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 filed 10/31/2025 have been fully considered but they are not persuasive.
Regarding the 101 rejections, on pages 13 of “Remarks” applicant contends that the amended claim 1 does not recite abstract ideas under Step 2A Prong 1. The examiner respectfully disagrees. The amended limitations of generating, by using the user input, a plurality of input music features derived from the original music data that are not in a concatenating relationship,…new extension music data obtained from the plurality of input music features having alterations determined based on the user input, wherein the alterations facilitate concatenation of musical elements corresponding to the plurality of input music features with musical continuity between the new extension music data and the original music data, under the broadest reasonable interpretation, includes a step of observation, evaluation, and judgement and could be performed mentally or with pen and paper like taking features from different musical sources and extending a musical score with the features while maintaining harmony, which is either a mental process of evaluation/judgement (MPEP 2106)). Therefore, the amended claim 1 still recites an mental process abstract idea.
On pages 13-14 of “Remarks” applicant contends that the amended claim 1 provides a practical application under Step 2A Prong 2. The examiner respectfully disagrees. Applicant contends that the claimed invention recites elements that integrate the abstract ideas into a practical application by providing a technical solution. The examiner respectfully disagrees. The amended claim 1 recites the additional elements of receiving user input specifying a directionality of alteration for extending original music data and the trained model is configured to output a outputs the plurality of output music features having the alterations; and displaying the generated new extension music data as an extension of the original music data. Under the broadest reasonable interpretation, the limitations merely recites steps of mere data gathering or mere data outputting and the courts have found that the steps of mere data gathering/outputting to be insignificant extra solution activity and thus does not integrate the abstract ideas into a practical application (MPEP 2106.05(g)). Further, the amended claim also recites the additional element of using a trained model. Under the broadest reasonable interpretation, the limitation recites using a generic trained model to perform abstract ideas which merely add the words “apply it”, or an equivalent, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and thus does not integrate the abstract ideas into a practical application (MPEP 2106.05(f)).
Additionally, it appears that the proposed improvement in this case is only realized because of the judicial exception used in the claim. The judicial exception itself cannot provide the improvement. See: “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” (MPEP 2106.05(a)).
On pages 14 of “Remarks” applicant contends that the amended claim 1 recites additional elements that are not well understood, routine, or conventional activities under Step 2B. The examiner respectfully disagrees. As discussed above, the amended limitations of claim 1 still recite mental process abstract ideas. Additionally, the mention of performing the identified abstract ideas using a trained model, under the broadest reasonable interpretation, merely recite steps that apply generic computer components to perform an abstract idea which represents merely adding the words “apply it”, or an equivalent, which are not indicative of an inventive concept (MPEP 2106.05(f)). Under Step 2B, the courts have found that adding the words “apply it”, or an equivalent, with the judicial exception does not qualify as significantly more under Step 2B (MPEP 2106.05). Further, the additional elements of receiving data and displaying data, under the broadest reasonable interpretation, recite steps of mere data gathering/outputting, which has been recognized by the courts as being well-understood, routine, and conventional functions. Specifically, the courts have recognized computer functions directed to mere data gathering/outputting as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(g)). Therefore, applicant’s arguments regarding the 101 rejections are not persuasive.
Regarding the 103 rejections, applicant's arguments filed with respect to the prior art rejections have been fully considered but they are moot. Applicant has amended the claims to recite new combinations of limitations. Applicant's arguments are directed at the amendment. Please see below for new grounds of rejection, necessitated by Amendment.
Claim Rejections - 35 USC § 101
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.
Claims 1-12 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1, in step 1 of the 101 analysis set forth in MPEP 2106, the claim recites An information processing method for generating music data, the method comprising;. The claim recites a method. A method is one of the four statutory categories of invention.
In Step 2A, Prong 1 of the 101 analysis set forth in MPEP 2106, the examiner has determined that the following limitations recite a process that, under broadest reasonable interpretation, covers a mental process or mathematical concept but for the recitation of generic computer components:
generating, by using the user input, a plurality of input music features derived from the original music data that are not in a concatenating relationship,…new extension music data obtained from the plurality of input music features having alterations determined based on the user input, wherein the alterations facilitate concatenation of musical elements corresponding to the plurality of input music features with musical continuity between the new extension music data and the original music data, (i.e., the broadest reasonable interpretation includes a step of observation, evaluation, and judgement and could be performed mentally or with pen and paper like taking features from different musical sources and extending a musical score with the features while maintaining harmony, which is either a mental process of evaluation/judgement (MPEP 2106)).
