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 .
Information Disclosure Statement
The information disclosure statement(s)(IDS) submitted on 1/7/25, 4/3/25 has been considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-3, 10,11, 15 24-26 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Taghipour (Taghipour, Armin, (2016): Psychoacoustics of detection of tonality and asymmetry of masking: implementation of tonality estimation methods in a psychoacoustic model for perceptual audio coding, PhD Thesis, Friedrich-Alexander Universität Erlangen-Nürnberg.
With respect to claim 1, Taghipour teaches wherein the masking threshold determinator is configured to acquire a plurality of bandpass signals using a plurality of filters comprising different bandwidths (Taghipour ¶Figure 5.4: PM with the initial PSFM. [masking with given freq information] Only one output channel of the filter [bandpass] bank is shown. 104 DFTs are applied to the outputs of the 104 filters. Spectral resolution of PSFM calculation varies with the DFT length; it is higher for low frequencies. Four different DFT lengths are used); and
wherein the masking threshold determinator is configured to acquire a masking threshold information associated with a given frequency region on the basis of bandpass signal values of at least two ones of the bandpass signals (Taghipour ¶Figure 5.4: PM with the initial PSFM. [masking with given freq information] Only one output channel of the filter [bandpass] bank is shown. 104 DFTs are applied to the outputs of the 104 filters. Spectral resolution of PSFM calculation varies with the DFT length; it is higher for low frequencies. Four different DFT lengths are used.)
With respect to claim 2, Taghipour teaches wherein the bandpass signal values are complex values (Taghipour ¶Section 4.3.1 Last Para: Minimum-phase filters were generated for both the real-valued and the complex-valued versions [complex-valued] of the filter bank. The real-valued filter design was done with pairs of conjugate poles and zeros. The complex-valued filters were represented by individual poles and zeros.);
wherein the masking threshold determinator is configured to take phases of the bandpass signal values into account when acquiring the masking threshold information associated with the given frequency region on the basis of the bandpass signal values of the at least two ones of the bandpass signals(Taghipour ¶Section 4.3.1 Last Para: Minimum-phase filters were generated for both the real-valued and the complex-valued versions [complex-valued] of the filter bank. The real-valued filter design was done with pairs of conjugate poles and zeros. The complex-valued filters were represented by individual poles and zeros.)
With respect to claim 10 Taghipour teaches wherein the masking threshold determinator is configured to acquire a masking threshold information associated with a given frequency region on the basis of magnitudes of the bandpass signal values of the at least two ones of the bandpass signals (Taghipour ¶p78 Caption Figure 5.10: Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output channel of the filter bank is shown. AM-R is calculated from the short-time magnitude [magnitude] spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256).)
With respect to claim 11 Taghipour teaches wherein the masking threshold determinator is configured to combine bandpass signal values of different ones of the bandpass signals in order to acquire the masking threshold information (Taghipour ¶p78 Caption Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output [Eq. 5.6 page 79 also shows sums all the magnitudes for scaling ] channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256, ¶p79 description of Eq. 5.6: where A[k] is the k-th element of the current amplitude modulation spectrum. A[0] represents the average envelope, for 1 k l 2 , and A[k] represents the variations around this average. Only a restricted spectral region is used for this formula, since modulation frequencies much higher than the bandwidth of a filter can only be caused by components located in other bands); and
wherein the masking threshold determinator is configured to acquire the masking threshold information associated with the given frequency region using a weighted combination of bandpass signal values, or non-linearly processed versions of the bandpass signal values, associated with a plurality of frequency regions (Taghipour ¶p78 Caption Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output [Eq. 5.6 page 79 also shows sums all the magnitudes for scaling ] channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256, ¶p79 description of Eq. 5.6: where A[k] is the k-th element of the current amplitude modulation spectrum. A[0] represents the average envelope, for 1 k l 2 , and A[k] represents the variations around this average. Only a restricted spectral region is used for this formula, since modulation frequencies much higher than the bandwidth of a filter can only be caused by components located in other bands.)
