DETAILED ACTION
This communication is in response to the Amendments and Arguments filed on . Claims 01/20/2026 are pending and have been examined.
Any previous objection/rejection not mentioned in this Office Action has been withdrawn by the Examiner.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 01/21/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/12/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Change of Examiner
The Examiner of record has changed from Cameron Young to Paras Shah.
Response to Arguments
With respect to the Applicant’s arguments of the 35 USC 103 rejections, the Applicant has further amended the independent claims to recite “based on processing the vision data” and “subsequent to and responsive to determining the user profile for the user based on processing the vision data”. Therefore, the Applicant’s arguments in light of these amendments have been considered but are moot in view of new grounds for rejection. A new reference has been applied to teach primarily the newly added limitation and to address the arguments made of record.
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.
Claims 1 – 2, 4 – 10, 12 – 15 and 19 – 22 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2020/0380977 A1 to Oliver Unter Ecker (hereinafter Ecker) in view of U.S. Patent Application Publication No. 2014/0247208 A1 to David Henderek et al. (hereinafter Henderek.) in view of U.S. Patent Application Publication No. 2018/0150844 to Dolan et al. (hereinafter Dolan).
Regarding claim 1, Ecker teaches a client device comprising: (Ecker teaches a device for initiating voice control by using a gaze. (i.e., a client device.) Ecker at ¶¶ [0005] - [0008].)
at least one vision component; (Ecker teaches the device comprising a camera (i.e., a vision component). Ecker at ¶¶ [0028] - [0033].)
at least one microphone; (Ecker teaches the device comprising one or more microphones for receiving a user's voice. (i.e., at least one microphone). Ecker at ¶¶ [0028] - [0033].)
one or more processors; (Ecker teaches the device comprising processing circuitry (e.g., GPU, VPU, CPU) which process images and/or video as well as other hardware that processes other forms of data or information. (i.e., one or more processors). Ecker at ¶¶ [0028] - [0033] and [0047].)
memory operably coupled with the one or more processors, wherein the memory stores instructions that, in response to execution of the instructions by one or more of the processors, cause one or more of the processors to perform the following operations: (Ecker teaches the device comprising one or more processors configured to execute instructions stored in memory on a device readable medium wherein the instructions provide any of the various features, functions, or benefits of the device. (i.e., memory coupled to the one or more processors) Ecker at ¶ [0047].)
receiving a stream of vision data that is based on output from the vision component of the client device; (Ecker teaches receiving images or video received from the cameras of the device. (i.e., receiving a stream of vision data from the vision component of the client device.) Ecker at ¶¶ [0028] - [0033].)
receiving a stream of audio data that is based on output from the microphone of the client device; (Ecker teaches receiving audio from the one or more microphones of the device. (i.e., receiving a stream of audio data based on output from the microphone.) Ecker at ¶¶ [0028] - [0033].)
determining, based on processing the vision data: that a gaze of a user is directed toward the client device, and a user profile for the user; (Ecker teaches the device processing the images received by the cameras on the device to determine the presence of the gaze of a user. (i.e., the gaze is directed toward the client device) Ecker at ¶¶ [0035] - [0037]. Further, Ecker teaches the detecting device (i.e., the device processing images to determine the gaze of the user) may also perform facial recognition of the user to authenticate the user for accessing a profile of the user. (i.e., determining the gaze of a user is directed at the device and authenticating the user for a user profile associated with that user.) Ecker at ¶ [0041].)
determining, subsequent to and responsive to determining the user profile for the user based on processing the vision data and based on processing the audio data, that a spoken utterance, included in the audio data: temporally corresponds to the gaze, …; (Ecker teaches the audio data received from the user containing voice commands that are only processed when the gaze occurs. (i.e., temporally, the voice command corresponds to the gaze for at least a duration of the gaze.) Ecker at ¶ [0043]. Further, Ecker teaches authenticating the user for a user profile. Ecker at ¶ [0041]. Further, Ecker teaches determining a user profile before or after performing gaze detection, and processing voice commands as a response to gaze detection (which can occur after determining a user profile.) Ecker at ¶¶ [0041] – [0043].)
and in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze [[and has the voice characteristics that match the user profile that is determined based on processing the vision data]]: causing at least one dormant function of the automated assistant to be activated. (Ecker teaches the device performing a function on the device designated by the user's speech. (i.e., causing one dormant function of the automated assistant to be activated.) Ecker at ¶ [0032].)