If the claim limitations, under their broadest reasonable interpretation, covers activities classified under Mental processes: concepts performed in the human mind (including observation, evaluation, judgement, or opinion) (see MPEP 2106.04(a)(2), subsection (III)) or Mathematical concepts: mathematical relationships, mathematical formulas or equations, or mathematical calculations (see MPEP 2106.04(a)(2), subsection (I)). Accordingly, the claim recites an abstract idea.
In Step 2A, Prong 2 of the 101 analysis, set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application:
receiving user input specifying a directionality of alteration for extending original music data; (i.e., the broadest reasonable interpretation of receiving data is mere data gathering/outputting, which is an insignificant extra solution activity (MPEP 2106.05(g))).
and a trained model (i.e., the generic computer components recited in this limitation merely add the words “apply it”, or an equivalent, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f))).
and wherein, upon receiving the user input with respect to the original music data, the trained model is configured to output a plurality of output music features having the alterations; (i.e., the broadest reasonable interpretation of outputting features is mere data gathering/outputting, which is an insignificant extra solution activity (MPEP 2106.05(g))).
and displaying the generated new extension music data as an extension of the original music data. (i.e., the broadest reasonable interpretation of displaying features is mere data gathering/outputting, which is an insignificant extra solution activity (MPEP 2106.05(g))).
Since the claim does not contain any other additional elements, that amount to integration into a practical application, the claim is directed to an abstract idea.
In Step 2B of the 101 analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception:
Regarding limitations (I) and (III-IV), under the broadest reasonable interpretation, recite steps of mere data gathering/outputting, which has been recognized by the courts as being well-understood, routine, and conventional functions. Specifically, the courts have recognized computer functions directed to mere data gathering/outputting as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity when considering evidence in view of Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018), see USPTO Berkheimer Memorandum (April 2018)).
Examiner uses Berkheimer: Option 2, a citation to one or more of the court decisions discussed in MPEP 2106.05(d)(II) as noting well-understood, routine, and conventional nature of the additional elements:
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). See MPEP 2106.05(d)(II).
Further, limitation (II), under the broadest reasonable interpretation, merely recite steps that apply a generic trained machine learning model to perform a judicial exception, which represents merely adding the words “apply it”, or an equivalent, which are not indicative of an inventive concept (MPEP 2106.05(f)). Considering additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible.
Regarding claim 2, it is dependent upon claim 1 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 2 recites wherein the plurality of input music features includes features extracted from partial data having a data length shorter than a data length of the new extension music data. Under the broadest reasonable interpretation, the limitations recite altering features that are partial data which is a step of observation, evaluation, and judgement which can be performed mentally or with pen and paper. The steps of observation, evaluation, and judgement are mental processes thus, claim 2 does not solve the deficiencies of claim 1.
Regarding claim 3, it is dependent upon claim 1 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 3 recites wherein each of the plurality of input music features is a feature extracted from partial data having a data length shorter than a data length of the new extension music data, and wherein the new extension music data has the same data length as a total data length of each piece of partial data corresponding to each of the plurality of input music features. Under the broadest reasonable interpretation, the limitations recite combining the altered partial features to create new data which is a step of observation which can be performed mentally or with pen and paper. The step of observation is a mental process thus, claim 3 does not solve the deficiencies of claim 1.
Regarding claim 4, it is dependent upon claim 1 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 4 recites further comprising: generating additional new extension music data obtained from the plurality of output music features having further alterations,. Under the broadest reasonable interpretation, the limitations recite altering features more than once which is a step of observation, evaluation, and judgement which can be performed mentally or with pen and paper. The steps of observation, evaluation, and judgement are mental processes. Claim 4 also recites the generation of the additional new extension music data performed using the plurality of output music features and iteratively using the trained model. Under the broadest reasonable interpretation, merely recites steps that apply a generic trained model to perform a judicial exception which represents merely adding the words “apply it”, or an equivalent, which are not indicative of an inventive concept (MPEP 2106.05(f)). Therefore, claim 4 does not solve the deficiencies of claim 1.
Regarding claim 5, it is dependent upon claim 4 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 5 recites further comprising: displaying the new extension music data and the additional new extension music data that have been generated and a number of times of alterations to generate each of the plurality of output music features by the iterative use of the trained model, in association with each other. Under the broadest reasonable interpretation, the limitations recite steps displaying outputs which recite steps of mere data outputting, which has been recognized by the courts as being well-understood, routine, and conventional functions. Specifically, the courts have recognized computer functions directed to mere data gathering/outputting as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(d)). Therefore, claim 5 does not solve the deficiencies of claim 4.