With respect to claim 15, Taghipour teaches wherein (Taghipour ¶4.3.2 Modeling of forward masking Due to the forward masking, the masking thresholds of a frame are relevant for the thresholds of the following frames. In the presented PM, this is modeled with a decaying exponential function. The computation of the exponential decay is carried out in the form of a \resistor{capacitor circuit," which is shown in Figure 4.6.)
With respect to claim 24 Taghipour teaches wherein center frequencies of the filters of ERB or Bark, and/or wherein the filters of the filterbank comprise 3dB bandwidths which are smaller than a third of [[a]] an ERB or Bark (Taghipour ¶4.3.1 The filter bank The filters were designed based on the theory of the auditory filters in the inner ear (Fletcher, 1940). The design of the initial filter bank was based on the Bark scale (Fastl and Zwicker, 2007), similar to the subbands in most conventional codecs. For an alternative version of the filter bank based on the ERBN (Moore, 2012), see Section 4.4. The center frequencies of neighboring filters are spaced 1 4 Bark apart from each other. Figure 4.5 illustrates the construction of the desired frequency responses (Taghipour et al., 2010). The bandpass filters, which take into account the spreading in simultaneous masking, were designed from reversed masking curves (Bosi, 2003; Fastl and Zwicker, 2007). The slope of the magnitude frequency response of a filter was chosen to be 20 dB/Bark towards the low frequencies and -27 dB/Bark towards the high frequencies. For a sampling rate of 48 kHz and with a Bark-based design, the filter bank consisted of a total of 104 filters.)
With respect to claim 25, Taghipour teaches wherein the filters of a filterbank are chosen to comprise an asymmetric transfer function, and/or wherein the filterbank is an All-Pole-Gammatone filterbank, and/or wherein the filterbank is a complex-valued All-Pole-Gammatone filterbank(Taghipour ¶Figure 4.5: Construction of the desired frequency response for a filter with center frequency fthr (Taghipour et al., 2010). Left: influence of maskers at different frequencies on the threshold at fthr. Right: magnitude response of the filter. The abscissa shows the frequencies on a Bark scale.).
With respect to claim 26 Taghipour teaches wherein for the given frequency region, an attenuation of a filter of ERB or Bark above and/or 1 ERB or Bark below its center frequency is at least 40 dB. (Taghipour ¶4.3.1 The filter bank The filters were designed based on the theory of the auditory filters in the inner ear (Fletcher, 1940). The design of the initial filter bank was based on the Bark scale (Fastl and Zwicker, 2007), similar to the subbands in most conventional codecs. For an alternative version of the filter bank based on the ERBN (Moore, 2012), see Section 4.4. The center frequencies of neighboring filters are spaced 1 4 Bark apart from each other. Figure 4.5 illustrates the construction of the desired frequency responses (Taghipour et al., 2010). The bandpass filters, which take into account the spreading in simultaneous masking, were designed from reversed masking curves (Bosi, 2003; Fastl and Zwicker, 2007). The slope of the magnitude frequency response of a filter was chosen to be 20 dB/Bark towards the low frequencies and -27 dB/Bark towards the high frequencies. For a sampling rate of 48 kHz and with a Bark-based design, the filter bank consisted of a total of 104 filters.) They do not specifically 40dB. It would be obvious to one of ordinary skill in the art at the time of the invention to do 40dB to achieve better attenuation in compatible ways and is a matter of design choice.
With respect to claim 38 Taghipour teaches A method for determining masking threshold information, comprising acquiring a plurality of bandpass signals using a plurality of filters comprising different bandwidths, and acquiring the masking threshold information associated with a given frequency region on the basis of bandpass signal values of at least two ones of the bandpass signals (Taghipour ¶Figure 5.4: PM with the initial PSFM. [masking with given freq information] Only one output channel of the filter [bandpass] bank is shown. 104 DFTs are applied to the outputs of the 104 filters. Spectral resolution of PSFM calculation varies with the DFT length; it is higher for low frequencies. Four different DFT lengths are used).
