.e. implemented on a smart home device…or a vessel [0042],[0050]).
While Abramson provides generating a chat bot that interacts with a user using a specific personality and voice, Abramson does not specifically teach the selection and output of a story to the user, and thus does not teach
the software platform is implemented on a smart home device, a toy, and/or a vessel, wherein the software platform sends a selected story to the smart home device, the toy, and/or the vessel, wherein the selected story is selected or created based on inputs received via the smart home device, the toy, and/or the vessel, wherein the inputs include an audio input, a touchscreen input, and/or a click select input, wherein a text-to-speak (TTS) engine converts a text of the selected story into an audio output using the voice model, wherein the audio output is played through the smart home device, the toy, and/or the vessel.
Killalea, however, teaches the software platform is implemented on a smart home device, a toy, and/or a vessel, wherein the software platform sends a selected story to the smart home device, the toy, and/or the vessel, wherein the selected story is selected or created based on inputs received via the smart home device, the toy, and/or the vessel, wherein the inputs include an audio input, a touchscreen input, and/or a click select input (a user of a user computing device, such as a smart phone or entertainment device, i.e. implemented on a smart home device…or a vessel, selects a written work, along with character identities and voice options, i.e. story is selected or created based on inputs received via the smart home device…or the vessel, where the user may provide input via a GUI using an audio input device, a touch sensitive panel, or a pointing device, i.e. inputs include an audio input a touchscreen input and/or a click select input, and the server computing device using a program to perform a task, provides the written work to the user computing device, i.e. software platform implemented on a smart home device…or a vessel…sends a selected story (3:50-58),(9:51-20),(11:40-64),(12:55-63)), wherein a text-to-speak (TTS) engine converts a text of the selected story into an audio output using the voice model (the written work stored as text, and selected by the user, i.e. text of the selected story, is audibly rendered through a text-to-speech feature, i.e. TTS engine converts…into an audio output, where a voice for audibly rendering the written work may include a custom voice created by software based on a recording of the user’s speech, i.e. using the voice model (2:15-39),(4:10-17),(7:1-10),(11:40-64)), wherein the audio output is played through the smart home device, the toy, and/or the vessel (the written work is audibly rendered, i.e. audio output is played, at a user computing device, such as a smart phone, entertainment device, or electronic book reader, i.e. through the smart home device…or the vessel (2:15-25),(3:27-49),(4:1-17),(10:32-33)).
Abramson and Killalea are analogous art because they are from a similar field of endeavor in presenting information to a user with customized voices. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the generation of a chat bot that interacts with a user using a specific personality and voice teachings of Abramson with the audible rendering of a written work in a custom voice generated from recordings of user speech as taught by Killalea. It would have been obvious to combine the references to enable multiple users to view a single written work, where each user can select the set of character attributes they prefer, including custom voices for specific characters (Killalea (9:51-10:31)).