Regarding claim 6, it is dependent upon claim 1 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 6 recites further comprising: generating the new extension music data by also using an additional feature determined with respect to the plurality of input music features. Under the broadest reasonable interpretation, the limitations recite making alterations to features based on a criteria which is a step of observation, evaluation, and judgement which can be performed mentally or with pen and paper. The steps of observation, evaluation, and judgement are mental processes. Therefore, claim 6 does not solve the deficiencies of claim 1.
Regarding claim 7, it is dependent upon claim 6 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 7 recites further comprising: displaying the new extension music data that has been generated and the directionality of an alteration given by the additional feature, in association with each other. Under the broadest reasonable interpretation, the limitations recite steps displaying outputs which recite steps of mere data outputting, which has been recognized by the courts as being well-understood, routine, and conventional functions. Specifically, the courts have recognized computer functions directed to mere data gathering/outputting as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(d)). Therefore, claim 7 does not solve the deficiencies of claim 6.
Regarding claim 8, it is dependent upon claim 6 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 8 recites further comprising: displaying the additional feature corresponding to the new extension music data that has been generated. Under the broadest reasonable interpretation, the limitations recite steps displaying outputs which recite steps of mere data outputting, which has been recognized by the courts as being well-understood, routine, and conventional functions. Specifically, the courts have recognized computer functions directed to mere data gathering/outputting as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(d)). Therefore, claim 8 does not solve the deficiencies of claim 6.
Regarding claim 9, it is dependent upon claim 1 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 9 recites wherein the plurality of input music features includes one or more features sampled from a standard normal distribution of the original music data. Under the broadest reasonable interpretation, the limitations recite features to be altered are selected based on a probability which is a step of observation, evaluation, and judgement which can be performed mentally or with pen and paper. The steps of observation, evaluation, and judgement are mental processes thus, claim 9 does not solve the deficiencies of claim 1.
Regarding claim 10, it is dependent upon claim 9 and fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. For example, claim 10 recites wherein a feature sampled from the standard normal distribution of the original music data is used instead of a feature extracted from partial data having a data length shorter than a data length of the new extension music data. Under the broadest reasonable interpretation, the limitations recite determining whether to select a feature from a first or second source which is a step of observation, evaluation, and judgement which can be performed mentally or with pen and paper. The steps of observation, evaluation, and judgement are mental processes thus, claim 10 does not solve the deficiencies of claim 9.
Regarding claim 11, in step 1 of the 101 analysis set forth in MPEP 2106, the claim recites An information processing apparatus comprising: circuitry configured to. The claim recites an apparatus comprising a circuit which is interpreted as a machine. A machine is one of the four statutory categories of invention. For the Step 2A/2B analyses, since claim 11 is similar to claim 1 it is rejected under the same rationales as claim 1.
The additional limitation below fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception.
circuitry configured to (i.e., the generic computer components recited in this limitation merely add the words “apply it”, or an equivalent, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f))).
Considering additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible.
Regarding claim 12, in step 1 of the 101 analysis set forth in MPEP 2106, the claim recites A non-transitory computer-readable storage medium. The claim recites a computer program product which is interpreted as an article of manufacture. An article of manufacture is one of the four statutory categories of invention. For the Step 2A/2B analyses, since claim 12 is similar to claim 1 it is rejected under the same rationales as claim 1.
The additional limitation below fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception.
A non-transitory computer-readable storage medium having embodied thereon an information processing program, which when executed by a computer causes the computer to function execute a method for generating music data (i.e., the generic computer components recited in this limitation merely add the words “apply it”, or an equivalent, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f))).
Considering additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible.
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, 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 1-8 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Kolen, et al., US Patent Publication 10657934B1 (“Kolen”) in view of Simon, et al., “LEARNING A LATENT SPACE OF MULTITRACK MEASURES” (“Simon”).
