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.
Claim 25 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because it is directed to a program claim per se.
Examiner’s Note
Examiner has cited particular columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to
fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-9, 11, 13-21, 23 and 25 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Dieleman (US 2024/0144944).
As to claim 1, Dieleman teaches a method Figs.1-2 for processing an input audio signal, comprising: conditioning a first processing stage comprising a first neural network system 210 with a representation of the input audio signal to generate a latent signal comprising a prediction of a bit-rate reduced representation of a processed version of the input audio signal, said first neural network system being trained to generate a bit-rate reduced representation of a target processed version of a given audio signal, wherein said bit-rate reduced representation has a format associated with a pre-defined audio codec quantized to a desired bit-rate (Pars.50-51; Figs.3-5), conditioning a second processing stage comprising a second neural network system 220 with said latent signal to predict said processed version of the input audio signal, said second neural network system being trained to generate an enhanced representation of a given bit-rate reduced audio representation of a processed version of an audio signal, wherein said bit-rate reduced representation has a format associated with said pre-defined audio codec (Pars.52-57, and transforming said predicted processed version of the input audio signal into an output audio signal 112(Pars.70, 82, 95-116)
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As to claim 2, Dieleman teaches wherein the input audio signal and the output audio signal are in time domain (Fig.1; Pars.4-5)
As to claim 3, Dieleman teaches wherein said enhanced representation has a format associated with said pre-defined audio encoding process (Pars.7-8, 51-54; Figs.1-5).
As to claim 4, Dieleman teaches wherein the representation of the input signal, the bit-rate reduced representation, and the enhanced representation, are all in a same transform domain (Figs.1-2).
As to claim 5, Dieleman teaches wherein the transform domain is a waveform transform domain (Figs.1-2; Pars.20-25)..
As to claim 6, Dieleman teaches wherein the representation of the input signal, the bit-rate reduced representation, and the enhanced representation all include a set of MDCT lines (quantized values/levels) and associated envelope/amplitude information (Fig.4, #410-430; Pars.4, 21).
As to claim 7, Dieleman teaches wherein the MDCT lines have reduced signal dynamics (Pars.81-90).
As to claim 8, Dieleman teaches, wherein the step of transforming includes increasing signal dynamics of the enhanced representation (Fig.4, Pars.81-94).
As to claim 9, Dieleman teaches wherein the first neural network system or the second neural network system is trained and operates in a generative setting (Figs.1-3).
As to claim 11, Dieleman wherein said input audio signal is a distorted audio signal, and said first neural network system predicts a bit-rate reduced representation of a signal enhanced version of the input audio signal or wherein said input audio signal is a mixture audio signal, and said first neural network system predicts a bit-rate reduced representation of a source-separated version of the input audio signal (Figs.1-4; Pars.24-25).
Regarding claims 13-21, 23 and 25, the corresponding computer program and system comprising the steps similar to the claims above are analogous therefore rejected as being anticipated by Dieleman for the foregoing reasons.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL DEMELASH ABEBE whose telephone number is (571)272-7615. The examiner can normally be reached monday-friday 7-4.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Daniel Washburn can be reached at 571-272-5551. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL ABEBE/Primary Examiner, Art Unit 2657
