DETAILED ACTION
This communication is in response to the Amendments/Response filed on 04/13/2026.
Applicant has elected Invention I: including claims 1-9.
Claims 10-33 have been canceled by the Applicant.
Claim(s) 34-45, which depend on claims 8-9, have been added by the Applicant.
Claims 1-9 and 34-45 of the instant application are pending and have been examined.
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 .
Election/Restrictions
Applicant’s election with traverse of Invention I, including claims 1-9, drawn to audio encoding method associated with coding quantized vectors (related to Figs. 2, 4, and 12), classified in G10L 19/20, G10L 19/035, and G10L 19/038, in the reply filed on 12/09/2025 is acknowledged.
The traversal is on the ground(s) that “there is no serious burden to examine claims 21- 32 along with claims 1-9. The pending claims recite encode-side and decode-side processes used in coding of audio according to vector codebooks. A proper search of the encode-side claims (group I above) likely will encompass a proper search for examination of the decode-side claims as well.” This is not found persuasive because Inventions I and II are directed to I: audio encoding associated with coding quantized vectors and II: decoding frames of audio data with reference to a codebook, respectively, as noted above. These inventions are distinct because:
These two inventions as noted above can have a materially different design, mode of operation, function, or effect since Invention I deals with audio encoding associated with coding quantized vectors, whereas Invention II relates to using decoding frames of audio data with reference to a codebook. As can be seen the mode of operation or effect is both different. Therefore, satisfying element (1) in determining distinctness.
As already noted, these two inventions do not overlap in scope and are mutually exclusive. Invention I is related to audio encoding associated with coding quantized vectors whereas Invention II is related to decoding frames of audio data with reference to a codebook which is not being claimed in Invention I. Therefore, satisfying element (2) in determining distinctness.
The requirement is still deemed proper and is therefore made FINAL.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/05/2024 and 09/12/2024 were filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 34-39 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 34-39 recites the limitation "the medium" in line 1 of each claim. There is insufficient antecedent basis for this limitation in the claim.
The claims should read: “the non-transitory computer readable memory of claim 9…”
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(s) 1-9 and 34-45 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. More specifically directed to the abstract idea grouping of: mathematical concept and/or mental process.
The independent claim(s) recite(s):
1. (Original) An audio encoding method, comprising:
parsing a sequence of audio samples contained within a frame of a predetermined size into a plurality of windows of smaller size,
transforming the audio samples in the windows into respective sets of frequency-domain coefficients,
developing a plurality of vectors, each vector containing frequency-domain coefficients selected from a plurality of the windows,
quantizing vectors of the plurality of vectors according to a vector codebook, and
coding the quantized vectors as an encoded audio signal.
8. (Original) A system for audio encoding, comprising:
a processor; and
a memory storing instructions, that when executed by the processor, cause the system to:
[perform the limitations as in claim 1, above.]
9. (Original) A non-transitory computer readable memory storing instructions for encoding audio that, when executed by a processor, cause the processor to:
[perform the limitations as in claim 1, above.]
This reads on a human (e.g., mentally and/or using pen and paper):
Using a predetermined set of rules to segment/divide an audio signal of a predetermined size (e.g., samples/data points) into a plurality of smaller-sized windows;
Using predetermined set of rules (e.g., Fourier transform – mathematical concept) to transform the audio signal and to obtain their respective frequency-domain coefficients;
Writing down a plurality of vectors containing the frequency-domain coefficients;
Using a predetermined set of rules (e.g., quantization – mathematical concept) on the vectors; and
Writing down the results as encoded audio signal.
This judicial exception is not integrated into a practical application because for example: claim 8 recites a system, a processor, and a memory storing instructions, while claim 9 recites a non-transitory computer readable memory storing instructions and a processor. As an example, in [0085] of the as filed specification, it is disclosed: The computer-readable storage medium can be any storage medium that can be read, written, or otherwise accessed by a general purpose or special purpose computing device, including any processing electronics and/or processing circuitry capable of executing instructions. Therefore, a general-purpose computer or computing device is described and mainly used as an application thereof. Accordingly, these additional elements do not integrate the abstract idea into a practical idea because it does not impose any meaningful limits on practicing the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of using a computer is listed as a general computing device as noted. The claim is not patent eligible.
With respect to claims 2, 40, and 34, the claim(s) recite:
2, 40, and 34. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, wherein the vectors are composed of a plurality of the frequency-domain coefficients corresponding to disjoint frequencies in one of the windows.
