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 disclosure is objected to because of the following informalities:
Page 7 line 10 recites “properties:”, which should be “properties.”.
Page 7 lines 18-22 recite “For this purpose, particularly in connection with legal requirements, e.g., the indication of the sound level in dB(A), such as for the EU tire label for characterizing the sound volume of tires (in this case, the device would be only one tire, for example).”. This sentence is incomplete and must be revised.
Page 9 line 25 recites “comparison 204”, which should be “KPI 204”.
Page 11 line 25 recites “each decision tree 401”, which should be “each decision tree 401, 402, and 403”.
Page 13 line 18 recites “10”, which should be “410”.
Page 14 line 19 and Page 16 lines 13 and 19 recite “dependences”, which should “dependencies”.
Appropriate correction is required.
Claim Objections
Claims 1-2 and 5-7 are objected to because of the following informalities:
Claim 1 line 18, Claim 5 lines 4 and 8, Claim 6 line 18, and Claim 7 line 20 recite “dependences”, which should be “dependencies”.
Claim 2 line 5 recites “frequency amplitudes”, which should be “the frequency amplitudes”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7 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.
Claims 1 and 6-7 recite “a device feature” in Claim 1 line 12, Claim 6 line 12, and Claim 7 line 14 but recites “each device feature” in Claim 1 line 3, Claim 6 line 3, and Claim 7 line 5. It is unclear which device feature is “a device feature” or whether it is a new device feature outside of “each device feature”, rendering this limitation in the claims as indefinite.
Claims 1 and 6-7 recite “the device feature” in Claim 1 lines 14-15, Claim 6 line 14-15, and Claim 7 line 16-17 but recites “each device feature” in Claim 1 line 3, Claim 6 line 3, and Claim 7 line 5 and “a device feature” in Claim 1 line 12, Claim 6 line 12, and Claim 7 line 14. It is unclear which device feature is “the device feature” or whether it is a new device feature outside of “each device feature” or “a device feature”, rendering this limitation in the claims as indefinite.
Claims 1 and 6-7 recite “a device” in Claim 1 lines 16-17, Claim 6 lines 16-17, and Claim 7 lines 18-19 but recite “a device” in Claim 1 line 1, Claim 6 line 2, and Claim 7 line 2. It is unclear which device is “a device” in Claim 1 lines 16-17, Claim 6 lines 16-17, and Claim 7 lines 18-19 or whether it is a new device, rendering this limitation in the claims as indefinite.
Claims 1 and 6-7 recite “the device” in Claim 1 line 22, Claim 3 line 1, Claim 5 line 3, Claim 6 line 22, and Claim 7 line 24 but recites “a device” in Claim 1 line 1, Claim 6 line 2, and Claim 7 line 2 and “a device” in Claim 1 lines 16-17, Claim 6 lines 16-17, and Claim 7 lines 18-19. It is unclear which device is “the device”, rendering this limitation in the claims as indefinite.
Claim 4 line 3 recites “an associated value”, but Claim 1 line 9 recites “an associated value”. It is unclear if the “associated value” recited in Claim 4 is a separate one from the “associated value” recited in Claim 1, rendering this limitation in the claim as indefinite.
Claims that depend on the above rejected claims are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
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 1-10 and 16-21 are rejected under 35 U.S.C. 101. The claimed invention is directed to the abstract concept of performing mental steps without significantly more. The claim(s) recite(s) the following abstract concepts in BOLD of
With regards to Claim 1,
a method for adjusting a noise generated by a device, comprising the following steps:
ascertaining, for each device feature of a plurality of device features, a dependence of a contribution of the device feature to a noise evaluation characteristic number on a value of the device feature by training an explainable boosting machine with a plurality of combinations of values for the device features and, for each of the combinations, an associated value of the noise evaluation characteristic number, wherein each of a plurality of decision trees of the explainable boosting machine ascertains, depending on the value of a device feature assigned to the decision tree, a contribution to the noise evaluation characteristic number for the device that has the value for the device feature;
ascertaining values of the device features for a device of which the noise is to be adjusted;
ascertaining, from the dependences ascertained for the device features, changes, for one or more of the device features, to the values of the device features for improving the noise evaluation characteristic number; and
adjusting the device of which the noise is to be adjusted, according to the ascertained changes.
With regards to Claim 6,
a production system configured to adjusting a noise generated by a device, the production system configured to:
ascertain, for each device feature of a plurality of device features, a dependence of a contribution of the device feature to a noise evaluation characteristic number on a value of the device feature by training an explainable boosting machine with a plurality of combinations of values for the device features and, for each of the combinations, an associated value of the noise evaluation characteristic number, wherein each of a plurality of decision trees of the explainable boosting machine ascertains, depending on the value of a device feature assigned to the decision tree, a contribution to the noise evaluation characteristic number for the device that has the value for the device feature;
ascertain values of the device features for a device of which the noise is to be adjusted;
ascertain, from the dependences ascertained for the device features, changes, for one or more of the device features, to the values of the device features for improving the noise evaluation characteristic number; and
adjust the device of which the noise is to be adjusted, according to the ascertained changes.
