DETAILED ACTION
In the response to this office action, the examiner respectfully requests that support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line numbers in the specification and/or drawing figure(s). This will assist the examiner in prosecuting this application.
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 .
Drawings
The drawings are objected to because:
Figure 5 shows a key which is most likely intended for color figures. This makes the key unclear in black and white drawings. Different types of dashed lines is suggested to make it clear in black and white.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description:
Figure 2 shows item 212 not mentioned in the specification.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 1-9 and 12-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1, the limitation of determining, based on a set of DI features, a placement of each of the plurality of loudspeakers relative to a listener, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a generic trained machine-learning model. That is, other than reciting “by a trained machine-learning model”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a trained machine-learning model” language, “determining” in the context of this claim encompasses the user manually determining where left, right, center, etc. speakers are to be placed for audio reproduction based on collected data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Additionally, the limitations of “determining human directivity index (DI) pattern data corresponding to a location of a listener” is a mathematical calculation of a ratio of acoustical energy which can be calculated mentally or with pencil and paper given input data as stated, “based on vocalization recorded by a microphone at each of a plurality of loudspeakers” is an insignificant data gather step as is collecting pattern data through measurement via a microphone. Further the “extracting a set of DI features from the DI pattern data” is a mental process of selecting DI values. Note the DI values from the table in paragraph [0019] from which a person may select/extract DI values for reasons such as grouping only the L speaker data (the claimed “feature”) to determine the placement of the L speaker. Also note in paragraph [0021] DI values can be features. “Providing the set of DI features to a trained machine-learning model” is an insignificant extra solution activity of providing the value to generic computer components at a high level generality.
This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a trained machine-learning model. The model is only recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic machine-learning component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a generic machine-learning model to perform the determining step amounts to no more than mere instructions to automate the determining of the placement using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Claims 12 and 13 are rejected in an analogous manner to claim 1, given the recited media, loudspeakers, and microphones are just conventional items used in a conventional manner.
Claims 2-9 and 14-20 only further define the mental processes or the DI pattern data.
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) 1-4, 6, 9, 12-16, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bharitkar et al. (US 20220159401 A1) in view of Dyonisio et al. (US 20230217173 A1).
Regarding claim 13, Bharitkar discloses a system comprising:
a plurality of loudspeakers (figure 1, items 104-114);
at least one microphone (paragraph [0020], see claim 8); and
one or more non-transitory computer readable storage media (paragraph [0019]) storing instructions (paragraph [0019]); and one or more processors (paragraph [0019]) coupled to the one or more non-transitory computer readable storage media and operable to execute the instructions to (paragraph [0019]):
determine human directivity index (DI) pattern data corresponding to a location of the listener (information on the location of the listener, see abstract, paragraphs [0017], [0019] to [0023], and [0032] to [0033]), based on sound recorded by a microphone (paragraph [0020], see claim 8);
extract a set of DI features from the DI pattern data (data may be based on microphone and other sensors such as camera, paragraph [0037], features such as facial features, man/woman info etc.);
provide the set of DI features to a trained machine-learning model (paragraphs [0027] to [0028], [0031] to [0033], figure 3, and claim 11); and
determine, by the trained machine-learning model and based on the set of DI features, a placement of each of the plurality of loudspeakers relative to the listener (see abstract, paragraphs [0027] to [0028], [0031] to [0033], figure 3, and claim 11).
Bharitkar does not expressly disclose using vocalizations.
Dyonisio discloses in a system comprising a plurality of microphones, each microphone co-located with at least one of the plurality of loudspeakers such that each of the plurality of loudspeakers is co-located with at least one of the plurality of microphones (paragraph [0013], “at least some of the microphones and at least some of the loudspeakers are implemented in (or coupled to) smart audio devices”, paragraph [0031], “A smart speaker may include a network connected speaker and microphone for cloud based services”); and
determining human directivity index (DI) pattern data (any information regarding the location of the user) corresponding to a location of a listener, based on vocalization (see abstract) recorded by a microphone (see at least the abstract and paragraphs [0002], [0005], and [0068]) at each of a plurality of loudspeakers (paragraph [0013], “at least some of the microphones and at least some of the loudspeakers are implemented in (or coupled to) smart audio devices”, paragraph [0031], “A smart speaker may include a network connected speaker and microphone for cloud based services”).