This reads on a human (e.g., mentally and/or using pen and paper):
Wherein the vectors obtained above comprise a plurality of frequency-domain coefficients including disjoint frequencies.
No additional limitations are present.
With respect to claims 3, 41, and 35, the claim(s) recite:
3, 41, and 35. (Previously Presented) The audio encoding method/system/medium of claims 1, 8, and 9, wherein the vectors are composed of plurality of the frequency-domain coefficients corresponding to a frequency in a plurality of the windows.
This reads on a human (e.g., mentally and/or using pen and paper):
Wherein the vectors obtained above comprise a plurality of frequency-domain coefficients including a frequency in the plurality of windows.
No additional limitations are present.
With respect to claims 4, 42, and 36, the claim(s) recite:
4, 42, and 36. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, further comprising:
scalar quantizing a first subset of the plurality of vectors;
wherein a second subset of the plurality of vectors different from the first subset are quantized according to the vector codebook.
This reads on a human (e.g., mentally and/or using pen and paper):
Using a predetermined set of rules (e.g., scalar quantization – mathematical concept) on the vectors; and
Wherein second subset of vectors is different from the first one and are quantized in accordance to predefined rules.
No additional limitations are present.
With respect to claims 5, 43, and 37, the claim(s) recite:
5, 43, and 37. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, further comprising:
estimating envelope parameter(s) for an envelope of frequency-domain coefficients across a plurality of the windows;
normalizing the frequency-domain coefficients of the plurality of windows based on the envelope parameters;
estimating residual structure parameter(s) for the normalized frequency-domain coefficients; and
removing residual structure from the normalized frequency-domain coefficients based on the residual structure parameter(s) to produce reduced-correlation coefficients;
wherein the quantizing is applied to vectors of the reduced-correlation coefficients.
This reads on a human (e.g., mentally and/or using pen and paper):
Estimating using a predetermined set of rules (i.e., mathematical concept) envelope parameters for the windows;
Normalizing using a predetermined set of rules (i.e., mathematical concept);
Estimating using residual structure parameters (i.e., mathematical concept);
Removing coefficients associated with residual structure parameters (i.e., mathematical concept) from the vectors to generate reduced-correlation coefficients;
Applying predetermined set of rules (e.g., quantization – mathematical concept) on the vectors of reduced-correlation coefficients.
No additional limitations are present.
With respect to claims 6, 44, 38, the claim(s) recite:
6, 44, and 38. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, wherein the quantizing includes selecting an index from the vector codebook for corresponding vectors based on a perceptual weighting of frequencies included in the corresponding vectors.
This reads on a human (e.g., mentally and/or using pen and paper):
Using predetermined set of rules to select index from predefined values (i.e., mental process) for vectors based on predetermined set of rules (i.e., mathematical concept – weighting of frequencies).
No additional limitations are present.
With respect to claims 7, 45, 39, the claim(s) recite:
7, 45, and 39. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, wherein the vector quantization is conjugate vector quantization, and the vector codebook is a conjugate vector codebook.
This reads on a human (e.g., mentally and/or using pen and paper):
Wherein the predetermined set of rules (e.g., quantization – mathematical concept) on the vectors involves conjugate vector quantization (i.e., mathematical concept) and conjugate predefined values (i.e., mathematical concept).
No additional limitations are present.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 8-9, 34-35, and 40-41 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koishida et al. (US 20080312759 A1) further in view of Kruger et al. (US 20080015852 A1).