Ecker, however, does not teach determining voice characteristics that match the user profile that is determined based on processing the vision data.
In a similar field of endeavor (e.g., waking a device in standby using gaze detection) Henderek teaches determining voice characteristics that match [[the user profile that is determined based on processing the vision data]]. (Henderek teaches authenticating a user using a voice pattern (i.e., the voice has voice characteristics that match the user profile) for waking a device for a user using gaze detection. Henderek at ¶ [0053].)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker with the teachings of Henderek to provide determining voice characteristics that match the user profile that is determined based on processing the vision data. Doing so would have improved the security of the device by prevent unauthorized users from accessing the device and allowing only authorized users to wake and user the device as recognized by Henderek at ¶ [0053]. Thus, Ecker and Henderek teach all of the limitations of claim 1 due to their similar fields of endeavor and analogous approaches to waking a device via user interaction with the device.
However, Ecker in view of Henderek do not specifically teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that match the user profile that is determined based on processing the vision data. The Examiner does note that Ecker teaches the connection of accessing a user profile based on the user being recognized from facial recognition. Henderek teaches the ability to match prestored username and password to a voice pattern. But the combination do not specifically connect the profile which was identified from the image being used to match information contained therein to user voice.
Dolan does teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that match the user profile that is determined based on processing the vision data (see [0068], where the identification of a user account of the person is performed by matching the image of the person with image of the account holder and see [0070], audio signal is captured and compared to a voiceprint associated with user 102m where user 102 was determined to be associated with user accounts based on the captured image).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker in view of Henderek with the teachings of Dolan to provide authenticate a user based on profile specific information. Doing so protects the public entry of authentication information (see Dolan [0023]-[0024]).
Regarding claim 2, Ecker in view of Henderek in view of Dolan (hereinafter Ecker-Henderek-Dolan) teaches all the limitations of claim 1. Further, Ecker teaches the client device of claim 1, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and has the voice characteristics that match the user profile that is determined based on processing the vision data comprises: transmitting of data, from the client device, to a remote server associated with the automated assistant. (Ecker teaches transmitting command information to a server when the command is something that would not be performed locally on the device. (i.e., transmitting command information to a server to perform dormant functions). Ecker at ¶ [0046].)
Regarding claim 4, Ecker-Henderek-Dolan teaches all the limitations of claim 1 as laid out above. Further, Ecker teaches the client device of claim 1, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and has the voice characteristics that match the user profile that is determined based on processing the vision data comprises: automatic speech processing of the audio data. (Ecker teaches performing automatic speech recognition on input audio data for processing voice control commands of a user device. (i.e., automatic speech recognition of audio data is performed.) Ecker at ¶ [0028].)
Regarding claim 5, Ecker-Henderek-Dolan teaches all the limitations of claim 1 as laid out above. Further, Ecker teaches the client device of claim 1, wherein determining, based on processing the vision data, the user profile of the user comprises performing facial recognition based on processing the vision data. (Ecker teaches performing facial recognition of the user for authentication purposes (i.e., facial recognition for the user profile.) Ecker at ¶ [0041].)
Regarding claim 6, Ecker-Henderek-Dolan teaches all the limitations of claim 1 as laid out above. Further, Ecker teaches the client device of claim 1, wherein determining, based on processing the vision data, that the gaze of the user is directed toward the client device comprises processing the vision data using a trained gaze machine learning model stored locally at the client device. (Ecker teaches performing gaze detection on the detecting device using artificial intelligence or neural network approaches. (i.e., performing gaze detection using a trained gaze machine learning model stored locally at the client device.) Ecker at ¶¶ [0037] - [0038].)
Regarding claim 7, Ecker-Henderek-Dolan teaches all the limitations of claim 1 as laid out above. Further, Ecker teaches the client device of claim 1, further comprising: determining that the user profile is authorized for the client device; wherein causing the at least one dormant function of the automated assistant to be activated is further contingent on determining that the user profile is authorized for the client device. (Ecker teaches performing user authentication to confirm the user's identity such that if the user is not recognized and authenticated the detecting device may not perform commands issued by the user or the device may not perform certain commands that do not require authentication. (i.e., activating the dormant function requires user authentication.) Ecker at ¶ [0041].)