Regarding claim 9, Abramson teaches
An artificial intelligence (AI) system for interactive storytelling (a system of creating a conversational chat bot of a specific person including personality using a neural network, i.e. AI system [0014-5]), comprising:
a software platform including a server including at least one processor and at least one memory including at least one database (the system, which may include program modules for running software applications, i.e. software platform, creates a conversational chat bot, where components of a system may occur remotely, such as one or more server devices, i.e. hosted on a server, where the server can store data for one or more entities, i.e. database, on a system memory, i.e. memory, and has a processing unit, i.e. processor [0014],[0018-20],[0036]);
wherein the software platform is constructed and configured for communication with a user device (components of the system, i.e. software platform, may be employed remotely such as on a server device, where the server may perform components of the system and provide data to and from the client computing device through a network, i.e. constructed and configured for communication with a user device [0019],[0029:1-4],[0049-50]);
wherein the software platform implements a virtual assistant (VA) service (the system, i.e. software platform, creates and implements a conversational chatbot through an input processing unit, i.e. implements a virtual assistant (VA) service [0014-5],[0023-4]));
wherein the VA service is operable to construct at least one user profile and at least one user personality profile (the input processing unit, i.e. VA service, may store data by user identification, including social data of the user that includes characteristics of the user, as well as traits, attributes, and psychographic data, i.e. construct at least one user profile, the index engine of the input processing unit generates personality indices, where each index may be associated with a specific person or entity, and the person or entity may be a celebrity, historical figure, or fictional character, i.e. at least one artificial personality profile [0023-5],[0053]), wherein the at least one user profile and the at least one artificial personality profile are stored on the at least one database (data, i.e. at least one user profile and the at least one artificial personality profile, may be stored by the system in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stored on the at least one database [0014],[0019-20],[0024],[0036]);
wherein the VA service receives at least one video recording and/or at least one audio recording of a voice, wherein the at least one audio recording of a voice sample is used to create a voice model (the index engine of the input processing unit, i.e. VA service, accesses social data, i.e. receives, that includes voice and image data, such as recordings of interviews, and other audio and video data, i.e. at least one video recording and/or at least one audio recording of a voice, where the voice recordings are used to generate a voice font of a specific person, i.e. the at least one audio recording of the voice sample is used to create a voice model [0016:1-8],[0023-6],[0031],[0053]);
wherein the VA service stores the voice model on the at least one database (data including the voice font data, i.e. voice model, may be stored by the input processing unit, i.e. VA service, in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stores…on the at least one database Fig. 2,[0014],[0019-20],[0024],[0036]).
While Abramson provides generating a chat bot that interacts with a user using a specific personality and voice, Abramson does not specifically teach the selection and output of a story to the user, and thus does not teach
wherein the software platform sends a selected story to the user device, wherein the selected story is selected or created based on inputs received via the user device, wherein the inputs include an audio input, a touchscreen input, and/or a click select input;
wherein a text-to-speak (TTS) engine converts a text of the selected story into an audio output using the voice model; and
wherein the audio output is played through the user device.
Killalea, however, teaches wherein the software platform sends a selected story to the user device, wherein the story is selected or created based on inputs received via the user device, wherein the inputs include an audio input, a touchscreen input, and/or a click select input (a user of a user computing device selects a written work, along with character identities and voice options, i.e. story is selected or created based on inputs received via the user device, where the user may provide input via a GUI using an audio input device, a touch sensitive panel, or a pointing device, i.e. inputs include an audio input, a touchscreen input, and/or a click select input, and the server computing device using a program to perform a task, provides the written work to the user computing device, i.e. software platform sends a selected story to the user device (3:50-58),(9:51-20),(11:40-64),(12:55-63));
wherein a text-to-speak (TTS) engine converts the text of the selected story into an audio output using the voice model (the written work stored as text, and selected by the user, i.e. text of the selected story, is audibly rendered through a text-to-speech feature, i.e. TTS engine converts…into an audio output, where a voice for audibly rendering the written work may include a custom voice created by software based on a recording of the user’s speech, i.e. using the voice model (2:15-39),(4:10-17),(7:1-10),(11:40-64));
wherein the audio output is played through the user device (the written work is audibly rendered, i.e. audio output is played, at a user computing device, such as an electronic book reader, i.e. through the user device (2:15-25),(3:27-49),(4:1-17),(10:32-33)).
Abramson and Killalea are analogous art because they are from a similar field of endeavor in presenting information to a user with customized voices. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the generation of a chat bot that interacts with a user using a specific personality and voice teachings of Abramson with the audible rendering of a written work in a custom voice generated from recordings of user speech as taught by Killalea. It would have been obvious to combine the references to enable multiple users to view a single written work, where each user can select the set of character attributes they prefer, including custom voices for specific characters (Killalea (9:51-10:31)).
