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 Arguments
Applicant's arguments received 04/03/2026 have been considered but are moot in view of the new ground(s) of rejection. Detailed response is given in sections 3-7 below in this Office Action.
Claim Rejections - 35 USC § 101
3. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 101 that form the basis for the rejections under this section made in this Office action:
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.
4. Claims 1, 3-12, 14-18 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under the 2019 PEG (now been incorporated into MPEP 2106), the revised procedure for determining whether a claim is "directed to" a judicial exception requires a two-prong inquiry into whether the claim recites: (1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human interactions such as a fundamental economic practice, or mental processes); and (2) additional elements that integrate the judicial exception into a practical application (see MPEP § 2106.05(a)-(c), (e)-(h)).
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look to whether the claim: (3) adds a specific limitation beyond the judicial exception that is not "well-understood, routine, conventional" in the field (see MPEP § 2106.0S(d)); or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Claims 1, 3-12, 14-18 and 20 are directed to an abstract idea of extracting a melody from a polyphonic symbolic music file using machine learning model.
Specifically, representative claim 1 recites:
A method for extracting a melody, comprising:
(S1) receiving a polyphonic symbolic music file, wherein the polyphonic symbolic music file comprises a plurality of notes;
(S2) converting the polyphonic symbolic music file to a plurality of feature vectors, wherein each of the plurality of feature vectors is a multidimensional vector, and wherein each of the plurality of feature vectors corresponds to a particular note of the plurality of notes; and
(S3) generating classifications of the plurality of feature vectors corresponding to the plurality of notes using a model, wherein the model is trained to determine whether each of the plurality of notes belongs to the melody based on the plurality of feature vectors.
(S4) constructing a musical instrument digital interface (MIDI) file comprising a subset of the plurality of notes associated with the melody; and
(S5) performing at least one of a music generation task, a music searching task, or a music recommendation task using the MIDI file.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
The highlighted portion of the claim constitutes an abstract idea under the 2019 Revised Patent Subject Matter Eligibility Guidance and the additional elements are NOT sufficient to amount to significantly more than the judicial exceptions, as analyzed below:
Step
Analysis
1. Statutory Category ?
Yes.
method
2A - Prong 1: Judicial Exception Recited?
Yes.
See the bolded portion as listed above.
Under its broadest reasonable interpretation (BRI), the limitation S2 recited in the bolded portion encompasses mathematical relationships, namely a series of calculations leading to one or more numerical results or answers, which also encompasses mental processes, i.e. data manipulation, evaluation and judgment, that can be performed in the human mind or by a human using a pen and paper. Although it does not spell out any particular equation or formula being used, the lack of specific equations for the series of calculations merely indicates that the claim would monopolize all possible math concepts in practicing the method.
Under its BRI, the limitation S3 recited in the bolded portion encompasses mental processes that can be performed in the human mind or by a human using a pen and paper. in light of the USPTO’s July 17, 2024 Subject Matter Eligibility Examples (e.g., Examples 47-49), a computing scheme (e.g., prediction) using a machine learning model is considered an "abstract idea" if the claim focuses solely on the concept of performing the computing using a generic machine learning algorithm (e.g., deep learning, which may include artificial neural networks), without any specific technical improvements or applications that go beyond the basic idea of using a computer to analyze data and generate predictions; essentially, if the claim is too high-level and does not describe a concrete, inventive implementation of the machine learning process. In the instant case, it is deemed that the clamed “model” (including an artificial neural network and/or deep learning process), which is used like a “Black Box AI”, simply applies a trained machine learning model to perform evaluations/judgments and generate the output. Thus, recites mental processes that can be performed in the human mind or by a human using a pen and paper.
Nothing in the bolded portion precludes these limitations from practically being performed in the mind and/or with the aid of pen/paper. Note, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. See CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See also to MPEP 2106.04(a)(2).III
As to the physical parameters/variables recited in the bolded portion, under the BRI, they encompass merely data characterization which can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the relevant technological environment or field of use.
Further, according to the MPEP 2106.04(a)(2), if a claim limitation, under its broadest reasonable interpretation, covers mental processes except for the mention of generic computer components performing computing activities via basic function of the computer, then the claim is likely considered to be directed to an ineligible abstract idea, as it essentially describes a mental process that could be performed by a human without the computer components adding any significant practical application beyond the abstract concept itself.
Therefore, the bolded limitations fall within a combination of the mental process and the math concept groupings of abstract ideas under the 2019 PEG because they cover concepts performed in the human mind, including observation, evaluation, math calculations, judgment, and opinion.
2A - Prong 2: Integrated into a Practical Application?
No.
Under the BRI, the limitation S1 recited in claim 1 encompasses a process of gathering the data/information necessary for performing the abstract idea. The claim does not require any particular devices or sensors to receive the information. Thus, it does not impose any meaningful limits on the claim. See MPEP 2106.05(g)(3): … that were described as mere data gathering in conjunction with a law of nature or abstract idea. See also Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 13863, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering).