Regarding claim 8, Ecker teaches a method implemented by one or more processors of a client device that facilitates touch-free interaction between one or more users and an automated assistant, the method comprising: processing image frames captured by a camera of the client device; (Ecker teaches receiving images or video received from the cameras of the device. (i.e., processing image frames from the camera of the client device.) Ecker at ¶¶ [0028] - [0033].)
determining, based on processing the image frames: that a gaze of a user is directed toward the client device, and a user profile for the user; (Ecker teaches the device processing the images received by the cameras on the device to determine the presence of the gaze of a user. (i.e., the gaze is directed toward the client device) Ecker at ¶¶ [0035] - [0037]. Further, Ecker teaches the detecting device (i.e., the device processing images to determine the gaze of the user) may also perform facial recognition of the user to authenticate the user for accessing a profile of the user. (i.e., determining the gaze of a user is directed at the device and authenticating the user for a user profile associated with that user.) Ecker at ¶ [0041].)
processing audio data captured by one or more microphones of the client device; (Ecker teaches receiving audio from the one or more microphones of the device. (i.e., receiving a stream of audio data based on output from the microphone.) Ecker at ¶¶ [0028] - [0033].)
determining, subsequent to and responsive to determining the user profile for the user based on processing the vision data and based on processing the audio data, that a spoken utterance, included in the audio data: temporally corresponds to the gaze, …; (Ecker teaches the audio data received from the user containing voice commands that are only processed when the gaze occurs. (i.e., temporally, the voice command corresponds to the gaze for at least a duration of the gaze.) Ecker at ¶ [0043]. Further, Ecker teaches authenticating the user for a user profile. Ecker at ¶ [0041]. Further, Ecker teaches determining a user profile before or after performing gaze detection, and processing voice commands as a response to gaze detection (which can occur after determining a user profile.) Ecker at ¶¶ [0041] – [0043].)
and in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and [[has the voice characteristics that match the user profile that is determined based on processing the image frames]]: causing at least one dormant function of the automated assistant to be activated. (Ecker teaches the device performing a function on the device designated by the user's speech. (i.e., causing one dormant function of the automated assistant to be activated.) Ecker at ¶ [0032].)
Ecker, however, does not teach determining the audio data has voice characteristics that match the user profile that is determined based on processing the image frames.
In a similar field of endeavor (e.g., waking a device in standby using gaze detection) Henderek teaches determining the audio data has voice characteristics that [[match the user profile that is determined based on processing the image frames]]. (Henderek teaches authenticating a user using a voice pattern (i.e., the voice has voice characteristics that match the user profile) for waking a device for a user using gaze detection. Henderek at ¶ [0053].)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker with the teachings of Henderek to provide determining the audio data has voice characteristics that match the user profile that is determined based on processing the image frames. Doing so would have improved the security of the device by prevent unauthorized users from accessing the device and allowing only authorized users to wake and user the device as recognized by Henderek at ¶ [0053]. Thus, Ecker and Henderek teach all of the limitations of claim 1 due to their similar fields of endeavor and analogous approaches to waking a device via user interaction with the device.
However, Ecker in view of Henderek do not specifically teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that match the user profile that is determined based on processing the vision data. The Examiner does note that Ecker teaches the connection of accessing a user profile based on the user being recognized from facial recognition. Henderek teaches the ability to match prestored username and password to a voice pattern. But the combination do not specifically connect the profile which was identified from the image being used to match information contained therein to user voice.
Dolan does teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that match the user profile that is determined based on processing the vision data (see [0068], where the identification of a user account of the person is performed by matching the image of the person with image of the account holder and see [0070], audio signal is captured and compared to a voiceprint associated with user 102m where user 102 was determined to be associated with user accounts based on the captured image).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker in view of Henderek with the teachings of Dolan to provide authenticate a user based on profile specific information. Doing so protects the public entry of authentication information (see Dolan [0023]-[0024]).
Regarding claim 9, Ecker-Henderek-Dolan teaches all the limitations of claim 8 as laid out above. Further, Ecker teaches the method of claim 8, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and has the voice characteristics that match the user profile that is determined based on processing the image frames comprises: transmitting of data, from the client device, to a remote server associated with the automated assistant. (Ecker teaches transmitting command information to a server when the command is something that would not be performed locally on the device. (i.e., transmitting command information to a server to perform dormant functions). Ecker at ¶ [0046].)