As to independent claim 1, Koishida et al. teaches:
1. (Original) An audio encoding method (see Fig. 6 and ¶ [0015 and 0024]: “[0015] The following Detailed Description concerns various audio encoding/decoding techniques and tools… [0024] FIG. 6 is a data flow diagram of an audio encoding and decoding method that includes sparse spectral peak coding, and flexible frequency and time partitioning techniques.”), comprising:
parsing a sequence of audio samples contained within a frame of a predetermined size into a plurality of windows of smaller size (see ¶ [0015 and 0020]: “[0015] The following Detailed Description concerns various audio encoding/decoding techniques and tools that provide a way to fill spectral "holes" and missing high frequencies that may result from quantization at low bit rates, as well as flexibly combine coding at different transform window sizes along with vector quantization. [0020] The described techniques also include various ways to effectively combine vector quantization coding together with adaptively varying transform block sizes for tonal and transient sounds. With this approach, a traditional quantization coding using a first window size (i.e., transform block size) is applied to a portion of the spectrum, while vector quantization coding is applied to another portion of the spectrum. The vector quantization coding can use the same or a different (e.g., smaller) window (transform block) size to better preserve the time resolution of transients. In another variation, vector quantization coding using two different window sizes can be applied to a part of the spectrum. At the decoder, the separately coded parts of the spectrum are combined (e.g., summed) to produce the reconstructed audio signal.”),
transforming the audio samples in the windows into respective sets of frequency-domain coefficients (see ¶ [0049]: “The frequency transformer 210 receives the audio samples 205 and converts them into data in the frequency (or spectral) domain. For example, the frequency transformer 210 splits the audio samples 205 of frames into sub-frame blocks, which can have variable size to allow variable temporal resolution. Blocks can overlap to reduce perceptible discontinuities between blocks that could otherwise be introduced by later quantization. The frequency transformer 210 applies to blocks a time-varying Modulated Lapped Transform ("MLT"), modulated DCT ("MDCT"), some other variety of MLT or DCT, or some other type of modulated or non-modulated, overlapped or non-overlapped frequency transform, or uses sub-band or wavelet coding. The frequency transformer 210 outputs blocks of spectral coefficient data and outputs side information such as block sizes to the multiplexer ("MUX") 280.”),
developing a plurality of vectors, each vector containing frequency-domain coefficients selected from a plurality of the windows (see ¶ [0011 and 0016]: “[0011] In low bit rate coding, a recent trend is to exploit this wide-sense perceptual similarity and use a vector quantization (e.g., as a gain and shape code-vector) to represent the high frequency components with very few bits, e.g., 3 kbps. This can alleviate the distortion and unpleasant muffled effect from missing high frequencies. The transform coefficients of the "spectral holes" also are encoded using the vector quantization scheme. It has been shown that this approach enhances the audio quality with a small increase of bit rate. [0016] The described techniques include various ways of partitioning spectral holes and missing high frequencies into a band structure for coding using vector quantization (wide-sense perceptual similarity). In one described partitioning procedure applied to spectral holes (herein also referred to as the "hole-filling procedure"), a band structure is determined based on two threshold parameters: a minimum hole size threshold and a maximum band size threshold. In this procedure, the spectral coefficients produced by the block transform and quantization processes are searched for spectral holes whose width exceeds the minimum hole size threshold. Such holes are partitioned evenly into the fewest number of bands whose size does not exceed the maximum band size threshold. Thus, the number of bands required to fill the spectral holes can be controlled by these two threshold parameters. The vector quantization is then used to code shape vector(s) for the partitioned bands that are similar to the spectral coefficients that occupied the hole position prior to quantization (effectively, "filling the hole" in the spectrum).”),
quantizing vectors of the plurality of vectors (see ¶ [0054]: “The quantizer 250 quantizes the output of the weighter 240, producing quantized coefficient data to the entropy encoder 260 and side information including quantization step size to the MUX 280. In FIG. 2, the quantizer 250 is an adaptive, uniform, scalar quantizer. The quantizer 250 applies the same quantization step size to each spectral coefficient, but the quantization step size itself can change from one iteration of a quantization loop to the next to affect the bitrate of the entropy encoder 260 output. Other kinds of quantization are non-uniform, vector quantization, and/or non-adaptive quantization.”), and
coding the quantized vectors as an encoded audio signal (see ¶ [0058]: “The MUX 280 multiplexes the side information received from the other modules of the audio encoder 200 along with the entropy encoded data received from the entropy encoder 260. The MUX 280 can include a virtual buffer that stores the bitstream 295 to be output by the encoder 200.”).
However, Koishida et al. does not explicitly teach, but Kruger et al. does teach:
quantizing vectors of the plurality of vectors according to a vector codebook (see ¶ [0008]: “According to the present invention the above object is solved by a method for encoding audio data on the basis of linear prediction combined with vector quantisation based on a gain-shape vector codebook,”),
Koishida et al. and Kruger et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio encoding. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Koishida et al. to incorporate the teachings of Kruger et al. of quantizing vectors of the plurality of vectors according to a vector codebook which provides the benefit of improved performance for audio signals (abstract of Kruger et al.).
