NON-FINAL REJECTION, THIRD DETAILED ACTION
Status of Prosecution
The present application 18/020,820, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The application was filed in the Office on February 10, 2023 and is a national stage application of PCT application PCT/CN2021/111660 (August 10, 2021) which claims priority of to Chinese patent application CN202010798452.4 with a filing date of August 10, 2020.
The Office mailed a first detailed action, non-final rejection on Oct. 1, 2025.
Applicant filed amendments with remarks and arguments on Dec. 31, 2025.
The Office mailed a second detailed action, final rejection on Jan. 26, 2026.
Applicant filed a request for continued examination amendments with remarks and arguments on April 27, 2026.
Claims 1-6, 8-9, 11-17 and 19-20 are pending and are all rejected in this rejection. Claims 1, 11 and 12 are independent claims. Claims 7. 10 and 18 are cancelled.
Status of Claims
Claims 1, 4-6, 8-9, 11-12, 15-16 are rejected under 35 USC § 103 as being unpatentable over Jiang et al. (“Jiang”), Chinese Patent Application Publication CN109240637B published on January 18, 2019 in view of Kim et al. (“Kim ‘823”), United States Patent 2021/0255823 published on Aug. 19, 2021..
Claims 8-9 and 19-20 are rejected under 35 USC § 103 as being unpatentable over Jiang in view of Kim ‘823 and in further view of Kim et al. (“Kim”), United States Patent Application Publication 2011/0261267 published on Oct. 27, 2011.
Claims 2-3 and 13-14 are rejected under 35 USC § 103 as being unpatentable over Jiang in view of Kim ‘823 and in further view of VanBlon et al. (“VanBlon”), United States Patent Application Publication 2019/0079720 published on Mar. 14, 2019.
Claims 7, 10 and 18 are cancelled.
Response to Remarks and Arguments
Examiner thanks Applicant for the remarks and arguments.
Finally, regarding the prior art rejections, Examiner has newly rejected the claims with the application of Kim et al. (“Kim ‘823”), United States Patent 2021/0255823 published on Aug. 19, 2021.
The claims stand rejected.
Request for Continued Examination
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 April 27, 2026 has been entered.
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 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.
-A.
Claims 1, 4-6, 8-9, 11-12, 15-16 are rejected under 35 USC § 103 as being unpatentable over Jiang et al. (“Jiang”), Chinese Patent Application Publication CN109240637B published on January 18, 20191 in view of Kim et al. (“Kim ‘823”), United States Patent 2021/0255823 published on Aug. 19, 2021.
As to Claim 1, Jiang teaches: A method for recommending a volume, comprising:
acquiring a feature corresponding to a playing operation for an audio and/or video file by a user, wherein the feature represents a playing habit of the user (Jiang: Fig. 1, p. 5, at step [102], the historical data of audio or video of a user’s consumption (i.e. feature) is analyzed to determine the target playback volume), and inputting the feature into a volume recommendation model of the user (Jiang: p. 5, at step [10212], the decision tree model is trained by using information from the historical data in the form of training data set), and
processing the feature by the volume recommendation model wherein the volume recommendation model is a machine learning model acquired by training based on a correspondence between a feature and a volume setting in historical audio and/or video playing behaviors of the user (Jiang: pp. 5-6, the model is trained based on the data from the training data set by for instance manually labeling a portion of the data to get a “most appropriate volume”);
playing the audio and/or video file at the volume recommended for the user (Jiang: par. 013, the device is controlled to play the volume at the recommended volume).
[AltContent: rect]
PNG
media_image1.png
584
786
media_image1.png
Greyscale
Jiang may not explicitly teach: wherein the feature comprises a feature of a playing device, wherein the feature of the playing device comprises a connection state of the playing device to an output device and a type of the playing device;
processing the feature by the volume recommendation model to output a volume recommended for the user.
Kim ‘823 teaches in general concepts related to controlling output based on priority of different devices (Kim ‘823: Abstract). Specifically, Kim ‘823 teaches that the audio volume may be adjusted based on the connection history of the devices (Kim ‘823: pars. 0035-37, the priority of the devices is determined based on the connection or playback history, which in turn determines the audio level to be played back).
It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the application to have modified the Jiang disclosures and teachings by implementing the volume level adjustment with the features as taught and suggested by Kim ‘823. Such a person would have been motivated to do so with a reasonable expectation of success to allow for a better user experience for the user reducing cognitive burden with automatic volume adjustment.
As to Claim 4, Jiang and Kim ‘823 teach the elements of claim 1.
Jiang further teaches: wherein before the inputting the feature into a pre-generated volume recommendation model, and processing the feature by the volume recommendation model to output a volume recommended for the user, the method further comprises:
acquiring a playing habit of the user for the audio and/or video file, wherein the playing habit comprises at least one of playing device information for the audio and/or video file and/or attribute information of the audio and/or video file (Jiang: p. 5, the volume profile of a song, that is the volume correlated with the volume range and the volume values are attributes of the audio file), and the playing habit further comprises playing scenario information and playing volume information of the audio and/or video file; and
generating the volume recommendation model of the user based on the playing habit through machine learning (Jiang: pp. 5-6, the model is trained based on the data from the training data set by for instance manually labeling a portion of the data to get a “most appropriate volume”).
As to Claim 5, Jiang and Kim ‘823 teach the elements of claim 4.
Jiang further teaches: wherein the generating the volume recommendation model of the user based on the playing habit through machine learning comprises: clustering information in the acquired playing habit of the user for the audio and/or video file, to acquire the volume recommendation model of the user.
As to Claim 6, Jiang and Kim ‘823 teach the elements of claim 4.