With respect to claim 39 Taghipour teaches A non-transitory digital storage medium having a computer program stored thereon (Sec. 4.1.2 The experimental coding setup For the studies in Chapter 5, an MDCT-based transform audio coding scheme was chosen. For the experimental coding setup, a _xed input frame length of 1024 samples was used, which is equivalent to an MDCT window length of 2048 samples. Different variants of a PM, which will be described in Section 4.3, were applied for quantizer control. Although entropy coding was not applied, entropy3 rates were estimated. The different versions were controlled to have a desired average data rate, estimated for a large set of standard test audio signals with varying characteristics. This was possible by applying a scaling factor to the calculated masking thresholds. For the quality assessment tests, scaling factors were determined which resulted in equal average entropy rates of 48 kbit/s (medium quality) and/or 32 kbit/s (low quality)),comprising acquiring a plurality of bandpass signals using a plurality of filters comprising different bandwidths, and acquire the masking threshold information associated with a given frequency region on the basis of bandpass signal values of at least two ones of the bandpass signals, when said computer program is run by a computer (Taghipour ¶Figure 5.4: PM with the initial PSFM. [masking with given freq information] Only one output channel of the filter [bandpass] bank is shown. 104 DFTs are applied to the outputs of the 104 filters. Spectral resolution of PSFM calculation varies with the DFT length; it is higher for low frequencies. Four different DFT lengths are used).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3 is(are) rejected under 35 U.S.C. 103 as being unpatentable over Taghipour in further view of Kim (US 20130058498 A1)
With respect to claim 3, Taghipour does not explicitly disclose however Kim teaches Hartung teaches wherein the masking threshold determinator is configured to perform an averaging of the masking threshold information in a non-linear domain (Kim ¶[0050] The average value of the masking thresholds of the sub-bands included in the low band is obtained by averaging the masking thresholds of the sub-bands included in the low band among the masking thresholds obtained by the psychoacoustic model unit 220.)
It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify the audio system of Taghipour to include the averaging of Chen in order to increase perceptual accuracy.
Allowable Subject Matter
Claims 4 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 4 recites The masking threshold determinator according to claim 3, wherein the phase correction value describes a phase difference between transfer functions of filters comprising adjacent passbands at a . The closest teaching comes from Disch who teaches (Disch ¶[0049] Furthermore, in a special implementation of the above situation, one observes that a phase correction, which is independent the transposition order T, could be incorporated in the analysis filter bank step itself. Since a correction [phase correction] prior to the vocoder phase multiplication corresponds to T times the same correction after phase multiplication, the following decomposition occurs as advantageous)
However, none of the prior art of record including Disch and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 4, is allowable.
Claim 5 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 5 recites wherein between a first passband of a first filter and an adjacent second passband of a second filter there is a crossing frequency, wherein a phase correction value between the first filter and the second filter is a combination of a first phase shift between a pole of the first passband and the crossing frequency and of a second phase shift between a pole of the second passband and the crossing frequency. The closest teaching comes from Disch who teaches (Disch ¶[0049] Furthermore, in a special implementation of the above situation, one observes that a phase correction, which is independent the transposition order T, could be incorporated in the analysis filter bank step itself. Since a correction [phase correction] prior to the vocoder phase multiplication corresponds to T times the same correction after phase multiplication, the following decomposition occurs as advantageous).However, none of the prior art of record including Disch and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 5, is allowable.
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 9 recites wherein the masking threshold determinator is configured to a apply a non-linear mapping to respective magnitudes of complex values of the bandpass signals while keeping respective phase values of the complex values unchanged except for an optional phase correction. The closest teaching comes from the cited art Taghipour who teaches (Taghipour ¶Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256).). However, none of the prior art of record including Taghipour and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 9, is allowable.