It would have been obvious to a person of ordinary skill in the art to use the vocalizations of Dyonisio in the system of Bharitkar for the benefit of allowing the user to announce their presence and location in a hands free manner. Therefore, it would have been obvious to combine Dyonisio with Bharitkar, for the benefits above, to obtain the invention as specified in claim 13.
Regarding claim 14, Bharitkar discloses further comprising one or more processors (paragraph [0019]) configured to execute the instructions to adjust, based on the determined placement of each of the plurality of loudspeakers relative to the listener, an audio playback setting of one or more of the plurality of loudspeakers (paragraphs [0032] to [0033]).
Regarding claim 15, Bharitkar discloses wherein the audio playback setting comprises a spatial perception correction (paragraphs [0032] to [0033]).
Regarding claim 16, Bharitkar discloses wherein the placement comprises a distance of each of the plurality of loudspeakers relative to the listener (paragraphs [0019] to [0020], 508 of figure 5).
Regarding claim 18, Bharitkar discloses wherein the trained machine-learning model comprises a trained neural network (paragraph [0028], claim 11).
Regarding claim 1, Bharitkar discloses a method comprising:
determining human directivity index (DI) pattern data corresponding to a location of a listener (information on the location of the listener, see abstract, paragraphs [0017], [0019] to [0023], and [0032] to [0033]), based on sound recorded by a microphone (paragraph [0020], see claim 8);
extracting a set of DI features from the DI pattern data (data may be based on microphone and other sensors such as camera, paragraph [0037], features such as facial features, man/woman info etc.);
providing the set of DI features to a trained machine-learning model (paragraphs [0027] to [0028], [0031] to [0033], figure 3, and claim 11); and
determining, by the trained machine-learning model and based on the set of DI features, a placement of each of a plurality of loudspeakers relative to the listener (see abstract, paragraphs [0027] to [0028], [0031] to [0033], figure 3, and claim 11).
Bharitkar does not expressly disclose using vocalizations.
Dyonisio discloses determining human directivity index (DI) pattern data (any information regarding the location of the user) corresponding to a location of a listener, based on vocalization (see abstract) recorded by a microphone (see at least the abstract and paragraphs [0002], [0005], and [0068]) at each of a plurality of loudspeakers (paragraph [0013], “at least some of the microphones and at least some of the loudspeakers are implemented in (or coupled to) smart audio devices”, paragraph [0031], “A smart speaker may include a network connected speaker and microphone for cloud based services”).
It would have been obvious to a person of ordinary skill in the art to use the vocalizations of Dyonisio in the system of Bharitkar for the benefit of allowing the user to announce their presence and location in a hands free manner. Therefore, it would have been obvious to combine Dyonisio with Bharitkar, for the benefits above, to obtain the invention as specified in claim 1.
Claims 2-4 and 6 are rejected in an analogous manner to claims 14-16 and 18 respectively.
Regarding claim 9, Dyonisio discloses further comprising:
detecting a predetermined command vocalization by the listener; and determining the human DI pattern data in response to detecting the predetermined command vocalization (paragraphs [0035] and [0015],j “Tracking of the user location may be performed in response to sound uttered by the user (e.g., a voice command)”).
Claim 12 is rejected in an analogous manner to claim 13.
Allowable Subject Matter
Claim 10 and 11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DOUGLAS JOHN SUTHERS whose telephone number is (571)272-0563. The examiner can normally be reached M-F, 8 am -5 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vivian Chin can be reached at 571-272-7848. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DOUGLAS J SUTHERS/Examiner, Art Unit 2695
/VIVIAN C CHIN/Supervisory Patent Examiner, Art Unit 2695