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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/22/26 has been entered.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-19, 24, 70 and 72-77 is/are rejected under 35 U.S.C. 103 as being unpatentable over Soudek (US 20180272240) in view of Emma (US 20190156222)
In claims 1 and 24, Soudek discloses
Determining, by a first computing device, session data associated with a first interactive session with a first physical toy character, the session data including one or more of a session identifier associated with the first interactive session or a previous user input associated with the first physical toy (paragraph 38, the session data would be the customization, such as an input of the user’s name)
After determining the session data, receiving, by the first computing device, a first identifier associated with the first physical toy character (Figure 1, the first computing device is Modular interactive device 120. The first identifier is received from the RFID reader 126 from the RFID 130 from the physical toy 110. figure 6, #606)
Transmitting, by the first computing device, a request for a second interactive session to a second computing device, wherein the request is determined based on the session data, the user input and the first identifier(Figure 1, the second computing device is the server 190. The request is sent via the wireless interface 128 thru network 150. The request is based on the user input thru microphone 124. Figure 6 #602, 604, 608. Paragraph 38 shows that the request can also be determined based on the session data, as the user’s name of “Jason” is used in the response)
Receiving, by the first computing device, a response from the second computing device, wherein the response is contextually generated based on the first identifier and the user input and (figure 6 #620, figure 7 shows that the response is generated based on the first identifier and the user input)
Presenting, by the first computing device, the response to the user (figure 6 #612)
Soudek discloses the claimed invention except for that the response is created rather than generated, and the inputs are used as inputs to a machine learning model that is trained based on a curated data set that is associated with the first physical toy character, and wherein the curated data set includes a speech pattern associated with the physical toy (which is to say that Soudek chooses from a set of pre-recorded responses contextually based on the user input and the first identifier, rather than creating a new response from a machine learning model), however Emma discloses contextually creating a response based on the user input and the first identifier as inputs to a machine learning model (paragraph 16) that is trained based on a curated data set that is associated with the first physical toy character, and wherein the curated data set includes a speech pattern associated with the first physical toy (paragraph 123 discloses a voice training system which receives voice samples, which would include speech patterns). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Soudek with Emma in order to allow for a wider range of possible responses which are more closely catered to the user input.
In claims 2 and 70, Emma discloses wherein the response comprises newly generated text content, audio content, visual content, or a combination thereof created based on the user input and the first identifier (paragraph 16)
In claim 4, Soudek discloses the user input comprises audio input captured via a microphone of the first computing device (figure 1 #124)
In claim 5, Soudek discloses presenting the response to the user comprises converting text included in the response into audio data and outputting the audio data via a speaker of the first computing device, the first physical toy character or a combination thereof (paragraph 38)
In claim 6, Soudek discloses presenting the response further comprises providing haptic feedback to the user via the first computing device (a speaker reads on the BRI of haptic feedback, as speakers work via vibration, meaning that it may be felt via touch.)
In claim 7, Soudek discloses the haptic feedback is provided via the first physical toy character through one or more actuators of the first physical toy controlled by the first computing device (a speaker is an actuator)
In claim 8, Soudek discloses detecting a second identifier associated with a second physical toy character, and wherein the request is determined based on the first identifier and the second identifier (figure 1 shows two different characters and identifiers, see paragraphs 15 and 27)
In claim 9. Soudek discloses presenting the response comprises outputting an interaction between the first physical toy character and the second toy character (paragraph 27)
In claim 10 Soudek discloses extracting by the first computing device, at least one feature, phrase, keyword, or combination thereof from the audio input, wherein the request includes the at least one feature, at least one phrase, at least one keyword, or a combination thereof (paragraph 36)
In claims 11 and 12, Soudek discloses detecting the first identifier comprises receiving the first identifier from a wireless tag contained within the first physical controller, wherein the wireless tag is an RFID tag (figure 1 #126, paragraph 39)
In claim 13, Soudek discloses
Determining, by a first computing device, session data associated with a first interactive session with a first physical toy character, the session data including one or more of a session identifier associated with the first interactive session or a previous user input associated with the first physical toy (paragraph 38, the session data would be the customization, such as an input of the user’s name)
After determining the session data, receiving by a second computing device, from a first computing device over a network, a request for a second interactive session, wherein the request comprises at least one identifier corresponding to the physical toy character (Figure 1, the first computing device is Modular interactive device 120. The first identifier is received from the RFID reader 126 from the RFID 130 from the physical toy 110. figure 6, #606, the second computing device is the server 190. The request is sent via the wireless interface 128 thru network 150. The request is based on the user input thru microphone 124. Figure 6 #602, 604, 608)
