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 Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan et al. (US #2022/0093094) in view of D’Souza et al. (US #2019/0371329).
Regarding Claim 1, Krishnan discloses a computer-implemented (title, abstract, figs. 1A, 1C, 2-4C, 6A-15H, 19-24) method comprising:
receiving a user input (Krishnan ¶0060 discloses speech is detected in audio data representing audio 11. ¶0064 discloses … begin transmitting audio data 211, representing the audio 11, to the system(s) 120. ¶0066 discloses upon receipt by the system(s) 120, the audio data 211 may be sent to an orchestrator component 230. ¶0067 discloses the orchestrator component 230 may send the audio data 211 to a language processing component 292. ¶0068 discloses the NLU component 260 may determine an intent representing an action that a user desires be performed and may determine information that allows a device [e.g., the device 110, the system(s) 120, a skill component 290, a skill system(s) 125, etc.] to execute the intent) resulting in activation of a first application implemented on a user device (Krishnan ¶0068 discloses for example, if the text data corresponds to "play the 5th Symphony by Beethoven," the NLU component 260 may determine an intent that the system output music and may identify "Beethoven" as an artist/composer and "5th Symphony" as the piece of music to be played [on the user device 110]. ¶0294 discloses the system may [instead or in addition] perform an action based on the input text data 1102 and/or other input data 1104, such as calling one or more APIs 1110; fig. 12. ¶0303 discloses if the action selector 1118 determines to invoke an API call, one or more APIs 1110 may be activated and a corresponding action carried out), the user device configured to perform natural language processing and the first application configured to process a first type of natural language processing results data (Krishnan ¶0093 discloses although the components of fig. 2 may be illustrated as part of system(s) 120, device 110, or otherwise, the components may be arranged in other device(s) [such as in device 110 if illustrated in system(s) 120 or vice-versa, or in other device(s) altogether] without departing from the disclosure. fig. 3 illustrates such a configured device 110);
receiving input data representing a first natural language input (Krishnan fig. 3: 360, 365);
performing natural language processing using the input data to determine first natural language processing results data (Krishnan figs. 9-11B: 985; ¶0069, fig. 12: 1216; ¶0337);
determining that the first natural language processing results data corresponds to the first type of natural language processing results data (Krishnan ¶0103 discloses a device-determined directive may be formatted as a programmatic application programming interface [API] call. ¶0106 discloses the device 110 may include, or be configured to use, one or more skill components 390 that may work similarly to the skill component(s) 290 implemented by the system 120. The skill component(s) 390 may correspond to one or more domains that are used in order to determine how to act on a spoken input in a particular way, such as by outputting a directive that corresponds to the determined intent, and which can be processed to implement the desired operation. The skill component(s) 390 installed on the device 110 may include, without limitation, a smart home skill component [or smart home domain] and/or a device control skill component [or device control domain] to execute in response to spoken inputs corresponding to an intent to control a second device(s) in an environment, a music skill component [or music domain] to execute in response to spoken inputs corresponding to a intent to play music, a navigation skill component [or a navigation domain] to execute in response to spoken input corresponding to an intent to get directions, a shopping skill component [or shopping domain] to execute in response to spoken inputs corresponding to an intent to buy an item from an electronic marketplace, and/or the like); and
sending, to the first application operating on the user device, the first natural language processing results data (Krishnan ¶0294 discloses the system may instead or in addition perform an action based on the input text data 1102 and/or other input data 1104, such as calling one or more APIs 1110; fig. 12. ¶0303 discloses if the action selector 1118 determines to invoke an API call, one or more APIs 1110 may be activated and a corresponding action carried out).
Krishnan may not explicitly disclose sending, to the first application operating on the user device, the first natural language processing results data.
However, D’Souza (title, abstract, figs. 1-11) teaches sending, to the first application operating on the user device, the first natural language processing results data (D’Souza fig. 3: 326, 328; 330, 332: YES; fig. 4: 416; fig. 5: 510)).
Krishnan and D’Souza are analogous art as they pertain to communicating with multimedia devices. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify dialog management system (as taught by Krishnan) to enable/disable first application based on the query (as taught by D’Souza, ¶0126, fig. 3) to enable application’s functionality if a single application has a similarity value in excess of the similarity threshold (D’Souza, ¶0024).
Regarding Claim 2, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1, further comprising:
sending, from the user device to at least one second device, a first indication corresponding to the first application being configured for operation on the user device (Krishnan ¶0097 discloses if data is being processed the device 110 can indicate such to the user, for example by activating or changing the color of an illuminated output [such as an LED ring], displaying an indicator on a display [such as a light bar across the display], outputting an audio indicator [such as a beep] or otherwise informing a user that input data is being processed. As an indicator to the user, however, the system can output an audio, visual, or other indicator when the system directed input detector 385 is determining whether an input is potentially device directed. For example, the system may output an orange indicator while considering an input, and may output a green indicator if a system directed input is detected. ¶0099 discloses if the device 110 attempts to process a natural language user input for which the on-device language processing components are not necessarily best suited, the language processing results determined by the device 110 can indicate a low confidence or other metric indicating that the processing by the device 110 may not be as accurate as the processing done by the system 120).
Regarding Claim 3, Krishnan in view of D’Souza discloses the computer-implemented method of claim 2. But Krishnan may not explicitly disclose further comprising, after sending the first natural language processing results data: determining the first application has been disabled on the user device; and sending a second indication corresponding to the first application being disabled with respect to the user device.
However, D’Souza (title, abstract, figs. 1-11) teaches after sending the first natural language processing results data (D’Souza fig. 11: 1104-1112; ¶0172-¶0173):
determining the first application has been disabled on the user device (D’Souza fig. 11: 1158; ¶0174); and
sending a second indication corresponding to the first application being disabled with respect to the user device (D’Souza fig. 11: 1160; ¶0175).
