DETAILED ACTION
Claims 1-20 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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/30/2024 was 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 1-20 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, 9, and 17 recite the limitation "the fused structured noise" in line 7 of claim 1, line 11 of claim 9, and line 10 of claim 17. There is insufficient antecedent basis for this limitation in the claims.
Hence, dependent claims 2-8, 10-16, and 18-20 are also rejected.
Claims 5 and 13 recite the limitation "the complexity of the spectrum of the first synthesized audio at the first frequency" in line 5 of claim 5 and line 5 of claim 13. There is insufficient antecedent basis for this limitation in the claims.
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, 6, 9, 14, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wouters et al. (US 20210050024 A1) and further in view of Cutler et al. (US 20240112686 B1).
As to independent claim 1, Wouters et al. teaches:
1. A method for determining a source of synthesized audio (see ¶ [0002-0004]: “[0002] In accordance with an embodiment of the invention, an audio watermark is embedded in synthetic speech, such as synthetic speech created using text-to-speech (TTS) synthesis…”, “[0003] One embodiment according to the invention is a computerized method of processing a synthetic speech signal to facilitate distinguishing of the synthetic speech signal from a natural human speech signal…”, and “[0004] … The audio watermark signal may comprise data regarding a source of the synthetic speech signal…”), comprising:
generating (see ¶ [0002-0004] citations as in preamble above, more specifically ¶ [0004]: “… The audio watermark signal may comprise data regarding a source of the synthetic speech signal…”” and further Fig. 1 (108: audio watermark processor) and ¶ [0022]: “… The processor 102 and the memory 104, with the computer code instructions, are configured to implement an audio watermark processor 108. The audio watermark processor 108 is configured to, during or after generating the synthetic speech signal 107, automatically embed an audio watermark signal (symbolized here as W.sub.1) into the synthetic speech signal 107 based on an audio watermark key 110. For example, the audio watermark processor 108 can add the audio watermark signal, W.sub.1, to the output of a synthetic speech generator 106, such as a text-to-speech (TTS) synthesis system, either during or after its generation of the synthetic speech signal 107, S.sub.1…”);
fusing a digital watermark into the (see ¶ [0002-0004] citations as in preamble above and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and ¶ [0022] citations as in limitation(s) above and further ¶ [0022]: “…The audio watermark processor 108 is configured to, during or after generating the synthetic speech signal 107, automatically embed an audio watermark signal (symbolized here as W.sub.1) into the synthetic speech signal 107 based on an audio watermark key 110...”);
determining a target embedding position of the digital watermark based on a spectrum of the first synthesized audio (see ¶ [0002-0004] citations as in limitation(s) above and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and ¶ [0022] citations as in limitation(s) above and further ¶ [0025-0026]: “[0025] In one example in FIG. 2, the audio watermark processor 208 can be configured to embed the audio watermark signal into the synthetic speech signal by embedding the audio watermark signal in a pitch synchronous pattern 214 based on at least one pitch period 212 of the synthetic speech signal. As noted, information regarding pitch periods 212 is already available to the synthetic speech system, or can be easily generated. In this example, the audio watermark key 210a comprises the pitch synchronous pattern 214, symbolized in FIG. 2 by the two watermark signal pulses 214 at synchronous locations with the pitch periods 212 filled in black in FIG. 2. In this way, the audio watermark signal can be rendered less perceptible by a malicious actor, by having the audio watermark signal's energy coincide with pitch periods 212 that tend to render the audio watermark signal less perceptible, for example. [0026] In another example in FIG. 2, the audio watermark signal can be embedded into the synthetic speech signal based on a spectral pattern 218. For example, spectral pattern 218 comprises the second and fourth regions of the four spectral regions 216 of the synthetic speech signal (as a symbolic illustration), and a spectral pattern known by both the sender and the recipient of the synthetic speech signal can assist in rendering the audio watermark signal less perceptible. Here, the audio watermark key 210b comprises the spectral pattern 218. The spectral pattern 218 can, for example, be a spread spectrum pattern; and it can resemble noise. This method can, for example, be suitable for TTS systems that use spectral patterns as an intermediate representation, such as parametric TTS systems and waveform generation systems.”),