With regards to Claim 7,
non-transitory computer-readable medium on which is stored instructions for adjusting a noise generated by a device, the instructions, when executed by a processor, causing the processor to perform the following steps:
ascertaining, for each device feature of a plurality of device features, a dependence of a contribution of the device feature to a noise evaluation characteristic number on a value of the device feature by training an explainable boosting machine with a plurality of combinations of values for the device features and, for each of the combinations, an associated value of the noise evaluation characteristic number, wherein each of a plurality of decision trees of the explainable boosting machine ascertains, depending on the value of a device feature assigned to the decision tree, a contribution to the noise evaluation characteristic number for the device that has the value for the device feature;
ascertaining values of the device features for a device of which the noise is to be adjusted;
ascertaining, from the dependences ascertained for the device features, changes, for one or more of the device features, to the values of the device features for improving the noise evaluation characteristic number; and
adjusting the device of which the noise is to be adjusted, according to the ascertained changes.
Under step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category of a process.
Under Step 2A, Prong One, we consider whether the claims recite a judicial exception (abstract idea). In the above claim, the highlighted portions constitute an abstract idea because, under a broadest reasonable interpretation, they recite limitations that fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, they fall into the grouping of subject matter that, when recited as such in a claim limitation, cover performing mathematics or mental steps, see MPEP 2106.04(a)(2). Additionally, the claim limitations merely indicate a field of use or technological environment in which the judicial exception is performed, which is the field of adjusting noise generated by a device.
Next, under Step 2A, Prong Two, we consider whether the claims that recite a judicial exception are integrated into a practical application. In this step, we evaluate whether the claims recite additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that even though the claimed methods are tied to a particular machine or apparatus (i.e. a device), it does not represent an improvement to another technology or technical field as the device was already produced before the mental steps explained in Step 2A Prong 1. Similarly, there are no other meaningful limitations linking the use to a particular technological environment. Finally, there is nothing in the claim that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Finally, under Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because every step in BOLD of Claims 1, 6, and 7 point to a mental or mathematical step. In addition, in Claims 1, 6, and 7 the step of adjusting the device of which the noise is to be adjusted, according to the ascertained changes, amounts to nothing more than extra solution activity not tied to a particular technology or device as it is an insignificant application, see MPEP 2106.05(g). See In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because a production system configured to adjusting a noise generated by a device and a non-transitory computer-readable medium on which is stored instructions for adjusting a noise generated by a device are generic computer elements and not considered significantly more than the abstract idea. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
Claims 2 and 4-5 are rejected under 35 U.S.C. 101 as they are further directed to abstract ideas.
Claim 3 incorporates the abstract idea into a practical application, and is not rejected under 35 U.S.C 101.
Closest Prior Art of Record
Sun (US 20190163274 A1) discloses a system for processing and modulating the audio signals of a peripheral device, wherein the audio input from the peripheral device is used to generate an audio score (See Abstract) which is used by machine learning (such as decision trees, see para[0100] “A classification algorithm may be based on supervised machine learning techniques such-as SVM, Decision Tree”) to reduce latency between input and haptic output (See Para[0020] “the system may dynamically learn the haptic-commanding events in a user's surrounding and create reference parameters in order to create shortcuts in the input processing. Such shortcuts may cut down on latency between input and haptic output, providing for a substantially more real-time experience”). The audio score is consequently used to modulate the peripheral device (See Abstract).
Sun does not disclose that the individual frequency amplitudes of the peripheral device contribute to an individual score (like a KPI). It rather discloses that the change of frequency is used to generate a coefficient (See Para[0121]“calculating a coefficient related to broad and narrow changes in a frequency spectrum”). Sun also does not disclose an Explainable Boosting Machine consisting of a series of decision trees.
Knott (US 20180300651 A1) discloses a method to input audio signals into a machine learning method to generate a series of haptic cues in order to activate a series of actuators to apply a set of haptic outputs (See Abstract). Knott also discloses that the machine learning method can be an Explainable Boosting Machine (See Para[0175] “Different machine learning techniques such as linear support vector machine (linear SVM), boosting for other algorithms (e.g., AdaBoost), neural networks, logistic regression, naïve Bayes, memory-based learning, random forests, bagged trees, decision trees, boosted trees”). Knott also discloses a method to generate a score based on device features (See Para[0130] “The machine learning circuit 242 may further determine a score for the generated haptic illusion signals 202 based on the extracted features.”).
Knott does not disclose that the individual frequency amplitudes of the audio input is used to generate the score from the machine learning. Knott also does not disclose that the output of the machine learning model is used to reduce the noise of a device, even though it does teach a noise filter that reduces noise (See Fig. 10, the noise filter 1004).
Pinel (US 20200314458 A1) discloses a method for event detection via audio and visual input data. The audio data is used to generate a first audio parameter value that is indicative of the one or more frequencies/amplitudes of the audio data input(See Para[0035] “The first audio parameter value indicates one or more frequencies of a sound, one or more amplitudes of the sound, one or more durations of the sound, modulation of the sound, or a combination thereof.”). The audio data is combined with sonification audio data (which reflects the positions of two objects) as input to a trained event classifier for event detection (See Abstract).
Pinel does not disclose that the first audio parameter value is an output of the machine learning method as disclosed in the instant application. Pinel also does not disclose that the classifier is used to determine the individual contributions of the frequencies/amplitudes of the input audio signal to the first parameter value. In addition, the method of Pinel does not disclose the action of adjusting a noise of a device after processing the audio signal via machine learning.
The combination of Sun, Knott, and Pinel fails to teach that the explainable boosting machine determines a contribution of each frequency/amplitude of the input audio signal to a score or value. The combination further fails to disclose a method to change the frequencies of the input audio signal to improve the score or value (recited as “the noise evaluation characteristic number” in the instant application).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOSTOFA AHMED HISHAM whose telephone number is (571)272-8773. The examiner can normally be reached Monday - Friday, 7:00 a.m. - 4 p.m. ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at (571) 270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOSTOFA AHMED HISHAM/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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