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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-11 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jancsy (US 2020/0074876 A1).
Claims 1 and 5: Jancsy discloses a musical piece generation device and method executed by a computer, comprising: an electronic controller including at least one processor, the electronic controller being configured to execute a plurality of modules including a data acquisition module configured to acquire target musical piece data selected by a student indicating at least a part (segment) of a musical piece, a parameter acquisition module configured to acquire by measuring a value of a difficulty level parameter, a generation module configured to generate from the target musical piece data and the value of the difficulty level parameter, new musical piece data indicating at least a part of a new musical piece obtained by changing a difficulty level of the musical piece to a difficulty level specified by the difficulty level parameter (page 3 paragraph [0022]), and an output module configured to output the new musical piece data that has been generated (page 6 paragraph [0025]). The new musical piece data is generated by using a trained generative model (Markov model) (page 7 paragraph [0026]).
Claims 2 and 6: Jancsy discloses a musical piece generation device and method where the new musical piece is generated by changing a difficulty level of the musical piece, as stated above. The value of the difficulty level parameter is disclosed to indicate a width of a performance sound range corresponding to pitches that are the same or different of the new musical piece (page 8 paragraph [0030]).
Claims 3 and 7: Jancsy discloses a musical piece generation device and method where the new musical piece is generated by changing a difficulty level of the musical piece, as stated above. The value of the difficulty level parameter is disclosed to indicate a maximum number of simultaneously operated operators in a musical instrument used to play a chord (page 9 paragraph [0036]), as is known in the art.
Claims 4 and 8: Jancsy discloses a musical piece generation device and method as stated above, where the target musical piece data include an input token sequence (segment) arranged to indicate at least the part of the musical piece, and the new musical piece data include an output token sequence that is output from the trained generative model and arranged to indicate at least the part of the new musical piece (page 9 paragraph [0039]).
Claim 9: Jancsy discloses a model generation method executed by a computer comprising: acquiring a plurality of training datasets each of which includes a combination of training data (musical score) and correct answer data (musical score model), the training data including training musical piece data that indicate at least a part (segment) of a musical piece and including a difficulty level parameter for training, the correct answer data including new training musical piece data indicating at least a part of a new musical piece generated by changing a difficulty level of the musical piece of the training musical piece data to a difficulty level specified by the difficulty level parameter (page 3 paragraph [0022]); and executing machine learning of a generative model by using the plurality of training datasets that have been acquired, the machine learning being configured by training the generative model via Markov model such that, with respect to each of the training datasets, musical piece data, which are generated by the generative model from the training musical piece data and a value of the difficulty level parameter that are included in the training data (page 7 paragraph [0026]), match the new training musical piece data included in the correct answer data in order to compare a student’s performance audio model to a reference audio model to (page 6 paragraph [0025]).
Claim 10: Jancsy discloses a model generation method where the new musical piece is generated by changing a difficulty level of the musical piece, as stated above. The value of the difficulty level parameter is disclosed to indicate a width of a performance sound range corresponding to pitches that are the same or different of the new musical piece (page 8 paragraph [0030]).
Claim 11: Jancsy discloses a model generation method where the new musical piece is generated by changing a difficulty level of the musical piece, as stated above. The value of the difficulty level parameter is disclosed to indicate a maximum number of simultaneously operated operators in a musical instrument used to play a chord (page 9 paragraph [0036]), as is known in the art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER UHLIR whose telephone number is (571)270-3091. The examiner can normally be reached M-F 8:30-4.
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, Anita Coupe can be reached at 571-270-3614. 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.
/Christopher Uhlir/Primary Examiner, Art Unit 3619 December 23, 2025