wherein the digital watermark indicates a source of the first synthesized audio (see ¶ [0002-0004] citations as in limitation(s) above and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and ¶ [0002-0004, 0022, and 0025-0026] citations as in limitation(s) above, more specifically: ¶ [0004]: “… The audio watermark signal may comprise data regarding a source of the synthetic speech signal…”); and
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generating second synthesized audio based on the fused (see ¶ [0002-0004, 0022, and 0025-0026] citations as in preamble above and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and Fig. 1 (108: audio watermark processor, 110: audio watermark key, and 109: audio watermarked synthetic speech signal) and ¶ [0002, 0004, and 0022] citations as in limitation(s) above and further ¶ [0022]: “…For example, the audio watermark processor 108 can add the audio watermark signal, W.sub.1, to the output of a synthetic speech generator 106, such as a text-to-speech (TTS) synthesis system, either during or after its generation of the synthetic speech signal 107, S.sub.1. The result is an audio watermarked synthetic speech signal 109 (symbolized here as S.sub.1+W.sub.1). By the embedding of the audio watermark signal W.sub.1, the system thereby permits distinguishing of the synthetic speech signal 107 from a natural human speech signal when the audio watermark signal W.sub.1 is detected by a machine recipient 450 (see FIG. 4) of the synthetic speech signal, S.sub.1+W.sub.1, that is in possession of the same audio watermark key (110/410, see FIGS. 1 and 4)…” ¶ [0025]: “ In this example, the audio watermark key 210a comprises the pitch synchronous pattern 214, symbolized in FIG. 2 by the two watermark signal pulses 214 at synchronous locations with the pitch periods 212 filled in black in FIG. 2…”, and ¶ [0026]: “In another example in FIG. 2, the audio watermark signal can be embedded into the synthetic speech signal based on a spectral pattern 218. For example, spectral pattern 218 comprises the second and fourth regions of the four spectral regions 216 of the synthetic speech signal (as a symbolic illustration), and a spectral pattern known by both the sender and the recipient of the synthetic speech signal can assist in rendering the audio watermark signal less perceptible...”).
However, Wouters et al. does not explicitly teach, but Cutler et al. does teach:
generating structured noise of first (see ¶ [0047]: “In various examples, the audio processor 114 generates a suitable audio watermark for the first audio signal. In one example, the conferencing session is associated with a meeting join sound that comprises the audio watermark. In other examples, the audio watermark is included in other suitable notification sounds associated with the conferencing session. In still other examples, inserting the first audio signal into the audio receive channel comprises generating the audio watermark as a structured noise pattern. In one such example, generating the audio watermark as the structured noise pattern comprises sampling background noise from a microphone of the participant device and generating the structured noise pattern to simulate the sampled background noise. In another example, generating the audio watermark as the structured noise pattern comprises generating the structured noise pattern to simulate white noise. In yet another example, generating the audio watermark as the structured noise pattern comprises generating the structured noise pattern to simulate comfort noise. By using the structured noise pattern, comfort noise, or background noise for the audio watermark, the audio watermark is effectively concealed from the participants of the conferencing session.”);
fusing a digital watermark into the structured noise (see ¶ [0047] citation as in limitation(s) above, more specifically: “…In still other examples, inserting the first audio signal into the audio receive channel comprises generating the audio watermark as a structured noise pattern....”
and further ¶ [0042]: “At step 504, a first audio signal is inserted into the audio receive channel for playback by the participant device. For example, the audio processor 114 generates the first audio signal to include an audio watermark and inserts the first audio signal into the audio receive channel (e.g., audio receive channel 204).”);
generating second (see ¶ [0042 and 0047] citation as in limitation(s) above. More specifically: ¶ [0042]: “At step 504, a first audio signal is inserted into the audio receive channel for playback by the participant device. For example, the audio processor 114 generates the first audio signal to include an audio watermark and inserts the first audio signal into the audio receive channel (e.g., audio receive channel 204).”).