Krishnan and D’Souza are analogous art as they pertain to communicating with multimedia devices. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify dialog management system (as taught by Krishnan) to enable/disable first application based on the query (as taught by D’Souza, ¶0126, fig. 3) to enable/disable application’s functionality (D’Souza, ¶0026-¶0027).
Regarding Claim 4, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1. But Krishnan may not explicitly disclose further comprising: storing first data associating the first application and a first example of the first type of natural language processing results data.
However, D’Souza (title, abstract, figs. 1-11) teaches storing first data associating the first application and a first example of the first type of natural language processing results data (D’Souza figs. 2A-2B: 260, 254 and domains A-C).
Krishnan and D’Souza are analogous art as they pertain to communicating with multimedia devices. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify dialog management system (as taught by Krishnan) to enable/disable first application based on the query (as taught by D’Souza, ¶0126, fig. 3) to enable application’s functionality if a single application has a similarity value in excess of the similarity threshold (D’Souza, ¶0024).
Regarding Claim 5, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1. But Krishnan may not explicitly disclose wherein the first type of natural language processing results data comprises a directive processable by the first application to perform a first action.
However, D’Souza (title, abstract, figs. 1-11) teaches wherein the first type of natural language processing results data comprises a directive processable by the first application to perform a first action (D’Souza ¶0043 discloses for instance, at step 52, an enablement intent may be determined, as well as a directive of the enablement intent. In the illustrative example, the enablement intent may be, "Enable," while the directive may be, "Skill 1”; fig. 1A).
Krishnan and D’Souza are analogous art as they pertain to communicating with multimedia devices. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify dialog management system (as taught by Krishnan) to enable/disable first application based on the query (as taught by D’Souza, ¶0126, fig. 3) to enable application’s functionality if a single application has a similarity value in excess of the similarity threshold (D’Souza, ¶0024).
Regarding Claim 6, Krishnan in view of D’Souza discloses the computer-implemented method of claim 5. But Krishnan may not explicitly disclose wherein the first action corresponds to a second device.
However, D’Souza (title, abstract, figs. 1-11) teaches wherein the first action corresponds to a second device (D’Souza ¶0050 discloses as shown in fig. 1B, an individual may enable an application's functionality for their user account by speaking utterance 4, and backend system 100 may also be able to have additional communication with electronic device 10. At step 152, an enablement intent may be determined, as well as a directive of the enablement intent).
Krishnan and D’Souza are analogous art as they pertain to communicating with multimedia devices. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify dialog management system (as taught by Krishnan) to enable/disable first application based on the query (as taught by D’Souza, ¶0126, fig. 3) to enable application’s functionality if a single application has a similarity value in excess of the similarity threshold (D’Souza, ¶0024).
Regarding Claim 7, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1,
wherein the first natural language processing results data are sent to the user device from at least one second device (Krishnan fig. 1A: first device 110; second device 120).
Regarding Claim 8, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1, further comprising:
determining the first application corresponds to first model data to be used for natural language processing associated with the first application (Krishnan fig. 15E: movie domain); and
configuring a first natural language processing component using the first model data to determine an updated natural language processing component (Krishnan figs. 15F-15G: recipe domain; ¶0398-¶0399),
wherein performing the natural language processing uses the updated natural language processing component (Krishnan ¶0392 discloses fig. 15A-1H illustrates interactions with a virtual assistant system for managing and coordinating a natural language dialog involving multiple users in a MUD and/or conversation mode. These figures illustrate an example dialog using various techniques and components).
Regarding Claim 9, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1, further comprising:
determining the first application corresponds to first model data to be used by a speech synthesis component to create a synthesized speech response associated with the first application (Krishnan fig. 21: 2118);
configuring a speech synthesis component using the first model data to determine an updated speech synthesis component (Krishnan fig. 21: 2120);
determining, by the first application, first output data responsive to the first natural language input (Krishnan fig. 21: 2115; ¶0493: how specific words should be pronounced for example, by indicating the desired output speech quality in tags formatted according to the speech synthesis markup language [SSML] or in some other form);
processing the first output data using the updated speech synthesis component to determine output audio data representing a first synthesized speech response to the first natural language input (Krishnan fig. 21: output audio data 2190); and
causing, by at least one loudspeaker of the user device, presentation of output audio corresponding to the output audio data (Krishnan ¶0095 discloses example, the system 120, using a remote directive that is included in response data [e.g., a remote response], may instruct the device 110 to output an audible response [e.g., using TTS processing performed by an on-device TTS component 380] to a user's question via a loudspeaker(s) of [or otherwise associated with] the device 110, to output content [e.g., music] via the loudspeaker(s)).
Regarding Claim 10, Krishnan in view of D’Souza discloses the computer-implemented method of claim 1, further comprising:
determining that the first natural language processing results data further corresponds to a second type of natural language processing results data corresponding to a second application (Krishnan figs. 9-10: 985, 265/365); and
determining context data corresponding to an operating condition of the user device (Krishnan fig. 10: context aggregator 1006; context data 1008),
wherein sending the first natural language processing results data to the first application is based at least in part on the context data (Krishnan fig. 10: skill 290/390/125; and figs. 9-10: skill result data 930).
Claims 11-20 are rejected for the same reasons as set forth in Claims 1-10.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YOGESHKUMAR G PATEL whose telephone number is (571)272-3957. The examiner can normally be reached 7:30 AM-4 PM PST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Duc Nguyen can be reached at (571) 272-7503. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/YOGESHKUMAR PATEL/Primary Examiner, Art Unit 2691
Prosecution Insights