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 .
This communication is in response to Amendment filed on April 14, 2026. Claims 1-20 are pending. Claims 1, 9, and 15 are amended.
Response to Arguments
Referring to the 35 USC 101 rejection of claims 1-20, as amended, Applicant’s amendments to the claims are acknowledged, however are not found to be persuasive.
Referring to claims 1, 9 and 15, as amended, Applicant argues that the claims as a whole, recite a technological improvement because the claimed features “conserve battery life and/or other resources of the client device..shorten the overall duration of user/automated assistant interactions that occur via the client device and provide more efficient client and/or server resolution of spoken utterances and/or other inputs” as a result of the biasing steps. However Examiner respectfully disagrees.
The recitation of the biasing of the data selection is a mental step. The speech to text processing of audio data using the speech recognition machine learning model is then used to generate the responsive data that is rendered as output. The speech recognition machine learning model is used as a tool to implement the abstract idea of biasing data, wherein it is used to conduct speech to text processing. There are no further details as to how the machine learning model achieves the conservation of battery life and/or other resources of the client device..and shortening the overall duration of user/automated assistant interactions that occur via the client device and provide more efficient client and/or server resolution of spoken utterances and/or other inputs by using the biased data other than displaying an output.
Furthermore, Examiner submits with respect to Applicant’s arguments pertaining to the technical improvement, that there is no improvement to the overall experience to the user utilizing this claimed system because the improvement is only brought about by the biasing of the term used to customize the query input by the user, and which is implemented by the speech recognition machine learning model. Examiner submits that the use of the speech recognition machine learning model in this way is merely applying the judicial exception using a computer or computer software such as the machine learning model as a tool to perform the abstract idea of biasing the data. As such, Examiner is not persuaded that the claims recite a technological improvement. The claims are not patent eligible.
Claims 1-20 remain rejected under 35 USC 101 for at least the reasons stated above.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 2/19/2026 is being considered by the examiner.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 9 and 15 recite:
determining a current location of a user;
receiving, via an automated assistant, audio data that captures a spoken utterance from the user and that is detected via one or more microphones of the portable computing device,
wherein the spoken utterance includes natural language content corresponding to a request for the automated assistant to provide information about a location of interest;
determining whether location characteristic data is associated with an area that includes the current location, wherein the location characteristic data is accessible via one or more applications of the portable computing device;
in response to determining there is location characteristic data associated with the area:
generating, in response to receiving the spoken utterance from the user, responsive data by biasing a data selection based on the location characteristic data, wherein biasing the data selection based on the location characteristic data includes:
biasing speech to text processing toward a set of terms determined based on the location characteristic data, the speech to text processing including processing the audio data using a speech recognition machine learning model stored at the portable computing device to generate a recognition of the spoken utterance,
wherein biasing speech to text processing toward the set of terms includes restricting biasing of the speech to text processing to a subset, of the set of terms, based on the subset being determined to correspond to a location of interest within the area, and
using the recognition in generating the responsive data, wherein the recognition comprises a term of the subset of terms to which speech to text processing is biased; and
prior to receiving audio data that captures the spoken utterance from the user, causing the portable computing device to render output that informs the user that the speech to text processing is biased toward the subset of terms; and
rendering, via the automated assistant of the portable computing device, responsive output that is based on the responsive data.
Step 1: The claims as a whole fall within one or more statutory categories.
Step 2A prong 1: At least claims 1, 9 and 15 recite limitations that are abstract ideas.
“determining a current location of a user”
“determining whether location characteristic data is associated with an area that includes the current location, wherein the location characteristic data is accessible via one or more applications of the portable computing device”
“in response to determining there is location characteristic data associated with the area, generating, in response to receiving the spoken utterance from the user, responsive data by biasing a data selection based on the location characteristic data”
The limitations “determining a current location of a user” and “determining whether location characteristic data is associated with an area that includes the current location, wherein the location characteristic data is accessible via one or more applications of the portable computing device” are mental steps. A user can mentally determine their current location and determine characteristic data associated with the user’s current location. Thus, the claimed limitations can be performed by the human mind.