Regarding claim 1, Kolen discloses:
An information processing method for generating music data, the method comprising: receiving user input specifying a directionality of alteration for extending original music data; (Kolen, col. 1 lines 56-62, “As will be described, a musical composition application [An information processing method for generating music data,] may advantageously recommend musical phrases or passages based on previously input musical notes. For example, the application may recommend minutes, or even hours, of a musical score [for extending original music data;]. Additionally, the musical composition application may adjust musical notes specified by a user according to different constraints [the method comprising: receiving user input specifying a directionality of alteration].”).
generating, by using the user input, a plurality of input music features derived from the original music data…, and a trained model, new extension music data obtained from the plurality of input music features having alterations determined based on the user input, (Kolen, col. 2-3, “Indeed, and as will be described, a composer may specify a certain theme or melody [generating, by using the user input,]. The musical composition application may then expound upon this specified theme or melody. For example, the musical score application may generate one or more measures for inclusion in the musical score. Advantageously, these generated measures may conform to a same musical style as being utilized by the composer. Thus, the musical score application may rapidly auto-complete a musical score being created by the composer [a plurality of input music features derived from the original music data…,…new extension music data obtained from the plurality of input music features having alterations determined based on the user input,].”, and Kolen, col. 4 lines 38-40, “the recommended musical phrase being determined based on one or more machine learning models [and a trained model]”).
wherein the alterations facilitate concatenation of musical elements corresponding to the plurality of input music features with musical continuity between the new extension music data and the original music data, (Kolen, col. 2-3, “Indeed, and as will be described, a composer may specify a certain theme or melody. The musical composition application may then expound upon this specified theme or melody. For example, the musical score application may generate one or more measures for inclusion in the musical score. Advantageously, these generated measures may conform to a same musical style as being utilized by the composer. Thus, the musical score application may rapidly auto-complete a musical score being created by the composer [wherein the alterations facilitate concatenation of musical elements corresponding to the plurality of input music features with musical continuity between the new extension music data and the original music data,].”).
and wherein, upon receiving the user input with respect to the original music data, the trained model is configured to output a plurality of output music features having the alterations; (Kolen, col. 6 lines 49-56, “An example recommendation may include recommended musical notes, for example to complete or expound upon musical notes specified by a user [and wherein, upon receiving the user input with respect to the original music data,]. For example, the system may recommend a particular musical phrase be included in the musical score. The musical phrase may represent a measure of music or may represent minutes or hours of music (e.g., generated via machine learning models) [the trained model is configured to output a plurality of output music features having the alterations;].”).
and displaying the generated new extension music data as an extension of the original music data. (Kolen, col. 4 lines 36-38, “The user interface: presents a recommended musical phrase for inclusion in the musical score [and displaying the generated new extension music data as an extension of the original music data.]”).
While Kolen teaches a music generation program that takes multiple user preferences to extend or modify a musical track, Kolen does not explicitly teach:
that are not in a concatenating relationship
Simon teaches that are not in a concatenating relationship (Simon, pg. 2 col. 2, “We model measures with up to 8 tracks (see Figure 1 for an example with 4 tracks). Each track consists of a single “instrument” as extracted by pretty midi[31]. A track is represented as a MIDI-like sequence of events from an extension of the vocabulary used by Simon and Oore [37] to handle metric timing and choice of instrument; using separate tracks for each instrument is interpreted as features not in a concatenating relationship as each track correlates to a different instrument and thus not in a concatenating relationship (i.e. that are not in a concatenating relationship)”).
Kolen and Simon are both in the same field of endeavor (i.e. music generation). It would have been obvious for a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Kolen and Simon to teach the above limitation(s). The motivation for doing so is that considering multiple instruments at once improves music creation by considering the harmony between the instruments (cf. Simon, pg. 2 col. 1, “Like our work, the system uses a latent space shared across tracks to handle interdependencies between instruments.”).
Regarding claim 2, Kolen in view of Simon teaches the information processing method according to claim 1. Kolen further teaches wherein the plurality of input music features includes features extracted from partial data having a data length shorter than a data length of the new extension music data. (Kolen, col. 13-14, “The musical phrase, as described herein, may represent a portion of music. For example, a particular measure of music may be generated. As another example, multiple measures may be generated. As another example, a new melody line may be generated. In this example, the user may confirm the new melody line and one or more musical phrases or portions [wherein the plurality of input music features includes features extracted from partial data having a data length shorter] may be generated based on the melody line [than a data length of the new extension music data.].”).