Regarding claim 10, Ecker-Henderek-Dolan teaches all the limitations of claim 9 as laid out above. Further, Ecker teaches the method of claim 9, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and has the voice characteristics that match the user profile that is determined based on processing the image frames comprises: automatic speech processing of the audio data. (Ecker teaches performing automatic speech recognition on input audio data for processing voice control commands of a user device. (i.e., automatic speech recognition of audio data is performed.) Ecker at ¶ [0028].)
Regarding claim 12, Ecker-Henderek-Dolan teaches all the limitations of claim 8 as laid out above. Further, Ecker teaches the method of claim 8, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze and has the voice characteristics that match the user profile that is determined based on processing the image frames comprises: automatic speech processing of the audio data. (Ecker teaches performing automatic speech recognition on input audio data for processing voice control commands of a user device. (i.e., automatic speech recognition of audio data is performed.) Ecker at ¶ [0028].)
Regarding claim 13, Ecker-Henderek-Dolan teaches all the limitations of claim 8 as laid out above. Further, Ecker teaches the method of claim 8, wherein determining, based on processing the image frames, the user profile of the user comprises performing facial recognition based on processing at least one of the image frames. (Ecker teaches performing facial recognition of the user for authentication purposes (i.e., facial recognition for the user profile.) Ecker at ¶ [0041].)
Regarding claim 14, Ecker-Henderek-Dolan teaches all the limitations of claim 13 as laid out above. Further, Ecker teaches the method of claim 13, wherein determining, based on processing the image frames, that the gaze of the user is directed toward the client device comprises processing the image frames using a trained gaze machine learning model stored locally at the client device. (Ecker teaches performing gaze detection on the detecting device using artificial intelligence or neural network approaches. (i.e., performing gaze detection using a trained gaze machine learning model stored locally at the client device.) Ecker at ¶¶ [0037] - [0038].)
Regarding claim 15, Ecker-Henderek-Dolan teaches all the limitations of claim 8 as laid out above. Further, Ecker teaches the method of claim 8, further comprising: determining that the user profile is authorized for the client device; wherein causing the at least one dormant function of the automated assistant to be activated is further contingent on determining that the user profile is authorized for the client device. (Ecker teaches performing user authentication to confirm the user's identity such that if the user is not recognized and authenticated the detecting device may not perform commands issued by the user or the device may not perform certain commands that do not require authentication. (i.e., activating the dormant function requires user authentication.) Ecker at ¶ [0041].)
Regarding claim 19, Ecker teaches a client device comprising: (Ecker teaches a device for initiating voice control by using a gaze. (i.e., a client device.) Ecker at ¶¶ [0005] - [0008].)
at least one vision component; (Ecker teaches the device comprising a camera (i.e., a vision component). Ecker at ¶¶ [0028] - [0033].)
at least one microphone; (Ecker teaches the device comprising one or more microphones for receiving a user's voice. (i.e., at least one microphone). Ecker at ¶¶ [0028] - [0033].)
one or more processors; (Ecker teaches the device comprising processing circuitry (e.g., GPU, VPU, CPU) which process images and/or video as well as other hardware that processes other forms of data or information. (i.e., one or more processors). Ecker at ¶¶ [0028] - [0033] and [0047].)
memory operably coupled with the one or more processors, wherein the memory stores instructions that, in response to execution of the instructions by one or more of the processors, cause one or more of the processors to perform the following operations: (Ecker teaches the device comprising one or more processors configured to execute instructions stored in memory on a device readable medium wherein the instructions provide any of the various features, functions, or benefits of the device. (i.e., memory coupled to the one or more processors) Ecker at ¶ [0047].)
receiving a stream of vision data that is based on output from the vision component of the client device; (Ecker teaches receiving images or video received from the cameras of the device. (i.e., receiving a stream of vision data from the vision component of the client device.) Ecker at ¶¶ [0028] - [0033].)
receiving a stream of audio data that is based on output from the microphone of the client device; (Ecker teaches receiving audio from the one or more microphones of the device. (i.e., receiving a stream of audio data based on output from the microphone.) Ecker at ¶¶ [0028] - [0033].)