Furthermore, the limitation “generating, in response to receiving the spoken utterance from the user, responsive data by biasing a data selection based on the location characteristic data” is also a mental step. One can mentally generate responsive data according to user specific criteria or bias based on the characteristic data of a user’s current location. Thus, the claimed limitation can be performed by the human mind.
Step 2A prong 2:
The claims recite the limitation “receiving, via an automated assistant, audio data that captures a spoken utterance from the user and that is detected via one or more microphones of the portable computing device, wherein the spoken utterance includes natural language content corresponding to a request for the automated assistant to provide information about a location of interest”. This limitation is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
The claims recite the limitations:
“biasing speech to text processing toward a set of terms determined based on the location characteristic data, the speech to text processing including processing the audio data using a speech recognition machine learning model stored at the portable computing device to generate a recognition of the spoken utterance”,
“wherein biasing speech to text processing toward the set of terms includes restricting biasing of the speech to text processing to a subset, of the set of terms, based on the subset being determined to correspond to a location of interest within the area” and
“using the recognition in generating the responsive data, wherein the recognition comprises a term of the subset of terms to which speech to text processing is biased”.
These limitations are additional elements and are considered to be limitations that merely apply the judicial exception using a computer or computer software such as the machine learning model as a tool to perform the biasing the audio data.
Refer to MPEP 2106.05(f)(1), wherein in the example of Intellectual Ventures I v. Capital One Fin Corp, although the claims purported to modify the underlying XML document in response to the modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. As such, the court held the claims ineligible because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words “apply it”.
Examiner submits that the claims, as amended, similarly only provide the idea of an outcome of processing the audio data using the speech recognition machine learning model to generate a recognition of the data in order to display data responsive to the recognition without claiming steps that specifically describe how this processing of the audio data takes place that would go beyond reciting details of how a solution to a problem is accomplished.
The combination of these additional steps is no more than mere instructions to apply the exception using generic computer components (i.e. the one or more processor) and a speech recognition machine learning model to process and output data. Accordingly, even in combination, these additional steps do not integrate the abstract idea into a practical application because they do not impose meaningful limits on practicing the abstract idea.
The claims recite the limitations:
“prior to receiving audio data that captures the spoken utterance from the user, causing the portable computing device to render output that informs the user that the speech to text processing is biased toward the subset of terms”; and
“rendering, via the automated assistant of the portable computing device, responsive output that is based on the responsive data”.
These limitations are additional elements and are merely outputting data recited at a high level of generality and considered insignificant extra-solution activity as ‘selecting information for display' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claims 1, 9 and 15 recites the following additional elements “one or more processors”, “portable computing device”, “one or more microphones”, “speech recognition machine learning model”, “automated assistant of the portable computing device”, “system”, and “memory”, note that these recited additional elements are a high-level recitation of generic computer hardware and software components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
As explained with respect to Step 2A, Prong Two, the additional elements of “biasing speech to text processing toward a set of terms determined based on the location characteristic data, the speech to text processing including processing the audio data using a speech recognition machine learning model stored at the portable computing device to generate a recognition of the spoken utterance”, “wherein biasing speech to text processing toward the set of terms includes restricting biasing of the speech to text processing to a subset, of the set of terms, based on the subset being determined to correspond to a location of interest within the area” and “using the recognition in generating the responsive data, wherein the recognition comprises a term of the subset of terms to which speech to text processing is biased” are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f).
With respect to the " receiving”, “rendering output” and “rendering responsive output” limitations identified as insignificant extra-solution activity above when re-evaluated these elements are well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, the claims as a whole do not change this conclusion and the claims are ineligible.
Claims 2-4, 6, 10-12, 14, 16-18 and 20 depend from claims 1, 9 and 15 and thus include all the limitations of claim 1,9 and 15 therefore claims 2-4, 6, 10-12, 14, 16-18 and 20 recite the same abstract idea of "mental process".