As to independent claim 8, Koishida et al. further teaches:
8. (Original) A system for audio encoding (see Fig. 6 and ¶ [0015 and 0024] citations as in claim 1, above and further ¶ [0035]: “…The memory 120 stores software 180 implementing one or more audio processing techniques and/or systems according to one or more of the described embodiments.”), comprising:
a processor (see further ¶ [0035]: “…The processing unit 110 executes computer-executable instructions and may be a real or a virtual processor. In a multi-processing system, multiple processing units execute computer-executable instructions to increase processing power. The processing unit also can comprise a central processing unit and co-processors, and/or dedicated or special purpose processing units (e.g., an audio processor). The memory 120 may be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g., ROM, EEPROM, flash memory), or some combination of the two. The memory 120 stores software 180 implementing one or more audio processing techniques and/or systems according to one or more of the described embodiments.”); and
a memory storing instructions, that when executed by the processor, cause the system (see further ¶ [0035]: “…The memory 120 may be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g., ROM, EEPROM, flash memory), or some combination of the two. The memory 120 stores software 180 implementing one or more audio processing techniques and/or systems according to one or more of the described embodiments.”) to:
[perform the limitations as in claim 1, above.]
As to independent claim 9, Koishida et al. further teaches:
9. (Original) A non-transitory computer readable memory storing instructions for encoding audio that, when executed by a processor, cause the processor (see ¶ [0035] citation as in claim 8, above and further ¶ [0040]: “Embodiments can be described in the general context of computer-readable media. Computer-readable media are any available media that can be accessed within a computing environment. By way of example, and not limitation, with the computing environment 100, computer-readable media include memory 120, storage 140, communication media, and combinations of any of the above.”) to:
[perform the limitations as in claim 1, above.]
Regarding claims 2, 40, and 34, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
Koishida et al. further teaches:
2, 40, and 34. (Original) The audio encoding method/system/medium of claims 1, 8, and 9,
wherein the vectors are composed of a plurality of the frequency-domain coefficients corresponding to disjoint frequencies in one of the windows (see Figs. 8 and 10 and ¶ [0020, 0026, 0073, 0095]: “[0020] The described techniques also include various ways to effectively combine vector quantization coding together with adaptively varying transform block sizes for tonal and transient sounds. With this approach, a traditional quantization coding using a first window size (i.e., transform block size) is applied to a portion of the spectrum, while vector quantization coding is applied to another portion of the spectrum. The vector quantization coding can use the same or a different (e.g., smaller) window (transform block) size to better preserve the time resolution of transients. In another variation, vector quantization coding using two different window sizes can be applied to a part of the spectrum. At the decoder, the separately coded parts of the spectrum are combined (e.g., summed) to produce the reconstructed audio signal. [0026] FIG. 8 is a flow diagram of a procedure for encoding using vector quantization with varying transform block ("window") sizes to adapt time resolution of transient versus tonal sounds. [0073] In FIG. 4, the tile configurer 422 partitions frames of multi-channel audio on a per-channel basis. The tile configurer 422 independently partitions each channel in the frame, if quality/bitrate allows. This allows, for example, the tile configurer 422 to isolate transients that appear in a particular channel with smaller windows, but use larger windows for frequency resolution or compression efficiency in other channels. This can improve compression efficiency by isolating transients on a per channel basis, but additional information specifying the partitions in individual channels is needed in many cases. Windows of the same size that are co-located in time may qualify for further redundancy reduction through multi-channel transformation. Thus, the tile configurer 422 groups windows of the same size that are co-located in time as a tile. [0095] FIG. 6 illustrates an extension of the above described transform-based, perceptual audio encoders/decoders of FIGS. 2-5 that further provides band partitioning for vector quantization of spectral holes and missing high frequency regions, as well as varying window size with vector quantization to improve time resolution when coding transients. As discussed in the Background above, the application of transform-based, perceptual audio encoding at low bit rates can produce transform coefficient data for encoding that may contain spectral holes and missing high frequency regions where quantization produces zero-value spectral coefficients. A band partitioning procedure described more fully below balances partitioning into bands for vector quantization between the spectral holes and high frequency region, so as to better preserve quality in the perceptually more significant high frequency region. A procedure to vary window size for vector quantization coding also is described below.”).