Regarding claim 3, Kolen in view of Simon teaches the information processing method according to claim 1. Kolen further teaches:
wherein each of the plurality of input music features is a feature extracted from partial data having a data length shorter than a data length of the new extension music data, (Kolen, col. 13-14, “The musical phrase, as described herein, may represent a portion of music. For example, a particular measure of music may be generated. As another example, multiple measures may be generated. As another example, a new melody line may be generated. In this example, the user may confirm the new melody line and one or more musical phrases or portions [wherein each of the plurality of input music features is a feature extracted from partial data having a data length shorter] may be generated based on the melody line [than a data length of the new extension music data.].”).
and wherein the new extension music data has the same data length as a total data length of each piece of partial data corresponding to each of the plurality of input music features. (Kolen, col. 13-14, “The musical phrase, as described herein, may represent a portion of music. For example, a particular measure of music may be generated. As another example, multiple measures may be generated. As another example, a new melody line may be generated. In this example, the user may confirm the new melody line and one or more musical phrases or portions may be generated based on the melody line; the melody line, or new extension music, is made up of the one or more generated musical phrases or portions (i.e. and wherein the new extension music data has the same data length as a total data length of each piece of partial data corresponding to each of the plurality of input music features.).”).
Regarding claim 4, Kolen in view of Simon teaches the information processing method according to claim 1. Simon further teaches:
further comprising: generating additional new extension music data obtained from the plurality of output music features having further alterations, (Simon, pg. 1, col. 2 and see Figure 3, “Apply attribute transformations to an existing measure, e.g. “increase note density” or “add strings” [further comprising: generating additional new extension music data obtained from the plurality of output music features having further alterations,].”).
the generation of the additional new extension music data performed using the plurality of output music features and iteratively using the trained model. (Simon, pg. 6 col. 2, “We have shown how to train and apply a latent space model over measures of symbolic music with multiple polyphonic instruments [performed using the plurality of output music features and iteratively using the trained model.]. We believe that ours is the first model capable of generating full multitrack polyphonic sequences [the generation of the additional new extension music data] with arbitrary instrumentation.”).
Kolen and Simon are both in the same field of endeavor (i.e. music generation). It would have been obvious for a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Kolen and Simon to teach the above limitation(s). The motivation for doing so is that modifications to measures allows for the ability to control and generate music with rich instrumentation (cf. Simon, abstract, “We demonstrate that our latent space model makes it possible to intuitively control and generate musical sequences with rich instrumentation”).
Regarding claim 5, Kolen in view of Simon teaches the information processing method according to claim 4. Simon further teaches:
further comprising: displaying the new extension music data and the additional new extension music data that have been generated (Simon, pg. 4 see Figure 2 below,
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Figure 2 displays two measures generated by the model and is interpreted as a new extension and the additional new extension (i.e. further comprising: displaying the new extension music data and the additional new extension music data that have been generated)).
and a number of times of alterations to generate each of the plurality of output music features by the iterative use of the trained model, in association with each other. (Simon, pg. 4 see Figure 3 below,
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“Figure 3. Multiple transformations to a single measure via attribute vector arithmetic. On the left is the original measure, followed by its reconstruction from the latent space. After that are three transformations: increasing the pitch range, using only string instruments, and using more tracks [and a number of times of alterations to generate each of the plurality of output music features by the iterative use of the trained model, in association with each other.]”).
Kolen and Simon are all in the same field of endeavor (i.e. music generation). It would have been obvious for a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Kolen and Simon to teach the above limitation(s). The motivation for doing so is that displaying the results of a combination or change can inform the user about the progress of a music track.
Regarding claim 6, Kolen in view of Simon teaches the information processing method according to claim 1. Kolen further teaches further comprising: generating the new extension music data by also using an additional feature determined with respect to the plurality of input music features. (Kolen, col. 8 lines 10-15, “As the user utilizes the music composition application, the system may recommend one or more musical phrases for inclusion in a musical score [further comprising: generating the new extension music data]. The recommended musical phrases may be based, at least in part, on the musical genre. For example, the system may utilize the determined constraints to generate a recommended musical phrase [by also using an additional feature determined with respect to the plurality of input music features.].”).
Regarding claim 7, Kolen in view of Simon teaches the information processing method according to claim 6. Kolen further teaches further comprising: displaying the new extension music data that has been generated and the directionality of an alteration given by the additional feature, in association with each other. (Kolen, see Figure 1D, Figure 1D shows the recommended generated musical phrase based on the genre and constraints given by the user, therefore the new extension music is displayed with the directionality of an alteration given by the additional feature, the genre (i.e. further comprising: displaying the new extension music data that has been generated and the directionality of an alteration given by the additional feature, in association with each other.)).