determining, based on processing the vision data: that a gaze of a user is directed toward the client device, and a user profile for the user; (Ecker teaches the device processing the images received by the cameras on the device to determine the presence of the gaze of a user. (i.e., the gaze is directed toward the client device) Ecker at ¶¶ [0035] - [0037]. Further, Ecker teaches the detecting device (i.e., the device processing images to determine the gaze of the user) may also perform facial recognition of the user to authenticate the user for accessing a profile of the user. (i.e., determining the gaze of a user is directed at the device and authenticating the user for a user profile associated with that user.) Ecker at ¶ [0041].)
determining, subsequent to and responsive to determining the user profile for the user based on processing the vision data sand based on processing the audio data, that a spoken utterance, included in the audio data: temporally corresponds to the gaze, …; (Ecker teaches the audio data received from the user containing voice commands that are only processed when the gaze occurs. (i.e., temporally, the voice command corresponds to the gaze for at least a duration of the gaze.) Ecker at ¶ [0043]. Further, Ecker teaches authenticating the user for a user profile. Ecker at ¶ [0041]. Further, Ecker teaches determining a user profile before or after performing gaze detection, and processing voice commands as a response to gaze detection (which can occur after determining a user profile.) Ecker at ¶¶ [0041] – [0043].)
and in response to determining the [[spoken utterance has the voice characteristics that fail to match the user profile that is determined based on processing the vision data]]: refraining from causing at least one dormant function of the automated assistant to be activated. (Ecker teaches the device performing a function on the device designated by the user's speech. (i.e., causing one dormant function of the automated assistant to be activated.) Ecker at ¶ [0032]. Further, because Ecker teaches authenticating a user using facial recognition, the dormant function would not be performed if the user is not authenticated. Ecker at ¶ [0041].)
Ecker, however, does not teach determining voice characteristics that match the user profile that is determined based on processing the vision data.
In a similar field of endeavor (e.g., waking a device in standby using gaze detection) Henderek teaches determining voice characteristics that fail to [[match the user profile that is determined based on processing the vision data]]. (Henderek teaches authenticating a user using a voice pattern (i.e., the voice has voice characteristics that match the user profile) for waking a device for a user using gaze detection. Henderek at ¶ [0053]. As such, authenticating a user via a voice pattern means the voice characteristics that do not match the user do not authenticate the user. As such, the device or system would refrain from taking such an action as the user is not authenticated.)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker with the teachings of Henderek to provide determining voice characteristics that match the user profile that is determined based on processing the vision data. Doing so would have improved the security of the device by prevent unauthorized users from accessing the device and allowing only authorized users to wake and user the device as recognized by Henderek at ¶ [0053]. Thus, Ecker and Henderek teach all of the limitations of claim 19 due to their similar fields of endeavor and analogous approaches to waking a device via user interaction with the device.
However, Ecker in view of Henderek do not specifically teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that match the user profile that is determined based on processing the vision data. The Examiner does note that Ecker teaches the connection of accessing a user profile based on the user being recognized from facial recognition. Henderek teaches the ability to match prestored username and password to a voice pattern. But the combination do not specifically connect the profile which was identified from the image being used to match information contained therein to user voice.
Dolan does teach subsequent and responsive to determining the user profile for the user based on processing the vision data...has the voice characteristics that fail to match the user profile that is determined based on processing the vision data (see [0068], where the identification of a user account of the person is performed by matching the image of the person with image of the account holder and see [0070], audio signal is captured and compared to a voiceprint associated with user 102 where user 102 was determined to be associated with user accounts based on the captured image and see [0124], where a match is not found and process ends).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker in view of Henderek with the teachings of Dolan to provide authenticate a user based on profile specific information. Doing so protects the public entry of authentication information (see Dolan [0023]-[0024]).
Regarding claim 20, Ecker in view of Henderek-Dolan (hereinafter Ecker-Henderek-Dolan) teaches all the limitations of claim 19. Further, Ecker teaches the client device of claim 19, wherein the at least one dormant function of the automated assistant, refrained from being caused to be activated in response to determining that the spoken utterance has the voice characteristics that fail to match the user profile that is determined based on processing the vision data, comprises: refraining from transmitting of data, from the client device, to a remote server associated with the automated assistant. (Ecker teaches transmitting command information to a server when the command is something that would not be performed locally on the device. (i.e., transmitting command information to a server to perform dormant functions). Ecker at ¶ [0046]. Further, Ecker teaches authenticating a user using facial recognition. Ecker at ¶ [0041]. Since performing the command would only occur if the user was authenticated then the lack of authentication of a user would result in preventing the transmission of data from the client device to a remote server associated with the automated assistant.)