Regarding claims 3, 41, and 35, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
Koishida et al. further teaches:
3, 41, and 35. (Previously Presented) The audio encoding method/system/medium of claims 1, 8, and 9,
wherein the vectors are composed of plurality of the frequency-domain coefficients corresponding to a frequency in a plurality of the windows (see Figs. 8 and 10 and ¶ [0020, 0026, 0073, 0095] citations as in claims 2, 40, and 34, above and further ¶ [0055]: “[0055] The entropy encoder 260 losslessly compresses quantized coefficient data received from the quantizer 250, for example, performing run-level coding and vector variable length coding. The entropy encoder 260 can compute the number of bits spent encoding audio information and pass this information to the rate/quality controller 270.” and ¶ [0108]: “In the frequency extension procedure 730, the encoder 600 partitions the missing high frequency region into separate bands for vector quantization coding. As indicated at action 731, the encoder divides the frequency extension region (i.e., the spectral coefficients above the upper bound of the base band portion of the spectrum) into a desired number of bands. The bands can be structured such that successive bands are related by a ratio of their band size that is binary-increased, linearly-increased, or an arbitrary configuration.”).
Claims 4, 42, and 36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koishida et al. (US 20080312759 A1) further in view of Kruger et al. (US 20080015852 A1) as applied to claims 1 and 8-9 above, and further in view of Kim et al. (US 20170103766 A1).
Regarding claims 4, 42, and 36, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
Koishida et al. further teaches:
4, 42, and 36. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, further comprising:
scalar quantizing a first subset of the plurality of vectors (see ¶ [0054 and 0078]: “[0054] The quantizer 250 quantizes the output of the weighter 240, producing quantized coefficient data to the entropy encoder 260 and side information including quantization step size to the MUX 280. In FIG. 2, the quantizer 250 is an adaptive, uniform, scalar quantizer. [0078] The quantizer 460 quantizes the output of the multi-channel transformer 450, producing quantized coefficient data to the entropy encoder 470 and side information including quantization step sizes to the MUX 490. In FIG. 4, the quantizer 460 is an adaptive, uniform, scalar quantizer that computes a quantization factor per tile, but the quantizer 460 may instead perform some other kind of quantization.”);
However, Koishida et al. in combination with Kruger et al. do not explicitly teach, but Kim et al. does teach:
wherein a second subset of the plurality of vectors different from the first subset are quantized according to the vector codebook (see ¶ [0168]: “In at least some examples where quantization unit 500 applies vector quantization, quantization unit 500 is configured with a codebook that includes a set of entries. The codebook may be predefined or dynamically determined. The codebook may be based on a statistical analysis of spatial vectors. Each entry in the codebook indicates a point in the lower-dimension subspace. After transforming the spatial vector from the full dimension set to the reduced dimension set, quantization unit 500 may determine a codebook entry corresponding to the transformed spatial vector. Among the codebook entries in the codebook, the codebook entry corresponding to the transformed spatial vector specifies the point closest to the point specified by the transformed spatial vector. In one example, quantization unit 500 outputs the vector specified by the identified codebook entry as the quantized spatial vector. In another example, quantization unit 200 outputs a quantized spatial vector in the form of a code-vector index specifying an index of the codebook entry corresponding to the transformed spatial vector. For instance, if the codebook entry corresponding to the transformed spatial vector is the 8.sup.th entry in the codebook, the code-vector index may be equal to 8. In this example, audio decoding device 22 may inverse quantize the code-vector index by looking up the corresponding entry in the codebook. Audio decoding device 22D may determine an inverse quantized version of the spatial vector by assuming the components of the spatial vector that are in the full dimension set but not in the reduced dimension set are equal to zero.”).
Koishida et al., Kruger et al., and Kim et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio encoding. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Koishida et al. in combination with Kruger et al. to incorporate the teachings of Kim et al. of wherein a second subset of the plurality of vectors different from the first subset are quantized according to the vector codebook which provides the benefit of enabling conversion of the encoded audio data into coefficients ([0070] of Kim et al.).
Claims 5, 43, and 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koishida et al. (US 20080312759 A1) further in view of Kruger et al. (US 20080015852 A1) as applied to claims 1 and 8-9 above and further in view of Iwakami et al. (US 5684920 A).