Regarding claim 16, Abramson teaches
A method for using an artificial intelligence (AI) system for interactive storytelling comprising (a system of creating a conversational chat bot of a specific person including personality using a neural network, i.e. AI system [0014-5]):
providing a software platform including a server including at least one processor and at least one memory including at least one database (the system, which may include program modules for running software applications, i.e. software platform, creates a conversational chat bot, where components of a system may occur remotely, such as one or more server devices, i.e. hosted on a server, where the server can store data for one or more entities, i.e. database, on a system memory, i.e. memory, and has a processing unit, i.e. processor [0014],[0018-20],[0036]), wherein the software platform is constructed and configured for network communication with a user device (components of the system, i.e. software platform, may be employed remotely such as on a server device, where the server may perform components of the system and provide data to and from the client computing device through a network, i.e. constructed and configured for network communication with a user device [0019],[0029:1-4],[0049-50]);
the software platform implementing a virtual assistant (VA) service (the system, i.e. software platform, creates and implements a conversational chatbot through an input processing unit, i.e. implements a virtual assistant (VA) service [0014-5],[0023-4]));
the VA service constructing at least one user profile including personally identifiable information (the input processing unit, i.e. VA service, may store data by user identification, including social data of the user that includes user profiles and accounts, images, voice recordings, handwritten letters, and characteristics of the user, as well as traits, attributes, and psychographic data, i.e. construct at least one user profile including personally identifiable information [0023-5],[0053]);
the VA service constructing at least one artificial personality profile from media inputs including a video clip, an audio clip, and/or text, wherein the at least one artificial personality profile is based on a historical, public, fictional, or non-fictional figure (the index engine of the input processing unit, i.e. VA service, generates, i.e. operable to construct, personality indices, where each index may be associated with a specific person or entity, and the person or entity may be a celebrity, historical figure, or fictional character, i.e. at least one artificial personality profile, using social data that includes voice and image data, movies/television shows, and electronic news and articles, social media posts, and books or letters, i.e. media inputs created by and/or about the historical, public, fictional, or non-fictional figure, including a video, an audio, and/or text [0023-6],[0031],[0053]), wherein the at least one artificial personality profile is stored on the at least one database (data, i.e. at least one artificial personality profile, may be stored by the system in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stored on the at least one database [0014],[0019-20],[0024],[0036]);
the VA service receiving at least one audio recording and/or at least one video recording of a voice sample from the user device, wherein the at least one audio recording and/or the at least one video recording of a voice sample is from the historical, public, fictional, or non-fictional figure (the index engine of the input processing unit, i.e. VA service, accesses social data, i.e. receives, that includes voice and image data, such as recordings of interviews, and other audio and video data, i.e. at least one video recording and/or at least one audio recording of a voice sample of the historical, public, fictional, or non-fictional figure, where the voice recordings are used to generate a voice font of a specific person, i.e. voice sample of the historical, public, fictional, or non-fictional figure [0016:1-8],[0023-6],[0031],[0053]);
the VA service creating a voice model… from the audio clip of the media inputs, the video clip of the media inputs, the at least one audio recording and/or the at least one video recording of the voice sample (the index engine of the input processing unit, i.e. VA service, accesses social data that includes voice and image data, such as recordings of interviews, and other audio and video data, i.e. at least one video recording and/or at least one audio recording of the voice sample, where the voice recordings are used to generate a voice font of a specific person, i.e. creating a voice model [0016:1-8],[0023-6],[0031],[0053]);
the VA service storing the voice model on the at least one database (data including the voice font data, i.e. voice model, may be stored by the input processing unit, i.e. VA service, in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stores…on the at least one database Fig. 2,[0014],[0019-20],[0024],[0036]).
While Abramson provides generating a chat bot that interacts with a user using a specific personality and voice, Abramson does not specifically teach the selection and output of a story to the user, and thus does not teach
the software platform sending a selected story to the user device, wherein the selected story is based on an input received via a graphic user interface (GUI) of the user device, wherein the input includes an audio input, a touchscreen input, and/or a click select input;
the TTS engine converting a text of the selected story into an audio output using the voice model; and
the user device playing the audio output.