Under the BRI, each or the combination of the limitations S3 and S4 recited in claim 1 encompasses insignificant post solution activities. These limitations are not qualified for meaningful limitations to integrate the identified judicial exception into a practical application because they only generally attach post-solution activities and/or a field of use limitations to the judicial exception recited in the pending claims. See Accenture Global Servs., GmbH v. Guidewire Software, Inc., 728 F.3d 1336, 1347-48 (Fed. Cir. 2013) (claims to generating tasks based on rules to be completed upon the occurrence of an event recited an abstract idea and its implementation on a generic computer without any meaningful limitations to the concept did not transform the abstract idea into a patent-eligible application).
Furthermore, the mere instructions to apply a judicial exception on a generic computer and/or link the use of the judicial exception to the relevant technological environment cannot integrate a judicial exception into a practical application at Step 2A of the two-part Alice framework under the 2019 PEG. See MPEP 2106.05(g) and 2106.04(d).
The claim as a whole does not meet any of the following criteria to integrate the abstract idea into a practical application:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Various considerations are used to determine whether the additional elements are sufficient to integrate the abstract idea into a practical application. However, in all of these respects, the claim fails to recite additional elements which might possibly integrate the claim into a particular practical application. At most, it only generally links the judicial exception to a particular technological environment or field of use. See MPEP 2106.04(d)(2).
2B: Claim provides an Inventive Concept?
No.
At Step 2B, consideration is given to additional elements that provide an inventive concept (also called "significantly more" than the recited judicial exception). Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception itself. Because this approach considers all claim elements, the Supreme Court has noted that “it is consistent with the general rule that patent claims ‘must be considered as a whole.’”
In the instant case, focusing on what the inventors have invented exactly, Examiner considers that the “core” of the pending claims is directed to an algorithm of extracting a melody from a polyphonic symbolic music file using machine learning model, which is considered as a judicial exception falling within a combination of the mental process and the math concept groupings of abstract ideas under the 2019 PEG.
Representative claim 1 recites the additional limitations S1, S4 an S5. As discussed above in Step 2A, none of these additional limitations/elements makes the claim significantly more than the abstract idea. Further, under the BRI, it is deemed that these additional limitations recite activities that are all well-understood, routine, conventional in the art (see discussion of the prior art reference in sections 5-7 below), they do not provide any inventive concepts or reflect a qualified improvement. In particular, a process of constructing a Musical Instrument Digital Interface (MIDI) file from music notes may be considered an abstract idea because it is simply a "method of organizing human activity" that merely automates a task traditionally done by hand. The claim essentially describes taking musical notes and converting them into a data file without a specific technical improvement such as a specialized algorithm for MIDI generation that significantly improves computer performance or
a new algorithm for analyzing complex audio signals to generate the MIDI data more efficiently or accurately, rather than just using a generic computer to do the converting/constructing. See MPEP 2106.05 (Eligibility Step 2B: Whether a Claim Amounts to Significantly More).
Therefore, claim 1 is found to be ineligible under 35 U.S.C. 101.
The dependent claims 3-11 inherit attributes of the independent claim 1, but does not add anything which would render the claimed invention a patent eligible application of the abstract idea. The claim merely extends (or narrows) the abstract idea which does not amount for "significant more" because it merely adds details to the algorithm which forms the abstract idea as discussed above.
Claims 12, 14-18 and 20 are treated as ineligible subject matter under 35 U.S.C. § 101 for the same reason as for claims 1 and 3-11 set forth above.
Claim Rejections - 35 USC § 103
5. 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.
6. Claims 1, 8, 10, 12 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Wei et al. (CN 110136730 A, machine translation) in view of GROVES et al. (US 20240038205 A1).
Regarding claims 1, 12 and 18, Wei discloses a method and a system, including computer programs encoded on a storage device, for extracting a melody (para. 0009), comprising: receiving a polyphonic symbolic music file (para. 0013), wherein the polyphonic symbolic music file comprises a plurality of notes (under the broadest reasonable interpretation to the claim, polyphony refers to the number of individual notes an instrument can produce at once; the sound generated by a piano inherently includes polyphony because it's designed to play multiple notes simultaneously); converting the polyphonic symbolic music file to a plurality of feature vectors (para. 0014-0017), wherein each of the plurality of feature vectors is a multidimensional vector, and wherein each of the plurality of feature vectors corresponds to a particular note of the plurality of notes (para. 0017-0020); and generating classifications of the plurality of feature vectors corresponding to the plurality of notes using a model (para. 0040: “the neural network module will output the harmonic sequence of the corresponding style, thereby realizing the automatic harmonic arrangement”; para. 0045), wherein the model is trained to determine whether each of the plurality of notes belongs to the melody based on the plurality of feature vectors (para. 0004, 0040, 0044, 0055); constructing a music file corresponding to the melody based on the generated classifications (para. 0040); and performing at least one of a music generation task (e.g., automatically arranging a specific style of harmony for the main melody according to different song styles, thereby meeting the personalized needs of users; see para. 0007 and 0009) using the constructed music file (Abstract; para. 0007, 0009, 0045).
