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 .
Claim Rejections - 35 USC § 112
Claims 2,8-12,16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 2,8,10-12,16, the term “optionally” is vague and indefinite, as the metes and bounds are not clearly set forth. Correction is required.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1,4,6,14,15,18,20 is/are rejected under 35 U.S.C. 102(a)(1) as being fully met by Sun et al (SUN C. E. ET AL., Melody Harmonization using Orderless NADE, Chord Balancing, and Blocked Gibbs Sampling. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 13 May 2021, pages 1-5, cited by Applicant).
Regarding Claims 1,14,15, Sun discloses a computer-implemented method of recognising chords in music, the method comprising:
receiving music data for a time interval (3.1, Hooktheory Lead Sheet Dataset);
processing the music data in a machine learning model to output chord data corresponding to the time interval, the chord data comprising a set of chord features (2.3, Fig. 1, (1));
wherein the processing in the machine learning model comprises:
predicting a value of a chord feature from a set of chord features using an Autoregressive Distribution Estimator (ADE) (Introduction, “our model can predict 96 chords”);
modifying the ADE using the predicted value for the chord feature (2.2 Loss Function: “chord weighting”);
using the modified ADE to predict a value for a different feature of the chord from the set of chord features (2.3 Inference: Algorithm 1);
repeating the modifying and predicting until a value for each of the features in the set of chord features have been predicted (2.3 Inference: Algorithm 1 is iterated).
Regarding Claims 4,18, Sun discloses the set of chord features comprises chord root (Fig. 1),
Regarding Claims 6,20, Sun discloses the ADE is a Neural Autoregressive Distribution Estimator (NADE) (Abstract).
Allowable Subject Matter
Claims 2,8-12,16 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claims 3,5,7,13,17,19 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The references cited show related teachings in the art.
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JEFFREY . DONELS
Examiner
Art Unit 2837
/JEFFREY DONELS/Primary Examiner, Art Unit 2837
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