Killalea, however, teaches the software platform sending a selected story to the user device, wherein the selected story is based on an input received via a graphic user interface (GUI) of the user device, wherein the input includes an audio input, a touchscreen input, and/or a click select input (a user of a user computing device selects a written work, along with character identities and voice options, where the user may provide input via a GUI, i.e. story is selected or created based on inputs received via a GUI of the user device, using an audio input device, a touch sensitive panel, or a pointing device, i.e. inputs include an audio input, a touchscreen input, and/or a click select input, and the server computing device using a program to perform a task, provides the written work to the user computing device, i.e. software platform sends a selected story to the user device (3:50-58),(9:51-20),(11:40-64),(12:55-63));
the TTS engine converting a text of the selected story into an audio output using the voice model (the written work stored as text, and selected by the user, i.e. text of the selected story, is audibly rendered through a text-to-speech feature, i.e. TTS engine converts…into an audio output, where a voice for audibly rendering the written work may include a custom voice created by software based on a recording of the user’s speech, i.e. using the voice model (also ‘a voice model for a TTS engine from limitation 6)(2:15-39),(4:10-17),(7:1-10),(11:40-64)); and
the user device playing the audio output (the written work is audibly rendered, i.e. playing the audio output, at a user computing device, such as an electronic book reader, i.e. the user device (2:15-25),(3:27-49),(4:1-17),(10:32-33)).
Abramson and Killalea are analogous art because they are from a similar field of endeavor in presenting information to a user with customized voices. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the generation of a chat bot that interacts with a user using a specific personality and voice teachings of Abramson with the audible rendering of a written work in a custom voice generated from recordings of user speech as taught by Killalea. It would have been obvious to combine the references to enable multiple users to view a single written work, where each user can select the set of character attributes they prefer, including custom voices for specific characters (Killalea (9:51-10:31)).
Regarding claims 8, 12, and 18, Abramson teaches claims 1 and 9, and Abramson further teaches
(claims 8 and 12) the VA service creates at least two voice models, wherein the at least one database stores the at least two voice models/(claim 18) the at least one database storing the voice model (the input processing unit, i.e. VA service, creates personalized personality indices for multiple people, where each personality index uses social data for the respective person, including voice font data, and the social data is stored in a data store, i.e. the at least one database stores the at least two voice models, where the voice font of a specific person is created from voice data in the social data, i.e. creates at least two voice models [0020],[0022],[0024]).
While Abramson provides generating multiple voice fonts, Abramson does not specifically teach the selection and output of a particular voice model, and thus does not teach
(claims 8 and 12) wherein a server platform is operable to receive a selection of at least one of the at least two voice models, and wherein the at least one selected voice model is enabled for the VA service.
(claim 18) the software platform receiving a selection of the voice model and enabling the selected voice model for the VA service.
Killalea, however, teaches (claims 8 and 12) wherein a server platform is operable to receive a selection of at least one of the at least two voice models, and wherein the at least one selected voice model is enabled for the VA service/(claim 18) the software platform receiving a selection of the voice model and enabling the selected voice model for the VA service (the user utilizes a graphical interface of a user computing device to select a voice for each character in a written work, where multiple voices may be available, i.e. operable to receive a selection of at least one of the at least two voice models from the user device (10:6-43), where the selected voice is used to audibly render the written work using speech synthesis, i.e. the at least one selected voice model is enabled, where a server is used to process a written work to be presented to a user, i.e. server platform…VA service (2:16-51)).
Abramson and Killalea are analogous art because they are from a similar field of endeavor in presenting information to a user with customized voices. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the generation of multiple voice fonts teachings of Abramson with the selection of a specific voice for a character as taught by Killalea. It would have been obvious to combine the references to enable multiple users to view a single written work, where each user can select the set of character attributes they prefer, including custom voices for specific characters (Killalea (9:51-10:31)).