Wouters et al. and Cutler et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. to incorporate the teachings of Cutler et al. of generating structured noise of first audio based on the first audio; fusing a digital watermark into the structured noise; generating second audio based on the fused structured noise and the first audio which provides the benefit of providing audio status (e.g., audio system being functional, or not functional) for participant device (s) ([0019] of Cutler et al.).
As to independent claim 9, Wouters et al. further teaches:
9. An electronic device (see ¶ [0022]: “In the embodiment of FIG. 1, the system 100 comprises a processor 102, and a memory 104 with computer code instructions stored thereon. The processor 102 and the memory 104, with the computer code instructions, are configured to implement an audio watermark processor 108.”), comprising:
at least one processor (see ¶ [0022] citation as in limitation above: “processor 102”); and
a memory coupled to the at least one processor and having instructions stored therein (see ¶ [0022] citation as in limitation above: “memory 104”), wherein the instructions, when executed by the at least one processor, cause the electronic device to perform actions (see ¶ [0022] citation as in limitation above: “computer code instructions”) comprising:
[the limitations taught by Wouters et al. in combination with Cutler et al. as in claim 1, above]
As to independent claim 17, Wouters et al. further teaches:
17. A computer program product, the computer program product being tangibly stored on a non-transitory computer-readable medium and comprising machine-executable instructions (see ¶ [0009]: “A further embodiment according to the invention is a non-transitory computer-readable medium configured to store instructions for processing a synthetic speech signal to facilitate distinguishing of the synthetic speech signal from a natural human speech signal,…”), wherein the machine-executable instructions, when executed by a machine, cause the machine to perform actions (see ¶ [0009]: “… the instructions, when loaded and executed by a processor, cause the processor to process the synthetic speech signal to facilitate distinguishing of the synthetic speech signal from a natural human speech signal…”) comprising:
[the limitations taught by Wouters et al. in combination with Cutler et al. as in claim 1, above]
Regarding claims 6 and 14, Wouters et al. teaches the limitations as in claims 1 and 9, above.
Wouters et al. further teaches:
6 and 14. The method/electronic device according to claims 1 and 9, (wherein the actions [only on claim 14]) further comprising:
obtaining a target input audio for determining the source of the synthesized audio (see ¶ [0005]: “Another embodiment according to the invention is a computerized method of determining whether a speech signal is a natural human speech signal or a synthetic speech signal. The method comprises, with a machine recipient of the speech signal, the machine recipient being in possession of an audio watermark key, determining absence or presence of an audio watermark signal embedded into the speech signal based on the audio watermark key; and, based on a determined absence of the audio watermark signal, distinguishing the speech signal as being a natural human speech signal or, based on a determined presence of the audio watermark signal, distinguishing the speech signal as being a synthetic speech signal. The audio watermark signal to be detected is imperceptible by natural human audio perception of the synthetic speech signal with the embedded audio watermark signal.”);
applying the target input audio to an embedding model to obtain a classification result of the embedding model for the target input audio (see ¶ [0005] citation as in limitation above: “… the invention is a computerized method of determining whether a speech signal is a natural human speech signal or a synthetic speech signal…” and further ¶ [0004]: “…. Embedding the audio watermark signal may comprise: (i) embedding the audio watermark signal in a pitch synchronous pattern based on at least one pitch period of the synthetic speech signal, and wherein the audio watermark key comprises the pitch synchronous pattern or comprises information with which the pitch synchronous pattern can be derived or reconstructed; (ii) embedding the audio watermark signal into the synthetic speech signal based on a spectral pattern, and wherein the audio watermark key comprises the spectral pattern or comprises information with which the spectral pattern can be derived or reconstructed; or (iii) embedding the audio watermark signal into the synthetic speech signal based on a frequency hopping sequence, and wherein the audio watermark key comprises the frequency hopping sequence or comprises information with which the frequency hopping pattern can be derived or reconstructed. The audio watermark signal may comprise data regarding a source of the synthetic speech signal…”);
determining, in response to the classification result being classified into a first class, that the target input audio carries the digital watermark (see ¶ [0005] citation as in limitation above: “…, based on a determined absence of the audio watermark signal, distinguishing the speech signal as being a natural human speech signal or, based on a determined presence of the audio watermark signal, distinguishing the speech signal as being a synthetic speech signal…”); and
determining, in response to the classification result being classified into a second class, that the target input audio does not carry the digital watermark (see ¶ [0005] citation as in limitation above: “…, based on a determined absence of the audio watermark signal, distinguishing the speech signal as being a natural human speech signal or, based on a determined presence of the audio watermark signal, distinguishing the speech signal as being a synthetic speech signal…”).