Regarding claims 5, 43, and 37, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
However, Koishida et al. in combination with Kruger et al. do not explicitly teach, but Iwakami et al. does teach:
5, 43, and 37. (Original) The audio encoding method/system/medium of claims 1, 8, and 9, further comprising:
estimating envelope parameter(s) for an envelope of frequency-domain coefficients across a plurality of the windows (see ¶ Col. 4, lines 10-27: “(19) In general, the residual coefficients which are provided by normalizing the frequency-domain coefficients with the spectrum envelope thereof contain pitch components and appear as high-energy spikes relative to the overall power. Since the pitch components last for a relatively a long time, the spikes remain at the same positions over a plurality of frames; hence, the power of the residual coefficients has high inter-frame correlation. According to the present invention, since the redundancy of the residual coefficients is removed through utilization of the correlation between the amplitude or envelope of the residual coefficients of the past frame and the current one, that is, since the spikes are removed to produce the fine structure coefficients of an envelope flattened more than that of the residual coefficients, high efficiency quantization can be achieved. Furthermore, even if the input acoustic signal contains a plurality of pitch components, no problem will occur because the pitch components are separated in the frequency domain.” and ¶ Col. 5, lines 58-62: “(3) (a) The input signal is transformed into frequency-domain coefficients, then the spectrum envelope of the input signal is calculated and the frequency-domain coefficients are normalized or flattened with the spectrum envelope to obtain the residual coefficients.”);
normalizing the frequency-domain coefficients of the plurality of windows based on the envelope parameters (see ¶ Col. 4, lines 10-27 and ¶ Col. 5, lines 58-62 citations as in limitation above: ¶ Col. 5, lines 58-62: “(3) (a) The input signal is transformed into frequency-domain coefficients, then the spectrum envelope of the input signal is calculated and the frequency-domain coefficients are normalized or flattened with the spectrum envelope to obtain the residual coefficients.””);
estimating residual structure parameter(s) for the normalized frequency-domain coefficients (see ¶ Col. 4, lines 10-27 and ¶ Col. 5, lines 58-62 citations as in limitation above: “residual coefficients”); and
removing residual structure from the normalized frequency-domain coefficients based on the residual structure parameter(s) to produce reduced-correlation coefficients (see ¶ Col. 4, lines 10-27 and ¶ Col. 5, lines 58-62 citations as in limitation above: ¶ Col. 4, lines 10-27: “…According to the present invention, since the redundancy of the residual coefficients is removed through utilization of the correlation between the amplitude or envelope of the residual coefficients of the past frame and the current one, that is, since the spikes are removed to produce the fine structure coefficients of an envelope flattened more than that of the residual coefficients, high efficiency quantization can be achieved…”);
wherein the quantizing is applied to vectors of the reduced-correlation coefficients (see ¶ Col. 4, lines 10-27 and ¶ Col. 5, lines 58-62 citations as in limitation above: ¶ Col. 4, lines 10-27: “…According to the present invention, since the redundancy of the residual coefficients is removed through utilization of the correlation between the amplitude or envelope of the residual coefficients of the past frame and the current one, that is, since the spikes are removed to produce the fine structure coefficients of an envelope flattened more than that of the residual coefficients, high efficiency quantization can be achieved…”).
Koishida et al., Kruger et al., and Iwakami et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio encoding. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Koishida et al. in combination with Kruger et al. to incorporate the teachings of Iwakami et al. of estimating envelope parameter(s) for an envelope of frequency-domain coefficients across a plurality of the windows; normalizing the frequency-domain coefficients of the plurality of windows based on the envelope parameters; estimating residual structure parameter(s) for the normalized frequency-domain coefficients; and removing residual structure from the normalized frequency-domain coefficients based on the residual structure parameter(s) to produce reduced-correlation coefficients; wherein the quantizing is applied to vectors of the reduced-correlation coefficients which provides the benefit of achieving high efficiency quantization (Col. 4, lines 10-27 of Iwakami et al.).
Claims 6, 44, and 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koishida et al. (US 20080312759 A1) further in view of Kruger et al. (US 20080015852 A1) as applied to claims 1 and 8-9 above, and further in view of Ramo et al. (US 20250252963 A1).