Claims 2-4, 6, 10-12, 14, 16-18 and 20 furthermore recite that:
(claims 2, 10, 16) “the location characteristic data includes information related to one or more places of interests in the area”;
(claims 3, 11, 17): “biasing includes modifying the request by adding an alias having a defined relationship to the area”;
(claims 4, 12, 18): “biasing includes modifying the request by replacing a pronoun of the request with an alias having a defined relationship to the location of interest”;
(claims 6, 14, 20): “biasing the data selection based on the location characteristic data includes biasing the speech to text processing to an extent that is based on the location characteristic data”.
Step 1: Claims 2-4, 6, 10-12, 14, 16-18 and 20 as a whole fall within one or more statutory categories.
Step 2A prong 1: Claims 2-4, 6, 10-12, 14, 16-18 and 20 recite limitations that are abstract ideas because they depend from claims 1, 9 and 15 which recite mental steps.
The limitation “the location characteristic data includes information related to one or more places of interests in the area” in claims 2, 10 and 16 are mental steps as they further define the location characteristic data found in the mental step of determining, as determined in claims 1, 9 and 15.
The limitations “biasing includes modifying the request by adding an alias having a defined relationship to the area” and “biasing includes modifying the request by replacing a pronoun of the request with an alias having a defined relationship to the location of interest” and in claims 3, 4, 11, 12, 17 and 18 are mental steps. A person can mentally determine a change in the data they would like to request by specifying different criteria for which to search.
Step 2A prong 2:
Claims 6, 14, 20 recite the limitation “biasing the data selection based on the location characteristic data includes biasing the speech to text processing to an extent that is based on the location characteristic data”, which is an additional element and further defines the biasing speech to text processing step in claims 1, 9 and 15, which are additional elements and are considered to be limitations that merely apply the judicial exception using a computer or computer software such as the machine learning model as a tool to perform the biasing the audio data. See Intellectual Ventures I v. Capital One Fin Corp, MPEP 2106.05(f)(1).
Step 2B:
As explained with respect to Step 2A, Prong Two, the additional elements of “biasing the data selection based on the location characteristic data includes biasing the speech to text processing to an extent that is based on the location characteristic data” are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f).
Therefore, claims 2-4, 6, 10-12, 14, 16-18 and 20 as a whole are ineligible.
Claims 5, 13 and 19 depend from claims 1, 9 and 15 and thus include all the limitations of claims 1, 9 and 15, therefore claims 5, 13 and 19 recite the same abstract ideas of "mental processes".
Claims 5, 13 and 19 furthermore recite:
“causing the portable computing device to render a prompt that solicits whether the user desires the automated assistant to bias the data selection”; and
“causing the portable computing device to bias the data selection responsive to receiving an affirmative user input responsive to the prompt”.
Step 1: Claims 5, 13 and 19 as a whole fall within one or more statutory categories.
Step 2A prong 1: Claims 5, 13 and 19 recite limitations that are abstract ideas because they depend from claims 1, 9 and 15 which recite mental steps.
The limitation “bias the data selection responsive to receiving an affirmative user input responsive to the prompt” in claims 5, 13 and 19 is a mental step. A user can choose how to interpret a data selection based on given criteria. Thus, the claimed limitations can be performed by the human mind.
Step 2A prong 2:
Claims 5, 13 and 19 recite the limitation “render a prompt that solicits whether the user desires the automated assistant to bias the data selection” which is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claims 5, 13 and 19 recites the following additional elements “the portable computing device”, note that these recited additional elements are a high-level recitation of generic computer hardware components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the " render a prompt” limitation identified as insignificant extra-solution activity above, when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, claims 5, 13 and 19 as a whole are ineligible.
Claim 7 depends from claim 1 and thus includes all the limitations of claim 1, therefore claim 7 recites the same abstract idea of "mental process".
Claim 7 further recites:
determining that the current location of the user has changed to a second location;
receiving, via an automated assistant of the portable computing device, a second spoken utterance from the user, wherein the second spoken utterance includes natural language content corresponding to a request for the automated assistant to provide information about a second location of interest;
determining whether second location characteristic data is associated with an area that includes the second location, wherein the location characteristic data is accessible via one or more applications of the portable computing device;
in response to determining there is location characteristic data associated with the area that includes the second location:
generating, in response to receiving the second spoken utterance from the user, second responsive data by biasing a data selection based on the second location characteristic data; and
rendering, via the automated assistant of the portable computing device, responsive output that is based on the second responsive data.