Claims 2, 10, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wouters et al. (US 20210050024 A1) further in view of Cutler et al. (US 20240112686 B1) as applied to claim(s) 1, 9, and 17 above, and further in view of Gurijala et al. (US 10236006 B1).
Regarding claims 2, 10, and 18, Wouters et al. teaches the limitations as in claims 1, 9, and 17, above.
Wouters et al. further teaches:
2, 10, and 18. The method/electronic device/computer program product according to claims 1, 9 and 17,
wherein generating the (see ¶ [0002-0004 and 0022] citations as in claim 1 above and Fig. 1 (108: audio watermark processor))
Cutler et al. further teaches:
generating structured noise of first (see ¶ [0045 and 0047] citations as in claim 1 above )
Wouters et al. and Cutler et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. to incorporate the teachings of Cutler et al. of generating structured noise of first audio based on the first audio which provides the benefit of providing audio status (e.g., audio system being functional, or not functional) for participant device (s) ([0019] of Cutler et al.).
However, Wouters et al. in combination with Cutler et al. do not explicitly teach, but Gurijala et al. does teach:
comprises: generating a pseudo-random sequence based on the first synthesized audio (see ¶ Col. 19, lines 40-57: “(111) Varying sound strength of the host audio can also affect its ability to mask a watermark signal. Loudness is a subjective measure of strength of a sound to a human listener in which the sound is ordered on a scale from quiet to loud. Objective measures of sound strength include sound pressure, sound pressure level (in decibels), sound intensity or sound power. Loudness is affected by parameters including sound pressure, frequency, bandwidth and duration. The human auditory system integrates the effects of sound pressure level over a 600-1000 ms window. Loudness for a constant SPL will be perceived to increase in loudness with increasing duration, up to about 1 second, at which time the perception of loudness stabilizes. The sensitivity of the human ear also changes as function of frequency, as represented in equal loudness graphs. Equal loudness graphs provide SPLs required for sounds at different frequencies to be perceived as equally loud.”
¶ Col. 20, line 65 - Col. 21, line 5: “(119) The watermark protocol specifies signal communication techniques employed, such as a type of data modulation to encode data using a signal carrier. One such example is direct sequence spread spectrum (DSSS) where a pseudo random carrier is modulated with data. There are a variety of other types of modulation, phase modulation, phase shift keying, frequency modulation, etc. that can be applied to generate a watermark signal.”); and
modulating the pseudo-random sequence to generate the (structured noise as taught by Cutler et al. in claims 1, 9, and 17 as well as in limitation, above.) (see Gurijala ¶ Col. 19, lines 40-57 and ¶ Col. 20, line 65 - Col. 21, line 5 citations as in limitation(s) above and further ¶ Col. 2, lines 15-20: “… In some embodiments, the classifier determines noise or other types of distortion that are present in the incoming audio signal (“detected noise”), or that are anticipated to be incurred by the watermarked audio after it is distributed (“anticipated noise”)…” and
¶ Col. 22, lines 31-67: “(129) In our implementations, options for DWM types include both frequency domain and time domain watermark signals. (130) One frequency domain option is a constellation of peaks in the frequency magnitude domain. This option can be used as a fixed data, synchronization component of the watermark signal. It may also carry variable data by assigning code symbols to sets of peaks at different frequency locations. Further, auxiliary data may be conveyed by mapping data symbols to particular frequency bands for particular time offsets within a segment of audio. In such case, the presence or absence of peaks within particular bands and time offsets provides another option for conveying data. (131) There are variations on the basic option of code symbols that correspond to signal peaks. One option is to vary the mapping of a code symbol to inserted peaks at frequency locations over time and/or frequency band. Another is to differentially encode a peak at one location relative to trough or notch at another location. Yet another option is to use the phase characteristics of an inserted peak to convey additional data or synchronization information. For example, the phase of the peak signal can be used to detect the translational shift of the peak. (132) Another option is a DSSS modulated pseudo random watermark signal applied to selected frequency magnitude domain locations. This particular option is combined with differential encoding for adjacent frames. Within each frame, the DSSS modulation yields a binary antipodal signal in which frequency locations (bump locations) are adjusted up or down according to the watermark signal chip value mapped to the location. In the adjacent frame, the watermark signal is applied similarly, but is inverted. Due to the correlation of the host signal in neighboring frames, this approach allows the detector to increase the watermark to host signal gain by taking the difference between adjacent frames, with the watermark signal adding constructively, and the host signal destructively (i.e. host signal is reduced based on correlation of host signal in these adjacent frames).”).