Regarding claims 6, 44, 38, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
However, Koishida et al. in combination with Kruger et al. do not explicitly teach, but Ramo et al. does teach:
6, 44, and 38. (Original) The audio encoding method/system/medium of claims 1, 8, and 9,
wherein the quantizing includes selecting an index from the vector codebook for corresponding vectors based on a perceptual weighting of frequencies included in the corresponding vectors (see ¶ [0090 and 0097]: “[0090] Embodiments aim to address the above problem by using an approach whereby the dimension of the LSF vector is gradually increased during each quantization stage. The increase in vector dimension at each quantization stage allows for a change in the quantization “effort” to be applied on a perceptual basis. For instance, the first (or earlier) quantization stages can be arranged to quantize the lower indexed LSF coefficients (of the LSF vector) at a finer resolution than higher ordered indexed LSF coefficients. The change of quantization resolution at each quantization stage may be adapted to finely control the quantization distortion on a perceptual basis. For instance, a quantization stage may be adapted to the relative importance of the LSF coefficients associated at a particular dimension of the LSF vector coefficients at each stage. [0097] The first LSF vector quantization stage 501 is then arranged to quantize the first stage LSF sub vector 4003 by a M dimension first stage quantizer. This is depicted as the step 405 in FIG. 4. In embodiments the first stage quantizer can be a vector quantizer (VQ) arranged to quantize the M dimension first stage LSF sub vector by using a trained codebook. In other embodiments the first stage quantizer may comprise in itself be a multi-stage vector quantizer (MSVQ) where the residual output from a first VQ forms the input to a second VQ. In some embodiments it was found that a two stage MSVQ (as the first stage quantizer) was found to produce advantageous results. It is to be appreciated that this cascade approach of multiple VQ stages can be greater than two. However, the number of stages may be limited by the processing requirements for quantization and of the number of bits used for each stage. Returning to FIG. 4, the quantize first stage LSF sub vector is shown as 4004. One output from the first LSF vector quantization stage 501 may therefore be the codebook index/indices I.sub.1 for the quantized first stage LSF sub vector 4004. This is depicted in FIGS. 5 and 4 as the output 4100.”).
Koishida et al., Kruger et al., and Ramo et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio encoding. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Koishida et al. in combination with Kruger et al. to incorporate the teachings of Ramo et al. of wherein the quantizing includes selecting an index from the vector codebook for corresponding vectors based on a perceptual weighting of frequencies included in the corresponding vectors which provides the benefit of providing an efficient method in terms of the number of bits used for quantising line spectral coefficients ([0004] of Ramo et al.).
Claims 7, 45, and 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Koishida et al. (US 20080312759 A1) further in view of Kruger et al. (US 20080015852 A1) as applied to claims 1 and 8-9 above, and further in view of Pilli et al (US 20150371653 A1).
Regarding claims 7, 45, and 39, Koishida et al. in combination with Kruger et al. teaches the limitations as in claims 1, 8, and 9, above.
However, Koishida et al. in combination with Kruger et al. do not explicitly teach, but Pilli et al. does teach:
7, 45, and 39. (Original) The audio encoding method/system/medium of claims 1, 8, and 9,
wherein the vector quantization is conjugate vector quantization, and the vector codebook is a conjugate vector codebook (see ¶ [0080]: “Referring now to FIG. 14, an embodiment of a re-encoder of gains is provided. The G.729 encoder makes use of the PCM to encode the fixed and adaptive codebook gains, by using a conjugated-structure predictive vector quantizer. As in the CEVI algorithm the PCM is not available, an alternative algorithm was defined and implemented. This approach may be configured to amplify the original fixed codebook gain g(t), to produce a target fixed codebook gain ga(t), by using the amp_factor, ga(t)=amp_factor*g(t), and performs an exhaustive search in the conjugated-structure codebooks to match the new target fixed codebook gain. The encoder A may be a vector quantizer that contains a pair of adaptive/fixed codebook quantized values in each entry…”).
Koishida et al., Kruger et al., and Pilli et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio encoding. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Koishida et al. in combination with Kruger et al. to incorporate the teachings of Pilli et al. of wherein the vector quantization is conjugate vector quantization, and the vector codebook is a conjugate vector codebook which provides the benefit of providing audio speech intelligibility improvements ([0001] of Pilli et al.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Regarding frequency-domain and disjoint frequencies (pertinent to claims 2, 40, and 34):
Koishida et al. (US 20090006103 A1, ¶ [0231]).
Regarding estimating envelope parameters (pertinent to claims 5, 43, and 37):
Villemoes et al. (US 20180322886 A1, ¶ [0010])
Moriya et al. (US 5651090, ¶ col. 1, lines 23-41).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Keisha Y Castillo-Torres whose telephone number is (571)272-3975. The examiner can normally be reached Monday - Friday, 9:00 am - 4:00 pm (EST).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre-Louis Desir can be reached at (571)272-7799. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Keisha Y. Castillo-Torres
Examiner
Art Unit 2659
/Keisha Y. Castillo-Torres/Examiner, Art Unit 2659
Prosecution Insights