Regarding claims 10 and 19, Abramson in view of Killalea teaches claims 9 and 16, and Abramson further teaches
the VA service receives at least one audio file from the user device (the index engine of the input processing unit, i.e. VA service, accesses social data, i.e. receiving, that includes voice and image data, such as recordings of interviews, and other audio and video data, i.e. at least one audio file, from the client devices, i.e. user device, where the voice recordings are used to generate a voice font of a specific person, i.e. voice model [0016:1-8],[0020],[0023-6],[0031],[0053]),…, wherein the VA service stores the at least one audio file and the voice model on the at least one database (data including the voice data, i.e. audio file, and voice font data, i.e. voice model, may be stored by the input processing unit, i.e. VA service, in a data store, where components of the system may occur remotely, such as one or more server devices, where the server can store data for one or more entities on a system memory, i.e. stores…on the at least one database Fig. 2,[0014],[0019-20],[0024],[0036]).
Where Killalea further teaches wherein the at least one audio file is an audio recording of a specific section, page, and/or set of words of a story (the user may use a machine to record, i.e. at least one audio file from the user device, the user speaking utterances, words, and phrases from a script, i.e. audio recording of a specific story section, a storypage, and/or a set of words, to create a custom voice, i.e. voice model (2:26-39)).
And where the motivation to combine is the same as previously presented.
Regarding claims 11 and 17, Abramson in view of Killalea teaches claims 9 and 16, and Abramson further teaches
the software platform is implemented on a smart home device, a toy, and/or a vessel, wherein the smart home device, the toy, and/or the vessel is in network communication with the user device (the system may be distributed across and executable by multiple devices, where input may be entered on a client device and processed or accessed from other devices in a network, i.e. software platform is implemented…the smart home device the toy and/or the vessel is in network communication with the user device, and the computing devices may include a smart phone or other computer, i.e. implemented on a smart home device…or a vessel [0018-9],[0042],[0050]).
Regarding claims 15 and 20, Abramson in view of Killalea teaches claims 9 and 16, and Abramson further teaches
the at least one database is configured to store a plurality of artificial personalities, wherein the VA service is further configured to combine the plurality of artificial personalities to create a merged personality, wherein the merged personality includes one voice model (data stored on the server, i.e. at least one VA database is configured to store, may include multiple personality indexes, i.e. plurality of artificial personalities, such as a personalized personality index, and a generic personality index, where a personality index may include interaction rules that will govern how a personality index accesses multiple datasets, such as datasets from a specific person through their personality index and data from other users who also have personality indexes, where each personality index comprises social data, i.e. combine the custom personality with the at least one additional personality to create a merged personality, where the personality index contains voice font data, i.e. merged personality includes one voice model [0020],[0024],[0033:1-14],[0034:1-12]).
Claim(s) 13 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Abramson, in view of Killalea, in view of Murugeshan, and further in view of Gabai.
Regarding claim 13, Abramson in view of Killalea teaches claim 9.
While Abramson in view of Killalea provides converting a story using TTS, Abramson in view of Killalea does not specifically teach suggesting the story based on a semantic category, and thus does not teach
suggest a story to be converted using the TTS engine and the voice model based on a semantic category.
Murugeshan, however, teaches suggest —information-- … based on a semantic category (the system generates an adaptive response based on the domain, i.e. VA service is operable to suggest, where domain-related information extracted from the user query, i.e. based on a semantic category, are used to retrieve required information related to the query domain from a backend database to respond to the user’s query, i.e. information is categorized within the same predetermined semantic category as the stimulus [0024],[0042]).
Abramson, Killalea, and Murugeshan are analogous art because they are from a similar field of endeavor in enabling dialog between a user and a device with an intelligent dialog system. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the converting a story using TTS teachings of Abramson, as modified by Killalea, with the use of natural language processing functions to determine domain-related information for response retrieval as taught by Murugeshan. It would have been obvious to combine the references to enable a system to provide adaptive responses to user interactions based on user personality (Murugeshan [0024]).
While Abramson in view of Killalea and Murugeshan provides suggesting information based on domain, Abramson in view of Killalea and Murugeshan does not specifically teach that the information provided is a story converted using TTS and a voice model, and thus does not teach
suggest a story to be converted using the TTS engine and the voice model based on –the input--.