Wouters et al., Cutler et al. and Gurijala et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. in combination with Cutler et al. to incorporate the teachings of Gurijala et al. of generating a pseudo-random sequence based on the first synthesized audio and modulating the pseudo-random sequence to generate the noise which provides the benefit of not requiring a separate channel outside the audio information (Col. 1, lines 44-45 of Gurijala et al.).
Claims 3, 5, 11, 13, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wouters et al. (US 20210050024 A1) further in view of Cutler et al. (US 20240112686 B1) as applied to claim(s) 1, 9, and 17 above, and further in view of Stavropoulos et al. (WO 2014065902 A1).
Regarding claims 3, 11, and 19, Wouters et al. teaches the limitations as in claims 1, 9, and 17, above.
Wouters et al. further teaches:
3, 11, and 19. The method/electronic device/computer program product according to claims 1, 9 and 17, (wherein the actions [only on claim 11]) further comprising:
generating the digital watermark based on the first synthesized audio (see ¶ [0002-0004 and 0022] citations as in claim 1 above and Fig. 1 (108: audio watermark processor)),
However, Wouters et al. in combination with Cutler et al. do not explicitly teach, but Stavropoulos et al. does teach:
wherein the digital watermark comprises at least an identification of a synthesizer of the first synthesized audio, timestamp information of the first synthesized audio, and information of a synthesizing model for synthesizing the first synthesized audio (see ¶ [0030]: “Turning to FIG. 2A, an exemplary time-domain encoding diagram utilizing time synchronization is illustrated, where audio 21 1 is received at an input of encoder 200, together with one or more codes 210. Code 210 (also referred to in the art as a watermark) may designate broadcaster identification [i.e., identification of synthesizer], programming data [i.e., information of synthesizing model], or any other information that may be desirable to psychoacoustically insert into audio. As encoder 200 is based on time-domain encoding, code 210 is directly embedded into audio signal, and no domain transform is required. In code insertion/modulation block 217, code 210 is shaped before embedding operation to ensure robustness, and is inserted directly into the audio by adding the code to the audio signal. Shaping the code before embedding enables the encoder to maintain the original audio signal audibility and renders the code inaudible. Suitable techniques for time-domain encoding include low- bit encoding, pulse code modulation (PCM), differential PCM (DPCM) and adaptive DPCM (ADPCM). A synchronization signal 213 is received from a local external source (e.g., device 110), where interface 214 updates the accurate time for clock 215. Time data from clock 215 is used for generating timestamps 216 for embedded code 210 [i.e., timestamp information] into the audio at block 217, resulting in encoded audio 218.”).
Wouters et al., Cutler et al. and Stavropoulos et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. in combination with Cutler et al. to incorporate the teachings of Stavropoulos et al. of wherein the digital watermark comprises at least an identification of a synthesizer of the first synthesized audio, timestamp information of the first synthesized audio, and information of a synthesizing model for synthesizing the first synthesized audio which provides the benefit of providing improved time data which in turn produces more accurate results. ([0037] of Stavropoulos et al.).
Regarding claim 5 and 13, Wouters et al. in combination with Stavropoulos et al. teaches the limitations as in claims 3 and 11, above.