Step 1: Claim 7 as a whole falls within one or more statutory categories.
Step 2A prong 1: Claim 7 recites limitations that are abstract ideas because it depends from claim 1 which recites mental steps.
The limitation “determining that the current location of the user has changed to a second location” is a mental step. A user can mentally determine that their location has changed. Thus, the claimed limitation can be performed by the human mind.
The limitations “determining whether second location characteristic data is associated with an area that includes the second location, wherein the location characteristic data is accessible via one or more applications of the portable computing device” and “in response to determining there is location characteristic data associated with the area that includes the second location: generating, in response to receiving the second spoken utterance from the user, second responsive data by biasing a data selection based on the second location characteristic data” are mental steps. A user can determine data associated with the new location and can mentally determine a response to requested information based on how the data is interpreted based on a given criterion. Thus, the claimed limitations can be performed by the human mind.
Step 2A prong 2:
Claim 7 recites the limitation “receiving a second spoken utterance from the user, wherein the second spoken utterance includes natural language content corresponding to a request to provide information about a second location of interest”. This limitation is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Claim 7 recites the limitation “rendering responsive output that is based on the second responsive data”. This limitation is an additional element and is merely outputting data recited at a high level of generality and considered insignificant extra-solution activity as ‘selecting information for display' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claim 7 recites the following additional elements “automated assistant of the portable computing device”, note that these recited additional elements are a high-level recitation of generic computer software components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the "receiving” and “rendering responsive output” limitations identified as insignificant extra-solution activity above, when re-evaluated these element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, claim 7 as a whole is ineligible.
Claim 8 depends from claim 7 and thus includes all the limitations of claim 7, therefore claim 8 recites the same abstract idea of "mental process".
Claim 8 further recites:
generating, in response to receiving the second spoken utterance from the user, unbiased responsive data; and
rendering responsive output that is based on the unbiased responsive data.
Step 1: Claim 8 as a whole falls within one or more statutory categories.
Step 2A prong 1: Claim 8 recites limitations that are abstract ideas because it depends from claim 7 which recites mental steps.
The limitation “generating, in response to receiving the second spoken utterance from the user, unbiased responsive data” is a mental step. A user can mentally determine a response to requested information based on how the data is interpreted. Thus, the claimed limitation can be performed by the human mind.
Step 2A prong 2:
Claim 8 recites the limitation “rendering responsive output that is based on the unbiased responsive data”. This limitation is an additional element and is merely outputting data recited at a high level of generality and considered insignificant extra-solution activity as ‘selecting information for display' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claim 7 recites the following additional elements “the processors”, note that these recited additional elements are a high-level recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the “rendering responsive output” limitation identified as insignificant extra-solution activity above, when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, claim 8 as a whole is ineligible.
To expedite a complete examination of the instant application, the claims rejected under 35 U.S.C. 101 (nonstatutory) above are further rejected as set forth below in anticipation of applicant amending these claims to place them within the four statutory categories of the invention.
Novel and/or Non-obvious Subject Matter
Claims 1-20 were indicated as novel and/or non-obvious for the reasons addressed in the Final rejection dated September 20, 2025.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Lamont et al (US 2006/0230337) directed to: management and delivery of locationally specific information to a user [Abstract; entire document];
Anderson et al (US 7,376,640) directed to: searching for items of interest in proximity to geographical locations provided by the user [Fig 5-10 and related portions of specification];
Erbas et al (US 11,410,646) directed to: performing natural language understanding on utterances using automatic speech recognition techniques to obtain text that is processing using machine learning models; also a final ranker component for biasing results [Abstract; Fig 3-4 and related portions of specification].
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHERYL M SHECHTMAN whose telephone number is (571)272-4018. The examiner can normally be reached on M-F: 10am-6:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amy Ng can be reached on 571-270-1698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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CHERYL M SHECHTMANPatent Examiner
Art Unit 2164
/C.M.S//AMY NG/Supervisory Patent Examiner, Art Unit 2164
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