Determining, by the second computing device, a response to the request, wherein the response is based on the session data, at least one identifier, and the user inputs (Figure 1, the second computing device is the server 190. The request is sent via the wireless interface 128 thru network 150. The request is based on the user input thru microphone 124. Figure 6 #602, 604, 608. Paragraph 38 shows that the request can also be determined based on the session data, as the user’s name of “Jason” is used in the response)
and transmitting by the second computing device, the response to the first computing device for presentation to the user (figure 6 #612)
Soudek discloses the claimed invention except for that the response is created rather than generated, and the inputs are used as inputs to a machine learning model (which is to say that Soudek chooses from a set of pre-recorded responses contextually based on the user input and the first identifier, rather than creating a new response from a machine learning model), however Emma discloses contextually creating a response based on the user input and the first identifier as inputs to a machine learning model (paragraph 68). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Soudek with Emma in order to allow for a wider range of possible responses which are more closely catered to the user input
In claim 14, Soudek discloses detecting a second identifier associated with a second physical toy character, and wherein the request is determined based on the first identifier and the second identifier (figure 1 shows two different characters and identifiers, see paragraphs 15 and 27)and presenting the response comprises outputting an interaction between the first physical toy character and the second toy character (paragraph 27)
In claim 15, Soudek discloses the response is based on content specific to at least one character associated with the at least one identifier (paragraph 31). Emma discloses that a machine learning model is trained based on this content (paragraph 117)
In claim 16, Soudek discloses an indication of an accessory connected to the physical toy character, and determining the response comprises adjusting the response based on the accessory (paragraph 28)
In claim 17, Soudek discloses environmental context data, and the response is determined based on the environmental context data (the microphone data teaches the BRI of environmental context data, as the user is part of the environment)
In claim 18, Emma discloses retrieving information from a knowledge base associated with the toy character to generate the response and wherein the response is contextually created based on the information from the knowledge base associated with the toy character (paragraph 16)
In claim 19, Soudek discloses retrieving character specific setting associated with the at least one identifier, the first computing device, the first physical toy, or a combination thereof, and determining the response based on the character specific settings (the BRI of settings includes information about the character being set, such as paragraph 31)
In claims 3 and 72, Emma discloses an adventure mode in which the response is determined to include interactive narratives where the user participates in adventures with the first physical toy (paragraph 90 discloses a storybook mode which would be an adventure, and has interactive elements including user inputs)
In claims 3 and 73, Emma discloses a biographer mode in which determining the response includes determining a digital twin of the user by collecting personal information associated with the user, wherein the response is determined based on the personal information (It is noted by examiner that “a digital twin” is broad terminology that has no context beyond that it responds based on personal information. Paragraph 16 of Emma teaches constructing responses based on a personality score which is based on personal data, as such these responses are of a determined digital twin under the BRI and teaches the invention as claimed)
In claims 3 and 74, Emma discloses a music mode in which the response includes music generated by the machine learning model in real time basedo n the training of the machine learning model for music composition (it is noted by examiner that “music” is simply sounds combined in such a way to produce beauty of form, and beauty of form would be subjective and a term of degree. As such, the BRI of “music” with no further limitations would simply be any sound. It is further noted by examiner that to the degree that “music” IS further limiting than simply “sound”, the differentiation would be a matter of non-functional descriptive material, as no functional relationship exists and the limitation is directed to conveying a message or meaning to a human reader independent of the intended computer system, see MPEP 2111.05. As such, Soudek discloses a “sound effect” as per paragraph 25, and Emma discloses sound outputs as per paragraph 15)
In claim 75, Soudek discloses determining the session data includes storing the session data locally at the first computing device (paragraph 48 discloses that the user information and log data can be stored in the data store. Paragraph 54 discloses that the data store may be local)
In claim 76, Soudek discloses the session data includes synchronizing at least some of the session data with the second computing device (paragraph 54 discloses that the data store may be local and/or remotely)
In claim 77, Soudek discloses detecting by the second computing device, a third computing device in communication with the physical toy, wherein the third computing device is distinct from the first computing device, based on detecting the third computing device, initiating a shared session between the first computing device and the third computing device, wherein the shared session is associated with a shared session identifier between the first computing device and the third computing device and synchronizing content for the shared session wherein synchronizing the content includes coordinating the response with a second response from the third computing device (paragraph 15)
Claim(s) 71 is/are rejected under 35 U.S.C. 103 as being unpatentable over Soudek in view of Emma in view of Nagaraju (US 20180032908).