Wouters et al. further teaches:
5 and 13. The method/electronic device according to claims 3 and 11,
wherein determining the target embedding position of the digital watermark based on the spectrum of the first synthesized audio (see ¶ [0002-0004, 0022, and 0025-0026] citations as in claim 1 above and Fig. 1 (108: audio watermark processor and 110: audio watermark key)) comprises:
determining, in response to a short-time spectrum representation of the first synthesized audio at a first frequency and a first moment being lower than a human auditory threshold (see ¶ [0002-0004, 0022, and 0025-0026] citations as in claim 1 above, more specifically: ¶ [0025-0026]: “[0025] In one example in FIG. 2, the audio watermark processor 208 can be configured to embed the audio watermark signal into the synthetic speech signal by embedding the audio watermark signal in a pitch synchronous pattern 214 based on at least one pitch period 212 of the synthetic speech signal. As noted, information regarding pitch periods 212 is already available to the synthetic speech system, or can be easily generated. In this example, the audio watermark key 210a comprises the pitch synchronous pattern 214, symbolized in FIG. 2 by the two watermark signal pulses 214 at synchronous locations with the pitch periods 212 filled in black in FIG. 2. In this way, the audio watermark signal can be rendered less perceptible by a malicious actor, by having the audio watermark signal's energy coincide with pitch periods 212 that tend to render the audio watermark signal less perceptible, for example. [0026] In another example in FIG. 2, the audio watermark signal can be embedded into the synthetic speech signal based on a spectral pattern 218. For example, spectral pattern 218 comprises the second and fourth regions of the four spectral regions 216 of the synthetic speech signal (as a symbolic illustration), and a spectral pattern known by both the sender and the recipient of the synthetic speech signal can assist in rendering the audio watermark signal less perceptible. Here, the audio watermark key 210b comprises the spectral pattern 218. The spectral pattern 218 can, for example, be a spread spectrum pattern; and it can resemble noise. This method can, for example, be suitable for TTS systems that use spectral patterns as an intermediate representation, such as parametric TTS systems and waveform generation systems.”), and
in response to the complexity of the spectrum of the first synthesized audio at the first frequency and the first moment being lower than a complexity threshold, that the spectrum at the first frequency and the first moment is the target embedding position (see ¶ [0002-0004, 0022, and 0025-0026] citations as in claim 1 above, more specifically: “[0026] …For example, spectral pattern 218 comprises the second and fourth regions of the four spectral regions 216 of the synthetic speech signal (as a symbolic illustration), and a spectral pattern known by both the sender and the recipient of the synthetic speech signal can assist in rendering the audio watermark signal less perceptible…”).
Claim 4, 12, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wouters et al. (US 20210050024 A1) further in view of Cutler et al. (US 20240112686 B1) and Stavropoulos et al. (WO 2014065902 A1) as applied to claim(s) 3, 11 and 19 above, and further in view of Watson et al. (US 20040024588 A1).
Regarding claims 4, 12, and 20, Wouters et al. in combination with Stavropoulos et al. teaches the limitations as in claims 3, 11, and 19, above.
Wouters et al. further teaches:
4, 12, and 20. The method/electronic device/computer program product according to claims 3, 11, and 19,
wherein fusing the digital watermark into the (see ¶ [0002-0004] citations as in preamble above and Fig. 1 (108: audio watermark processor and 110: audio watermark key) and ¶ [0022] citations as in limitation(s) above and further ¶ [0022]: “…The audio watermark processor 108 is configured to, during or after generating the synthetic speech signal 107, automatically embed an audio watermark signal (symbolized here as W.sub.1) into the synthetic speech signal 107 based on an audio watermark key 110...”)
Cutler et al. further teaches:
fusing the digital watermark into the structured noise (see ¶ [0045 and 0047] citations as in claim 1 above.)
Wouters et al. and Cutler et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. to incorporate the teachings of Cutler et al. of fusing the digital watermark into the structured noise which provides the benefit of providing audio status (e.g., audio system being functional, or not functional) for participant device (s) ([0019] of Cutler et al.).
