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 .
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 1-9, 11-15, 17 and 20-24 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.
Specifically, representative Claim 1 recites:
A signal processing device comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: convert an input signal into a predetermined signal that is a signal in a time-frequency domain estimate a peak of a time frequency intensity of the predetermined signal as an intensity of a target signal that is a signal related to occurrence of an event; estimate a band including at least a bandwidth that is from a frequency related to a peak to a predetermined frequency and does not include a frequency related to a peak different from the peak, as a noise band that is a frequency band of a noise signal; estimate an intensity of the noise signal based on a time-frequency intensity in the noise band; and determine whether an event has occurred based on a ratio between the intensity of the target signal to the intensity of the noise signal.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the 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 claim is considered to be in a statutory category (process).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “convert an input signal into a predetermined signal that is a signal in a time-frequency domain estimate a peak of a time frequency intensity of the predetermined signal as an intensity of a target signal that is a signal related to occurrence of an event; estimate a band including at least a bandwidth that is from a frequency related to a peak to a predetermined frequency and does not include a frequency related to a peak different from the peak, as a noise band that is a frequency band of a noise signal; estimate an intensity of the noise signal based on a time-frequency intensity in the noise band” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “determine whether an event has occurred based on a ratio between the intensity of the target signal to the intensity of the noise signal” are treated as belonging to mental process grouping.
Similar limitations comprise the abstract ideas of Claims 11 and 20.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
In Claim 1: a signal processing device, memory, one processor;
In Claim 20: a non-transitory computer-readable storage medium
The additional element in the preamble of “A signal processing device, memory, processor (generic processor) and non-transitory computer-readable storage medium are generally recited and are not qualified as particular machines.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2-9, 12-15, 17, 21-24 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
Allowable Subject Matter
Claims 1-9, 11-15, 17 and 20-24 would be allowable if written overcome the 101 rejection set forth in this office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 1, Suzuki teaches a signal processing device (abstract) comprising: at least one memory configured to store instructions [0022]; and at least one processor configured to execute the instructions [0021] to: convert an input signal into a predetermined signal that is a signal in a time-frequency domain [0024];
The reference, along with all other references fail to specifically teach (1) a target signal estimation means configured to estimate a peak of a time-frequency intensity of the predetermined signal as an intensity of a target signal that is a signal related to occurrence of an event; (2) estimate a band including at least a bandwidth that is from a frequency related to a peak to a predetermined frequency and does not include a frequency related to a peak different from the peak, as a noise band that is a frequency band of a noise signal; (3) estimate an intensity of the noise signal based on a time-frequency intensity in the noise band; and (4) determine whether an event has occurred based on a ratio between the intensity of the target signal to the intensity of the noise signal.
It is for this reason, Claim 1 and all of its dependencies would be allowed.
Claim 11 and 20 includes analogous, though not necessarily coextensive, features in conjunction with Claim 1, an is, therefore, along with its dependencies, for similar rationale as disclosed above, would be allowed.
Conclusion
The prior art made record and not relied upon is considered pertinent to applicant’s disclosure.
Suzuki et al. (Sound Processing Apparatus And Sound Processing Method, 2023-07-27) teaches a sound processing apparatus includes sound collection circuity that collects a sound and generates a first sound signal, and processing circuitry that estimates an estimated noise, controls a gain of the first sound signal and outputs a second sound signal based on the estimated noise, performs filter processing to reduce a component of a predetermined frequency band of the second sound signal based at least in part on the estimated noise;
Song et al. (Signal Extracting Method And Device Based On Noise Background, 2022-06-24) teaches a signal extraction method and device based on noise background, the method comprises: acquire sampling signal including a mixed noise signal and a target signal; performing reverse convolution treated the sampling signal based on the preset response function corresponding to at least one device noise signal so as to make at least one device noise signal; performing reverse suppression to the sampling signal based on at least one device noise signal acquire such that to be the target signal to be treated; dividing the target signal to be treated into at least two sub-frequency bands according to the preset time window, performing noise recognition on the sub-frequency band sequence higher than the preset energy threshold value and the sub-frequency band sequence respectively higher than the preset energy threshold value, and fusing the output target signal based on the time sequence, making the complete target signal. It solves the problem that it can not quickly classify recognition noises, so it can not eliminate these noises well;
Sugiyama et al. (SIGNAL PROCESSING APPARATUS, SIGNAL PROCESSING METHOD, AND SIGNAL PROCESSING PROGRAM, 2016-01-21) teaches a signal processing apparatus for effectively detecting an abrupt change in an input signal. The signal processing apparatus includes a converter that converts an input signal into a phase component signal and an amplitude component signal in a frequency domain. The signal processing apparatus further includes a calculator that calculates feature amounts of the phase component signal and the amplitude component signal derived by the converter. The signal processing apparatus further includes a determiner that determines presence probability of an abrupt change in the input signal based on the feature amounts calculated by the calculator;
Hetherington et al. (Method And Apparatus For Suppressing Wind Noise, 2004-08-26) teaches a method, apparatus, and computer program to selectively suppress wind noise while preserving narrow-band signals in acoustic data. Sound from one or several microphones is digitized into binary data. A time-frequency transform is applied to the data to produce a series of spectra. The spectra are analyzed to detect the presence of wind noise and narrow band signals. Wind noise is selectively suppressed while preserving the narrow band signals. The narrow band signal is interpolated through the times and frequencies when it is masked by the wind noise. A time series is then synthesized from the signal spectral estimate that can be listened to. This invention overcomes prior art limitations that require more than one microphone and an independent measurement of wind speed. Its application results in good-quality speech from data severely degraded by wind noise;
Roby et al. (Method And Apparatus For Indicating Activation Of A Smoke Detector Alarm, 2004-07-29) teaches A method for detecting smoke detector alarms comprises analyzing at least two parameters of ambient sound over a period of time to detect a temporal pattern of the alarm. In one embodiment, a series of samples are taken over a period of time sufficiently long to include at least one full period of a repeating sound pattern, and the two parameters are frequency and amplitude of the loudest sound in each sample. The algorithmic analysis may be triggered by a detection algorithm that utilizes a lower amount of power than the algorithmic analysis. In other embodiments, the detection apparatus is incorporated into a conventional smoke detector that will detect both smoke and an alarm from another detector. In another embodiment, a smoke detector includes a transceiver to transmit an activation signal to neighboring smoke detectors when a fire is detected and to receive an activation signal from neighboring detectors.
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/MICHAEL J SINGLETARY/Examiner, Art Unit 2863