Regarding claim 21, Ecker-Henderek-Dolan teaches all the limitations of claim 19 as laid out above. Further, Ecker teaches the client device of claim 19, wherein determining, based on processing the vision data, the user profile of the user comprises performing facial recognition based on processing the vision data. (Ecker teaches performing facial recognition of the user for authentication purposes (i.e., facial recognition for the user profile.) Ecker at ¶ [0041].)
Regarding claim 22, Ecker-Henderek-Dolan teaches all the limitations of claim 19 as laid out above. Further, Ecker teaches the client device of claim 19, wherein determining, based on processing the vision data, that the gaze of the user is directed toward the client device comprises processing the vision data using a trained gaze machine learning model stored locally at the client device. (Ecker teaches performing gaze detection on the detecting device using artificial intelligence or neural network approaches. (i.e., performing gaze detection using a trained gaze machine learning model stored locally at the client device.) Ecker at ¶¶ [0037] - [0038].)
Claims 3 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Ecker-Henderek-Dolan as applied to claims 1 and 8 above, and further in view of U.S. Patent Application Publication No. 2014/0002344 A1 to Mukund Pai (hereinafter Pai).
Regarding claim 3, Ecker-Henderek-Dolan teaches all the limitations of claim 1 as laid out above. Further Ecker teaches the client device of claim 1, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze …. Graphically rendering content (Ecker teaches using the voice control process to control a television by looking at the television and speaking a command. (i.e., commanding the television to display content, i.e., graphically rendering content.) Ecker at ¶ [0022].) and has the voice characteristics that match the user profile that is determined based on processing the vision data (see above as taught by Dolan)
Ecker-Henderek-Dolan, however, does not teach the graphically rendered content is tailored to the user profile. In a similar field of endeavor, (e.g., performing facial recognition and determining a parameter of the facial recognition to induce a response) Pai teaches graphically rendering content that is tailored to the user profile. (Pai teaches displaying content and dynamically adjust the display of content based on a user profile wherein facial recognition is used to determine the user profile. Pai at ¶ [0023].)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker-Henderek-Dolan with the teachings of Pai to provide graphically rendering content tailor to a user profile. Doing so would have improved the user experience by reducing eye strain of the user as recognized by Pai at ¶ [0023].
Regarding claim 11, Ecker-Henderek-Dolan teaches all the limitations of claim 8 as laid out above. Further Ecker teaches the method of claim 8, wherein the at least one dormant function of the automated assistant, that is caused to be activated in response to determining the gaze of the user, and contingent on determining that the spoken utterance temporally corresponds to the gaze … further comprises: graphically rendering content …. (Ecker teaches using the voice control process to control a television by looking at the television and speaking a command. (i.e., commanding the television to display content, i.e., graphically rendering content.) Ecker at ¶ [0022].) and has the voice characteristics that match the user profile that is determined based on processing the image frames (as taught by Dolan above).
Ecker-Henderek-Dolan, however, does not teach the graphically rendered content is tailored to the user profile. In a similar field of endeavor, (e.g., performing facial recognition and determining a parameter of the facial recognition to induce a response) Pai teaches graphically rendering content that is tailored to the user profile. (Pai teaches displaying content and dynamically adjust the display of content based on a user profile wherein facial recognition is used to determine the user profile. Pai at ¶ [0023].)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Ecker-Henderek-Dolan with the teachings of Pai to provide graphically rendering content tailor to a user profile. Doing so would have improved the user experience by reducing eye strain of the user as recognized by Pai at ¶ [0023].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zurek (US 2014/0350924) is cited to disclose in [0075]-[0077] determination of authorized users based on gaze of user towards a devices which then triggers voice recognition Any inquiry concerning this communication or earlier communications from the examiner should be directed to PARAS D SHAH whose telephone number is (571)270-1650. The examiner can normally be reached Monday-Thursday 7:30AM-2:30PM, 5PM-7PM (EST), Friday 8AM-noon (EST).
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/Paras D Shah/Supervisory Patent Examiner, Art Unit 2653
06/13/2026
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