Regarding claim 8, Kolen in view of Simon teaches the information processing method according to claim 6. Kolen further teaches further comprising: displaying the additional feature corresponding to the new extension music data that has been generated. (Kolen, see Figure 1D, Figure 1D shows the recommended generated musical phrase based on the genre and constraints given by the user, therefore the additional feature, the genre, is displayed with the new extension music (i.e. further comprising: displaying the additional feature corresponding to the new extension music data that has been generated.)).
Regarding claim 11, the claim is similar to claim 1. Kolen teaches the additional limitations An information processing apparatus comprising: circuitry configured to (Kolen, col. 15 lines 6-9, “The musical adjustment and recommendation system 200 may be a system of one or more computers, one or more virtual machines executing on a system of one or more computers, and so on [An information processing apparatus comprising: circuitry configured to].”).
Regarding claim 12, the claim is similar to claim 1. Kolen teaches the additional limitations A non-transitory computer-readable storage medium having embodied thereon an information processing program, which when executed by a computer causes the computer to function execute a method for generating music data (Kolen, col. 4 lines 52-54, “Some aspects feature a computing system comprising one or more processors and non-transitory computer storage media storing instructions that when executed by the one or more processors [A non-transitory computer-readable storage medium having embodied thereon an information processing program, which when executed by a computer causes the computer to function execute a method for generating music data]”).
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Kolen, et al., US Patent Publication 10657934B1 (“Kolen”) in view of Simon, et al., “LEARNING A LATENT SPACE OF MULTITRACK MEASURES” (“Simon”) and further in view of Zhang, Non-Patent Literature “A Short Guide for Feature Engineering and Feature Selection” (“Zhang”).
Regarding claim 9, Kolen in view of Simon teaches the information processing method according to claim 1. The combination also teaches the original music data as seen in claim 1. While the combination teaches music generation using altered features, the combination does not explicitly teach wherein the plurality of input music features includes one or more features sampled from a standard normal distribution of the original music data.
(Zhang, pg. 13 see Table 3.1.2, “Method: Normalization – Standardization (Z-score scaling)…Definition: removes the mean and scales the data to unit variance. z = (X - X.mean)/ std…Pros: feature is rescaled to have a standard normal distribution that centered around 0 with SD of 1 [wherein the plurality of input music features includes one or more features sampled from a standard normal distribution of the original music data.]”).
Kolen, in view of Simon and Zhang are both in the same field of endeavor (i.e. machine learning). It would have been obvious for a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Kolen, in view of Simon, and Zhang to teach the above limitation(s). The motivation for doing so is that using a standard normal distribution feature scaling improves training of the model (cf. Zhang, pg. 13, “If range of inputs varies, in some algorithms, object functions will not work properly. Gradient descent converges much faster with feature scaling done. Gradient descent is a common optimization algorithm used in logistic regression, SVMs, neural networks etc.”).
Regarding claim 10, Kolen in view of Simon and Zhang teaches the information processing method according to claim 9. The combination also teaches the original music data as seen in claim 9. Kolen further teaches a feature extracted from partial data having a data length shorter than a data length of the new extension music data. (Kolen, col. 13-14, “The musical phrase, as described herein, may represent a portion of music. For example, a particular measure of music may be generated. As another example, multiple measures may be generated. As another example, a new melody line may be generated. In this example, the user may confirm the new melody line and one or more musical phrases or portions [a feature extracted from partial data having a data length shorter] may be generated based on the melody line [than a data length of the new extension music data.].”).
Zhang further teaches wherein a feature sampled from the standard normal distribution of the original music data is used instead of (Zhang, pg. 13 see Table 3.1.2, “Method: Normalization – Standardization (Z-score scaling)…Definition: removes the mean and scales the data to unit variance. z = (X - X.mean)/ std…Pros: feature is rescaled to have a standard normal distribution that centered around 0 with SD of 1 [wherein a feature sampled from the standard normal distribution of the original music data]” and Zhang, pg. 13, “If range of inputs varies, in some algorithms, object functions will not work properly. Gradient descent converges much faster with feature scaling done [is used instead of]. Gradient descent is a common optimization algorithm used in logistic regression, SVMs, neural networks etc.”).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the present application to combine the teachings of Zhang with the teachings of Kolen and Simon for the same reasons disclosed in claim 9.
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.
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/N.S.W./Examiner, Art Unit 2148
/MICHELLE T BECHTOLD/Supervisory Patent Examiner, Art Unit 2148