Claims 13-14 are objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 13 recites wherein the masking threshold determinator is configured to perform a weighting of bandpass signal values, or of non-linearly processed versions of the bandpass signal values that decreases with increasing difference between a center frequency of the given frequency region and center frequencies of one or more other frequency regions. The closest teaching comes from (Taghipour ¶Figure 5.4: PM with the initial PSFM. Only one output channel of the filter bank is shown.104 DFTs are applied to the outputs of the 104 filters. Spectral resolution of PSFM calculation varies with the DFT length; it is higher for low frequencies. Four different DFT lengths are used.) However, none of the prior art of record including Taghipour and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 13, is allowable and claim 14 is allowable because of dependency.
Claims 17 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 17 recites wherein the masking threshold determinator is configured to acquire the masking threshold information based on a spreading output, which is determined using the equation Ynl,b =EXnl,b+EXnl,klnl,k,bVb,0<b< B - 1 k 1 wherein yni,b designates a spreading output associated with a frequency band comprising band index b, wherein xni,k designates a non-linearly processed version of a bandpass signal value or a non-linearly processed version of a magnitude value of a bandpass signal value of a frequency band comprising band index k, wherein a designates a non-linear exponent value a; wherein k designates a running variable, wherein uni,k,b designates an upper spreading factor depending on the running variable k and the band index b, wherein lni,k,b designates [[an]] a lower spreading factor depending on the running variable k and the band index b, and wherein B designates a number of frequency bands; wherein at least one of the upper spreading factor uni.kb and the lower spreading factor lni.eb is dependent on a difference between the running variable k and the band index b; and wherein at least one of the upper spreading factor uni. b and the lower spreading factor lni.eb reduces exponentially with increasing difference between the running variable k and the band index b. The closest teaching comes from (Taghipour ¶Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256).). However, none of the prior art of record including Taghipour and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 13, is allowable and claim 14 is allowable because of dependency.
Claims 32 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 32 recites wherein the masking threshold determinator is configured to [[a]] apply a non-linear mapping to respective magnitudes of complex values of the bandpass The closest teaching comes from the cited art Taghipour who teaches (Taghipour ¶Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256).). However, none of the prior art of record including Taghipour and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 32, is allowable.
Claims 33 is objected to as being dependent upon a rejected base claim, but would be allowable if written in independent form including all of the limitations of the base claim and any intervening claims. Claim 33 recites wherein the masking threshold determinator is configured to perform an additional processing, e.g. for considering postmasking, in a non-linear domain wherein the masking threshold determinator is configured to apply anon-linear mapping to respective magnitudes of complex values of the bandpass signals while keeping respective phase values of the complex values unchanged except for an optional phase correction; and wherein the masking threshold determinator is configured to perform an additional processing of the non-linearly mapped magnitudes of the complex values of the bandpass signals in order to consider postmasking. The closest teaching comes from the cited art Taghipour who teaches (Taghipour ¶Figure 5.10: Block diagram of the AM-R tonality estimation method. Only one output channel of the filter bank is shown. AM-R is calculated from the short-time magnitude spectral coefficients of the squared envelope of the filter output. Different DFT lengths are used for the analysis of the filter outputs at low, middle and high frequencies (4096, 2048, 1024, 512 and 256).).
Chen (Chen, H., Taghipour, A., and Edler, B. (2014). Comparison of two tonality estimation methods used in a psychoacoustic model. 4th IEEE Int. Conf. Audio Lang. Image Process. (ICALIP), Shanghai, China. pp. 706-710.) further teaches ( Fig. 3. Block diagram of PSFM tonality estimation method and calculation of masking thresholds in the psychoacoustic model. Varying DFT lengths are shown for analysis of the input signal at low, middle and high frequencies (4096, 2048 and 1024, respectively). From the individual masking thresholds of 104 bands, a global masking threshold is calculated for a short frame.)
However, none of the prior art of record including Taghipour and Chen and other cited references searched teach the limitations as a whole included in the applicant’s claim specifically as noted/underlined earlier, and all supporting limitations thereof. Therefore, claim 33 is allowable.
Conclusion
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/ATHAR N PASHA/Primary Examiner, Art Unit 2657
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