Gabai, however, teaches suggest a story to be converted using the TTS engine and the voice model based on –the input-- (the toy can provide historical commentary related to a site or object pointed out by a user, i.e. suggest a story…based on the input, where the personification of a historical figure or history professor, i.e. voice model, provides historical commentary, i.e. story to be converted…using the voice model (41:59-65),(42:3-12),(55:1-21), and where the toy can perform text-to-speech synthesis, i.e. converted using the TTS engine (67:51-58)).
Where Murugeshan teaches that the semantic category is determined from the input [0024],[0042].
Abramson, Killalea, Murugeshan, and Gabai are analogous art because they are from a similar field of endeavor in presenting customized information to a user. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify suggesting information based on domain teachings of Abramson, as modified by Killalea and Murugeshan, with the interacting with a user through customized educational content as taught by Gabai. It would have been obvious to combine the references to enable the system to facilitate the education and participation of a child through the personification of a character the child has developed a relationship with or is more likely to pay attention to, and allow children who may even be on opposite sides of the world to interact with each other (Gabai (22:7-19),(42:3-28)).
Regarding claim 14, Abramson in view of Killalea teaches claim 9.
While Abramson in view of Killalea provides using NLP to process social data including audio, Abramson in view of Killalea does not specifically teach using NLP to analyze the input determine a semantic category, and thus does not teach
a stimulus is analyzed using natural language processing (NPL) and matched to a predetermined semantic category, wherein the VA service is configured to suggest a story to be converted using the TTS engine and the voice model based on the predetermined semantic category matched to the stimulus, wherein the story is categorized within the same predetermined semantic category as the stimulus.
Murugeshan, however, teaches a stimulus is analyzed using natural language processing (NPL) and matched to a predetermined semantic category (user interactions may be received in data formats including text, audio, and video, i.e. stimulus, where the system may perform part-of-speech tagging, stop-word removal, and word sense disambiguation, i.e. analyzed using natural language processing (NLP), as well as mapping using a domain ontology using meaningful n-grams and synonyms, to determine the domain, i.e. matched to a predetermined semantic category, and meaning of the keywords, as well as the mood of the user [0022-3],[0036],[0063]), wherein the VA service is configured to suggest —information-- … based on the predetermined semantic category matched to the stimulus, wherein the —information-- is categorized within the same predetermined semantic category as the stimulus (the system generates an adaptive response based on the domain, i.e. VA service is configured to suggest, where domain-related information extracted from the user query, i.e. based on the predetermined semantic category matched to the stimulus, are used to retrieve required information related to the query domain from a backend database to respond to the user’s query, i.e. information is categorized within the same predetermined semantic category as the stimulus [0024],[0042]).
While Abramson in view of Killalea and Murugeshan provides information to a user that is responsive to a query domain, Abramson in view of Killalea and Murugeshan does not specifically teach that the information provided is a story, and thus does not teach
suggest a story to be converted using the TTS engine and the voice model…matched to the stimulus.
Gabai, however, teaches suggest a story to be converted using the TTS engine and the voice model…matched to the stimulus (the toy can provide historical commentary related to a site or object pointed out by a user, i.e. suggest a story…matched to the stimulus, where the personification of a historical figure or history professor, i.e. educator voice model, provides historical commentary, i.e. converting the story…using the voice model (41:59-65),(42:3-12),(55:1-21), and where the toy can perform text-to-speech synthesis, i.e. converted using the TTS engine (67:51-58)).
Abramson, Killalea, Murugeshan, and Gabai are analogous art because they are from a similar field of endeavor in presenting customized information to a user. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the provision of information to a user that is responsive to a query domain teachings of Abramson, as modified by Killalea and Murugeshan, with the interacting with a user through customized educational content as taught by Gabai. It would have been obvious to combine the references to enable the system to facilitate the education and participation of a child through the personification of a character the child has developed a relationship with or is more likely to pay attention to, and allow children who may even be on opposite sides of the world to interact with each other (Gabai (22:7-19),(42:3-28)).
Conclusion
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/NICOLE A K SCHMIEDER/Primary Examiner, Art Unit 2659
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