However, Wouters et al. in combination with Cutler et al. and Stavropoulos et al. do not explicitly teach, but Watson et al. does teach:
comprises: converting the digital watermark into a digital signal through an encoding function (see ¶ [0175]: “In the Dolby Digital algorithm or coding process, even if the content in the upper frequency bands is determined to be insignificant, a coarse power spectrum is transmitted in the bitstream that can be used in the decoder to add random noise shaped to the power spectrum. This is a feature of the decoder that is turned on when the dither flag in the bitstream is enabled. The added noise in the decoder recreates the watermark in the decoded audio even if the encoder has judged it perceptually insignificant. The watermark may be inserted during either the encoding or the decoding process.”); and
fusing the digital signal of the digital watermark with the (structured noise as taught by Cutler et al. in claims 1, 9, and 17, as well as in limitation above.) (see ¶ [0175]: “…added noise in the decoder recreates the watermark in the decoded audio…”).
Wouters et al., Cutler et al., Stavropoulos et al. and Watson et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in audio watermarking. 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 Wouters et al. in combination with Cutler et al. and Stavropoulos et al. to incorporate the teachings of Watson et al. of converting the digital watermark into a digital signal through an encoding function and fusing the digital signal of the digital watermark with the noise which provides the benefit of improving security, in the sense that it becomes possible to reveal all aspects of the watermarking system (except for the deterministic sequence key) without sacrificing the robustness of the system ([0049] of Watson et al.).
Claims 7-8 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wouters et al. (US 20210050024 A1) further in view of Cutler et al. (US 20240112686 B1) as applied to claim(s) 1, 9, and 17 above, and further in view of Baughman et al. (US 11012662 B1).
Regarding claims 7 and 15, Wouters et al. teaches the limitations as in claims 6 and 14, above.
However, Wouters et al. in combination with Cutler et al. do not explicitly teach, but Baughman et al. does teach:
7 and 15. The method/electronic device according to claims 6 and 14, (wherein the actions [only on claim 15]) further comprising:
training the embedding model based on a training second synthesized audio (see ¶ Col. 6, line 44 – Col. 7, line 10: “(32) An embodiment configures and trains an embedding model, or configures an already-trained embedding model for use. An embedding model takes as its input a corpus of narrative text and produces a vector space, typically of several hundred dimensions, with each unique word, phrase, or other unit of narrative text in the corpus being assigned a corresponding vector in the space. Vectors are positioned in the vector space such that words that share common contexts in the corpus are located close to one another in the space. This spatial relationship between vectors allows a numerical model, such as a neural network, to learn and manipulate narrative text while taking textual context into account. One non-limiting example of a configuration for an embedding model is a two-layer neural network. Other embedding model configurations are also possible and contemplated within the scope of the illustrative embodiments. (33) Embedding models that already trained on a contemporary corpus of text are presently available. However, if a time characteristic of an adjustment specification is not the present day, a model trained on contemporary text is not necessarily appropriate to that time characteristic. For example, word usage, slang terms, and even the meaning of words changes over time, and new words are invented to describe new inventions. Thus, an embodiment adjusts a training corpus to conform to the time characteristic, then uses the adjusted training corpus to train the embedding model. (34) In particular, for a time characteristic in the past, an embodiment uses, as the training corpus, textual summaries of comparable multimedia content having that time characteristic. For example, if a time characteristic of an adjustment specification is to adjust the content to the 1970s, comparable content also having a time characteristic of the 1970s, would be used. ”).
Wouters et al., Cutler et al. and Baughman et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in multimedia processing (e.g., audio/speech). 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 Wouters et al. in combination with Cutler et al. to incorporate the teachings of Baughman et al. of training the embedding model based on a training second synthesized audio which provides the benefit of allowing a numerical model, such as a neural network, to learn and manipulate narrative text while taking textual context into account (¶ Col. 6, lines 44-59 of Baughman et al.).
Regarding claims 8 and 16, Wouters et al. teaches the limitations as in claims 7 and 15, above.