Wei is silent on: the constructed music file is a musical instrument digital interface (MIDI) file.
GROVES discloses a method for constructing a music file, comprising: classifying input data (para. 0052, 0062, 0098), and defining a corresponding melody (para. 0062, 0077, 0080), and constructing a MIDI file corresponding to the melody based on the classifications of the input data (para. 0038, 0064: “which may then be output as symbolic data (in the form of MIDI messages, in an example) or by synthesized as music synthesis data 130, such as an audio MIDI output 154”).
In view of GROVES’ teaching, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wei to construct a MIDI file corresponding to the melody based on the generated classifications, as an intended use of well-known technique for MIDI file generation. The skilled person would conceive and apply such modification, in view of GROVES, without needing inventive skill but depending on practical considerations and according to the dictates of the circumstances. Doing so would obviously improve the feasibility and applicability of the Wei’s invention.
Regarding claim 8, Wei does not mention explicitly: wherein the model is trained with a focal loss function, the focal loss function configured to balance positive and negative samples.
Examiner takes official notice that techniques of training a machine learning model with a focal loss function which balances positive and negative samples are well-known in the art. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate such well-known techniques into Wei’s method/system to arrive the claimed invention, as an intended use of known technology. The mere application of known technologies to a specific instance by those skilled in the art would have been obvious.
Regarding claims 10 and 17, Wei does not mention explicitly: improving accuracy of the model by maximizing a melody F-measure score.
With the broadest reasonable interpretation to the term “a melody F-measure score” (e.g., the accuracy of the determined notes which belongs to the melody based on the plurality of feature vectors), Examiner takes official notice that techniques of improving prediction accuracy of a machine leaning model, such as optimizing the model by re-training it iteratively with new or better (cleaning, adding more/diverse) training data, are well-known in the art. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate such well-known techniques into Wei’s method/system to arrive the claimed invention, as an intended use of the known techniques. The mere application of known technologies to a specific instance by those skilled in the art would have been obvious.
7. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Wei et al. in view of GROVES et al. as applied to claim 1 above, further in view of Tian (CN 113539214 A, machine translation).
Regarding claim 4, the combination of Wei/GROVES does not mention explicitly: wherein the model is a lightweight deep bidirectional long short-term memory, LSTM, model.
Tian discloses a method for converting a music file (Abstract), comprising: generating classifications (i.e., prediction) of input data using a model, wherein the model is a lightweight deep bidirectional long short-term memory, LSTM, model (see discussion of Fig. 5).
It is well-known that a Deep Bidirectional Long Short-Term Memory (BiLSTM) model is an advanced recurrent neural network (RNN) that processes sequential data in both forward (left-to-right) and backward (right-to-left) directions simultaneously. In view of Tian’ teaching, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate a Deep Bidirectional Long Short-Term Memory (BiLSTM) model into the combination of Wei/GROVES to arrive the claimed invention, as an intended use of known technology. Doing so would obviously improve the feasibility and accuracy of the Wei’s classifications by using multiple stacked LSTM layers to capture richer contextual information from both past and future elements, making it highly effective for complex tasks like speech recognition and time series analyses.
Examiner’s Note
8. While there are related references that discuss melody extraction from polyphonic symbolic music files, the prior art of record does not specifically provide teachings for the particularly claimed limitations including: wherein each of the plurality of feature vectors is a six-dimensional vector indicating features of pitch, duration, absolute pitch distance below, absolute pitch distance above, onset position in bar, and pitch in scale, the absolute pitch distance below feature representing a distance to a pitch of a neighboring lower note of the plurality of notes, the absolute pitch distance above feature representing a distance to a pitch of a neighboring higher note of the plurality of notes, the onset position in bar feature representing a score beat where a corresponding note onset is located within a score bar, and the pitch in scale feature indicating whether a pitch of a corresponding note of the plurality of notes is in a diatonic scale of a key signature (claims 3, 14 and 20), identifying note events indicative of attributes in response to receiving the polyphonic symbolic music file, wherein the attributes comprise start, duration, pitch, and track associated with the polyphonic symbolic music file; consolidating the note events to a single list in response to identifying a plurality of tracks; and extracting a time signature and a key signature associated with the polyphonic symbolic music file (claims 5, 6, 15 and 16), evaluating a performance of the machine learning model using statistic metrics of sparsity and pitch interval of consecutive notes (claim 7), the focal loss function as defined in instant claim 9, and the melody F-measure score as defined in instant claim 11. It is these limitations, as they are claimed in the combination recited in independent claim 1, 12 or 18, that would make the instant claims 3, 5-7, 9, 11, 14-16 and 20 distinguish over the prior art of record.
Conclusion
9. 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 extension fee 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 date of this final action.
Contact Information
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIANCHUN QIN whose telephone number is (571)272-5981. The examiner can normally be reached 9AM-5:30PM EST M-F.
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, Dedei Hammond can be reached at (571)270-7938. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JIANCHUN QIN/Primary Examiner, Art Unit 2837
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