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 .
Response to Amendment
Applicants’ amendment filed on 8/13/26 has been entered. Claims 1, 8, 15 have been amended. Claims 5, 12, 19 have been canceled. New claims 21-23 have been added. Claims 1-4, 6-11, 13-18, 20-23 are still pending in this application, with claims 1, 8, 15 being independent.
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 of this title, 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 1-4, 6, 8-11, 13, 15-18, 20-23 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2020/0066256 to Mossoba et al. (“Mossoba”) in view of U.S. Patent Application Publication No. 2004/0203824 to Mock et al. (“Mock”).
As to claims 1, 8 and 15, Mossoba discloses a computer-implemented method, a system and one or more non-transitory computer readable media, the computer-implemented method comprising: receiving, from a mobile device, audio data representing sound in an environment of the mobile device or contextual data associated with the mobile device [paragraphs 0032, 0034, 0064]; providing the audio data or the contextual data as input to a trained machine learning model [paragraphs 0032, 0034, 0064]; generating, as output from the trained machine learning model, a score relating to a probability of the mobile device having been located at a location of multiple candidate locations at a time when the audio data or the contextual data was generated [paragraphs 0032, 0034, 0039]; associating the mobile device with the location based at least in part on the score [paragraphs 0032, 0034, 0039, 0041]; storing device-to-location association data in memory based at least in part on the associating the mobile device with the location [paragraphs 0032, 0034, 0039, 0041];
Mossoba does not expressly disclose feature of sending, to the mobile device over a telecommunication network, the device-to-location association data indicating the location associated with the mobile device, the device-to-location association data usable by the mobile device to identify a frequency band for connecting to the telecommunications network.
In the same or similar field of invention, Mock discloses feature of sending, to the mobile device over a telecommunication network, the device-to-location association data indicating the location associated with the mobile device, the device-to-location association data usable by the mobile device to identify a frequency band for connecting to the telecommunications network [Mock paragraphs 0017, 0020-0023, 0025, Figs. 6].
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Mossoba to include feature of sending, to the mobile device over a telecommunication network, the device-to-location association data indicating the location associated with the mobile device, the device-to-location association data usable by the mobile device to identify a frequency band for connecting to the telecommunications network as taught by Mock. The suggestion/motivation would have been to optimize communication resources to determine a communication channel for a communication session [Mock paragraph 0005].
As to claims 2, 9 and 16, Mossoba discloses wherein the contextual data is provided as the input to the trained machine learning model [paragraphs 0032, 0034, 0064], and wherein the contextual data comprises at least one of: call history data relating to one or more phone calls made using the mobile device; application usage data relating to one or more mobile applications used by the mobile device; battery charging data relating to charging of a battery of the mobile device; device connection data relating to one or more devices to which the mobile device connected via a wired connection or a wireless connection; settings data relating to one or more settings associated with the mobile device; or sensor data generated by one or more sensors of the mobile device [paragraphs 0019 (sound sensors, vibration data, pressure data, temperature data, humidity data), 0020, 0041].
As to claims 3, 10 and 17, Mossoba discloses wherein the multiple candidate locations comprise an indoor location and an outdoor location [paragraphs 0018, 0039, 0042].
As to claims 4, 11 and 18, Mossoba discloses wherein the output from the trained machine learning model specifies the indoor location as at least one of: a building [paragraphs 0018, 0039]; a subway; a parking garage; a home; or an office [paragraphs 0018, 0039].
As to claims 6 and 13, Mossoba discloses wherein the audio data is provided as the input to the trained machine learning model, and wherein the audio data represents at least one of user speech [paragraphs 0032, 0034, 0064] or background noise in the environment.
As to claim 20, Mossoba discloses wherein both the audio data and the contextual data are provided as the input to the trained machine learning model [paragraphs 0019-0020, 0041].
As to claims 21, 22 and 23, Mossoba discloses wherein the device-to- location association data sent to the mobile device indicates whether the mobile device is located at an indoor location [paragraphs 0018, 0032, 0034, 0039, 0041, 0042].
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2020/0066256 to Mossoba et al. (“Mossoba”) and U.S. Patent Application Publication No. No. 2004/0203824 to Mock et al. (“Mock”) in further view of U.S. Patent Application Publication No. 2021/0201931 to Wang (“Wang”).
As to claims 7 and 14, Mossoba and Mock disclose the computer-implemented method of claim 1 and the system of claim 8 (see rejection of claims 1 and 8]. Further, Mossoba discloses wherein the audio data is provided as the input to the trained machine learning model [paragraphs 0032, 0034, 0039, 0041], and wherein the audio data comprises a sequence of coefficients [paragraph 0029].
Mossoba and Mock do not expressly disclose wherein the audio data comprises an audio impulse response represented by a sequence of coefficients of a space within which the mobile device was located at the time when the audio was generated.
In the same or similar field of invention, Wang discloses the features wherein the audio data comprises an audio impulse response represented by a sequence of coefficients of a space within which the mobile device was located at the time when the audio was generated [Wang Abstract, paragraphs 0022-23, 0042, 0046-47, 50].
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Mossoba and Mock to have feature of the audio data comprises an audio impulse response represented by a sequence of coefficients of a space within which the mobile device was located at the time when the audio was generated as taught by Wang. The suggestion/motivation would have been to provide systems and methods for more realistically and efficiently creating an audio track that includes speech, music, or sound effects that sound to the listener as if they were produced in a specific environment, such as a room, hallway, outdoor venue, etc. [Wang paragraph 0005].
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-4, 6-11, 13-18, 20-23 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
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 ANTIM G SHAH whose telephone number is (571)270-5214. The examiner can normally be reached Mon-Fri 7:30am-4pm.
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/ANTIM G SHAH/Primary Examiner, Art Unit 2693
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