However, Wouters et al. in combination with Cutler et al. do not explicitly teach, but Baughman et al. does teach:
8 and 16. The method/electronic device according to claims 7 and 15,
wherein training the embedding model based on the training second synthesized audio (see ¶ Col. 6, line 44 – Col. 7, line 10 citations as in claims 7 and 15, above. More specifically: ““(32) An embodiment configures and trains an embedding model, or configures an already-trained embedding model for use. […] Thus, an embodiment adjusts a training corpus to conform to the time characteristic, then uses the adjusted training corpus to train the embedding model. ”) comprises:
inputting a training first synthesized audio into the embedding model to generate the training second synthesized audio (see ¶ Col. 6, line 44 – Col. 7, line 10 citations as in claims 7 and 15, above and further ¶ Col. 20, lines 45-67: “(129) In block 1102, the application receives an adjustment specification specifying an adjustment to be made to a multimedia content, the adjustment including a time characteristic. In block 1104, the application matches, within a tolerance, the multimedia content to a set of comparable multimedia contents having a characteristic corresponding to the adjustment specification. In block 1106, the application uses the set of comparable multimedia contents to configure and train an embedding model. In block 1108, the application uses the trained embedding model and the set of comparable multimedia contents to generate a set of styles comprising modified video frames modified from video frames in the set of comparable multimedia contents. In block 1110, the application uses a frame adjustment model and a style in the set of styles to adjust a video frame of the multimedia content. ”);
inputting the training second synthesized audio into a training response model, and generating a training output audio of the training response model (see ¶ Col. 6, line 44 – Col. 7, line 10 citations as in claims 7 and 15, above and further ¶ Col. 20, lines 45-67 citations as in limitation above and further ¶ Col. 20, lines 45-67 : “…In block 1112, the application uses an audio adjustment model and the trained embedding model to adjust an audio portion of the multimedia content. In block 1114, the application synchronizes the video frame of the multimedia content and the audio portion of the multimedia content, producing an adjusted multimedia content adjusted according to the adjustment characteristic. Then the application ends.”); and
adjusting parameters of the embedding model based on the training output audio and the training second synthesized audio (¶ Col. 6, line 44 – Col. 7, line 10 citations as in claims 7 and 15, above and further ¶ Col. 20, lines 45-67 citations as in limitation above and further ¶ Col. 20, lines 45-67 : “…In block 1112, the application uses an audio adjustment model and the trained embedding model to adjust an audio portion of the multimedia content. In block 1114, the application synchronizes the video frame of the multimedia content and the audio portion of the multimedia content, producing an adjusted multimedia content adjusted according to the adjustment characteristic. Then the application ends.”).
Wouters et al., Cutler et al. and Baughman et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in multimedia processing (e.g., audio/speech). 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 Wouters et al. in combination with Cutler et al. to incorporate the teachings of Baughman et al. of inputting a training first synthesized audio into the embedding model to generate the training second synthesized audio; inputting the training second synthesized audio into a training response model, and generating a training output audio of the training response model; and adjusting parameters of the embedding model based on the training output audio and the training second synthesized audio which provides the benefit of allowing a numerical model, such as a neural network, to learn and manipulate narrative text while taking textual context into account (¶ Col. 6, lines 44-59 of Baughman et al.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Regarding audio watermarking (pertinent to claims 1, 9, and 17):
Van Der Veen et al. (US 20060168448 A1) ([0057] and Fig. 5-6)
Matsumura et al. (US 7272718 B1) (Col. 4, lines 56-65 and Col. 8, lines 1-11)
Regarding modulation of pseudo-random sequences (pertinent to claims 2, 10, and 18):
Tuttle et al. (US 6266362 B1) (Col. 3, lines 25-49 and Fig. 8A-8B)
Regarding modulation of pseudo-random sequences (pertinent to claims 3, 11, and 19):
Dai et al. (US 20180033113 A1) ([0025])
Hoffman et al. (US 20130304604 A1) ([0173])
Regarding modulation of watermarking and digital signals (pertinent to claims 4, 12, and 20):
Levine (US 6219634 B1) (Col. 2, line 42 – Col. 3, line 23)
Regarding modulation of watermarking and digital signals (pertinent to claims 7, and 15):
Sharifi (US 20210183367 A1) ([0005])
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Keisha Y. Castillo-Torres
Examiner
Art Unit 2659
/Keisha Y. Castillo-Torres/Examiner, Art Unit 2659
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