Jiang further teaches: wherein the generating the volume recommendation model of the user based on the playing habit through machine learning comprises: classifying information in the playing habit by using the playing volume information in the acquired playing habit of the user for the audio and/or video file as a target, to acquire the volume recommendation model of the user (Jiang: pp. 5-6, the model is trained based on the data from the training data set by for instance manually labeling a portion of the data to get a “most appropriate volume.” (i.e. a target)).
As to Claim 11, it is rejected by claim 1. Jiang further teaches a computer readable storage medium (Jiang: p.8, embodiment 6).
As to Claim 12, it is rejected by claim 1. Jiang further teaches a processor, and a program stored in the memory storage medium (Jiang: p.8, embodiment 5).
As to Claim 15, it is rejected by claim 4.
As to Claim 16, it is rejected by claim 5.
As to Claim 17, it is rejected by claim 6.
B.
Claims 8-9 and 19-20 are rejected under 35 USC § 103 as being unpatentable over Jiang et al. (“Jiang”), Chinese Patent Application Publication CN109240637B published on January 18, 2019 in view of Kim et al. (“Kim ‘823”), United States Patent 2021/0255823 published on Aug. 19, 2021 and in further view of Kim et al. (“Kim”), United States Patent Application Publication 2011/0261267 published on Oct. 27, 2011.
As to Claim 8, Jiang and Kim ‘823 teach the elements of claim 1.
Jiang and Kim ‘823 may not explicitly teach: wherein the playing audio and/or video file at the volume recommended for the user comprises: displaying the volume recommended for the user; and
playing the audio and/or video file at the volume in response to a confirmation operation on the volume.
Kim teaches in general concepts related controlling an electronic device for receiving electricity service charge information and controlling the device based on that information (Kim: Abstract). Specifically, Kim teaches that a user is prompted to confirm the change in a volume once a scenario of an electricity charge change is detected. (Kim: Fig. 15, pars. 0178-79, a user interface prompting the user [60c] to confirm the change in the volume at step [S330]).
PNG
media_image2.png
744
471
media_image2.png
Greyscale
It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the application to have modified the Jiang-Kim ‘823 disclosures and teachings by implementing the volume level adjustment as a user prompt as taught and suggested by Kim. Such a person would have been motivated to do so with a reasonable expectation of success to allow for a better user experience for the user with confirmation before volume changes are made.
As to Claim 9, Jiang, Kim ‘823 and Kim teach the elements of claim 8.
Jiang and Kim as combined further teaches: wherein after the displaying the volume recommended for the user, the method further comprises: adjusting the volume recommended for the user, to acquire an adjusted volume (Jiang: par. 013, the device is controlled to play the volume at the recommended volume);
and playing the audio and/or video file at the adjusted volume in response to a confirmation operation on the adjusted volume (Kim: Fig. 16, pars. 0178-79, a user interface prompting the user [60c] to confirm the change in the volume at step [S330]).
PNG
media_image3.png
373
471
media_image3.png
Greyscale
As to Claim 19, it is rejected by claim 8.
As to Claim 20, it is rejected by claim 9.
C.
Claims 2-3 and 13-14 are rejected under 35 USC § 103 as being unpatentable over Jiang et al. (“Jiang”), Chinese Patent Application Publication CN109240637B published on January 18, 2019 in view of Kim et al. (“Kim ‘823”), United States Patent 2021/0255823 published on Aug. 19, 2021 and in further view of VanBlon et al. (“VanBlon”), United States Patent Application Publication 2019/0079720 published on Mar. 14, 2019.
As to Claim 2, Jiang and Kim ‘823 teach the elements of claim 1.
Jiang and Kim ‘823 may not explicitly teach: wherein the feature comprises a playing scenario feature, and the playing scenario feature comprises a playing time and/or a playing location.
VanBlon teaches in general concepts related to dynamically changing sound settings of a device (VanBlon: Abstract). Specifically, VanBlon teaches that the contextual situation of a device may be considered including time and location to determine volume adjustments (VanBlon: par. 0047, the location, calendar events, ambient noise levels and time of day may be used for monitoring continuously).
It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the application to have modified the Jiang-Kim disclosures and teachings by considering context in the volume adjustment as taught and suggested by Kim. Such a person would have been motivated to do so with a reasonable expectation of success to allow for a better user experience for the user with automated settings related to time and location to reduce the cognitive burden on the user (VanBlon: par. 0002).
As to Claim 3, Jiang, Kim ‘823 and VanBlon teach the elements of claim 2.
Jiang, Kim ‘823 and VanBlon further teach: wherein the feature further comprises an attribute feature of the audio and/or video file, and/or a feature of a playing device (Examiner’s note: the use of “and/or” here is under a broadest reasonable interpretation as the conjunctive.),
wherein the attribute feature of the audio and/or video file comprises volume information of the audio and/or video file (Jiang: p. 5, the volume profile of a song, that is the volume correlated with the volume range and the volume values are attributes of the audio file), and/or type information of the audio and/or video file; and
the feature of the playing device comprises a connection state of the playing device to an output device and/or a type of the playing device.
As to Claim 13, it is rejected by claim 2.
As to Claim 14, it is rejected by claim 3.
Conclusion
Prior art made of the record:
Li et al., US PG Pub 2017/0180558 (June 22, 2017) (describing media playback system context adjustment);
Charlton et al., US PG Pub 2020/0076388 (Mar. 5, 2020) (describing media playback system with maximum volume setting).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES T TSAI whose telephone number is (571)270-3916. The examiner can normally be reached M-F 8-5 Eastern.
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, Viker Lamardo can be reached on 571-270-5871. 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./JAMES T TSAI
/JAMES T TSAI/ Primary Examiner, Art Unit 2147
1 Citations are to the translated copy provided with this Action.
Prosecution Insights