In claim 71, Soudek discloses
Determining, by a first computing device, session data associated with a first interactive session with a first physical toy character, the session data including one or more of a session identifier associated with the first interactive session or a previous user input associated with the first physical toy (paragraph 38, the session data would be the customization, such as an input of the user’s name)
After determining the session data, receiving, by the first computing device, a first identifier associated with the first physical toy character (Figure 1, the first computing device is Modular interactive device 120. The first identifier is received from the RFID reader 126 from the RFID 130 from the physical toy 110. figure 6, #606)
Transmitting, by the first computing device, a request for a second interactive session to a second computing device, wherein the request is determined based on the session data, the user input and the first identifier(Figure 1, the second computing device is the server 190. The request is sent via the wireless interface 128 thru network 150. The request is based on the user input thru microphone 124. Figure 6 #602, 604, 608. Paragraph 38 shows that the request can also be determined based on the session data, as the user’s name of “Jason” is used in the response)
Receiving, by the first computing device, a response from the second computing device, wherein the response is contextually generated based on the first identifier and the user input and (figure 6 #620, figure 7 shows that the response is generated based on the first identifier and the user input)
Presenting, by the first computing device, the response to the user (figure 6 #612)
Wherein the second computing device enables management of a comprehension version of an interaction history included in the session data (paragraph 38)
Soudek discloses the claimed invention except for that the response is created rather than generated, and the inputs are used as inputs to a machine learning model that is trained based on a curated data set that is associated with the first physical toy character, and wherein the curated data set includes a speech pattern associated with the physical toy (which is to say that Soudek chooses from a set of pre-recorded responses contextually based on the user input and the first identifier, rather than creating a new response from a machine learning model), however Emma discloses contextually creating a response based on the user input and the first identifier as inputs to a machine learning model (paragraph 16) that is trained based on a curated data set that is associated with the first physical toy character, and wherein the curated data set includes a speech pattern associated with the first physical toy (paragraph 123 discloses a voice training system which receives voice samples, which would include speech patterns). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Soudek with Emma in order to allow for a wider range of possible responses which are more closely catered to the user input.
Soudek in view of Emma fails to discloses detecting one or more conditions indicating a particular connectivity status associated with network connectivity to the second device, based on detecting the one or more conditions indicating the particular connectivity status, providing the user input to a local machine learning model associated with the first computing device, and receiving an output of the local machine learning model that is based on the user input and generating at least one local response at the first computing device based on the output of the local machine learning model, wherein the local machine learning model is associated with a first capability and wherein the machine learning model is associated with a second capability that is more advanced than the first capability however Nagaraju discloses determining that the edge device is disconnected from a server providing machine learning, and uses local machine learning for processing (paragraph 23) wherein the local machine learning model is associated with a first capability and wherein the machine learning model is associated with a second capability that is more advanced than the first capability (paragraph 35). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Soudek in view of Emma with Nagaraju in order to allow for the device to continue to operate when no longer connected to a server, despite the server models having improved capabilities.
Response to Arguments
Applicant's arguments and amendments have been fully considered but they are not persuasive.
Applicant argues that Emma merely teaches “acoustic reproduction via copying or simulating a voice” which is different from training a machine learning model. Emma’s entire invention is directed towards an artificial intelligence platform, paragraph 68 states that the simulated voice is “derived from analyzed speech patterns”, with analysis occurring in an NLP engine as per paragraph 99. Thus the simulation of the voice is occurring via the artificial intelligence engine of Emma.
Applicant argues that the prior art of Soudek fails to disclose session data and the request is determined based on the session data, however a session wherein a user inputs a name is taught in Soudek, and that session is used as part of the request in later sessions.
Applicant argues that Soudek in view of Emma in view of Nagaraju fails to disclose that the machine learning model is more advanced and enables management by the machine learning model of a comprehensive version of the interaction history, however Soudek discloses managing a comprehensive version of the interaction history, and Nagaraju discloses that the machine learning model is more advanced than the local machine learning model.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS HAYNES HENRY whose telephone number is (571)270-3905. The examiner can normally be reached M-F 10-6.
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/THOMAS H HENRY/ Primary Examiner, Art Unit 3715
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