DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendments filed February 18th, 2026 have been entered. Claims 21, 23, 28, 29, 31, 35, and 39 have been amended. Claims 21-40 are pending and have been examined. Applicant’s amendments to the specification and the claims have overcome all objections and rejections under 35 U.S.C. 112 previously set forth.
Response to Arguments
Applicant’s arguments with respect to claim(s) 21-40 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 21, 25-31, 34, and 39-40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bryan, Nicholas (US Pat. Pub. No. 2021/0142815 A1 hereinafter Bryan), in view of Isik et al. (US Pat. No. 12,008,457 B1 hereinafter Isik).
Regarding claim 21, Bryan discloses a method for dereverberating audio signals, the method comprising: obtaining, by a control system a real acoustic impulse response (AIR) (Bryan, [0026]: " This disclosure describes one or more embodiments of an impulse response system that generates accurate and realistic synthetic impulse responses. In particular, the impulse response system can parametrically control reverberation time and/or direct-to-reverberant ratio (DRR) as a function of frequency to generate synthetic impulse responses. For example, given an acoustic impulse response, the impulse response system can generate one or more synthetic impulse responses that modify the DRR by utilizing a windowed approach to applying a scalar gain to the early response signal. In addition, the impulse response system can generate one or more synthetic impulse responses that modify the reverberation time (e.g., T60) by removing a noise floor from a late-field response signal and adjusting the signal to a target decay rate. Further, utilizing the synthetic impulse responses, the impulse response system can perform a variety of functions to directly and/or indirectly improve a digital audio recording and/or signal processing."); identifying, by the control system, a first portion of the real AIR that corresponds to early reflections of a direct sound and a second portion of the real AIR that corresponds to late reflections of the direct sound (Bryan, [0044]: "Acoustic impulse responses includes an early-field response portion (or simply “early response”) and a late-field response portion (or simply “late response”). The early response can include a direct path arrival and early reflections (e.g., residual) imposed by the microphone-room geometry, while a late response can include information about the room volume and materials."; [0045]: "In various embodiments, an acoustic impulse response can be represented as shown below in Equations 1-3."); and generating, by the control system, one or more synthesized AIRs by modifying the first portion of the real AIR and/or the second portion of the real AIR (Bryan, [0029]: " the impulse response system can generate a synthetic impulse response by modifying one or more portions of an acoustic impulse response."). However, Bryan fails to expressly recite using, by the control system, the real AIR and the one or more synthesized AIRs to generate a plurality of training samples, each training sample comprising a non-reverberated input audio signal and a reverberated audio signal, wherein the reverberated audio signal is generated based at least in part on the non-reverberated input audio signal and one of the real AIR or one of the one or more synthesized AIRs, wherein the plurality of training samples are used to train a machine learning model that takes, as an input, a test audio signal with reverberation and generates, as an output, a dereverberation mask that when applied to a particular reverberated audio signal, generates a particular predicted dereverberated audio signal.
Isik teaches using, by the control system, the real AIR and the one or more synthesized AIRs to generate a plurality of training samples, each training sample comprising a non-reverberated input audio signal and a reverberated audio signal, wherein the reverberated audio signal is generated based at least in part on the non-reverberated input audio signal and one of the real AIR or one of the one or more synthesized AIRs (Isik, Col. 8, lines 39-48: “In various embodiments, synthetic reverberation may be applied, in some embodiments, in the dataset using a library of recorded and synthetically generated room impulse responses. Separate models may be trained to target the task with and without partial dereverberation. For non-dereverberating models, reverberation is added during training to the clean speech data as an augmentation before mixing. For training partially dereverberating models a faster decaying version of the reverberation may be added to the clean speech labels.”), wherein the plurality of training samples are used to train a machine learning model that takes, as an input, a test audio signal with reverberation and generates, as an output, a dereverberation mask that when applied to a particular reverberated audio signal, generates a particular predicted dereverberated audio signal (Isik, Col. 10, lines 25-30: “The first model may be a speech enhancement model that also does full dereverberation that is trained to estimate the reverb-only portion h*s−s, along with the clean signal s and noise n. This model uses the same architecture as discussed with regard to FIG. 4, but may use fewer filters, and early stopping to avoid overfitting.”; Col. 9, lines 41-44: “A real complex ratio mask 404 may be the output of the model along with imaginary complex ratio mask 408 which are used to generate enhanced audio data 406 through performance of inverse STFT 435.”).
Bryan and Isik are analogous arts because they both belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan to incorporate the teachings of Isik to generate training data and train a machine learning model for dereverberation. This allows for effective dereverberation of audio as part of audio enhancement in an audio processing system (Isik, Col. 1, Background). As such, the system can generate optimal audio for a user or for further processing.
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Bryan, Equations 1-3, for reference
Regarding claim 25, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses wherein modifying the second portion of the real AIR comprises truncating the second portion of the real AIR after a duration of time randomly selected from a predetermined range of late reflection durations (Bryan, [0057]: "the impulse response system can generate a synthetic impulse response by modifying the reverberation time. For example, the impulse response system can revise a decay rate parameter based on a target decay rate parameter (e.g., for one or more frequency sub-bands or for the entire full-band)."; [0140]: "In some embodiments, the impulse responses can be generated to have uniformly random statistics (e.g., yielding a DRR between −6-8 dB along with a T60 between 0.1-1.5 seconds)."; Here, changing the reverberation time and decay rate is seen as truncation because it changes the end time of the signal.).
Regarding claim 26, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses wherein modifying the second portion of the real AIR comprises modifying amplitudes of one or more responses included in the second portion of the real AIR (Bryan, [0057]: "In additional or alternative embodiments, the impulse response system can generate a synthetic impulse response by modifying the reverberation time. For example, the impulse response system can revise a decay rate parameter based on a target decay rate parameter (e.g., for one or more frequency sub-bands or for the entire full-band)."; Here, changing the decay rate is seen as modifying the amplitudes of the responses in the second portion of the acoustic impulse response.).
Regarding claim 27, the rejection of claim 26 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses wherein modifying the amplitudes of the one or more responses included in the second portion of the real AIR comprises: determining a target attenuation function associated with the second portion of the real AIR; and modifying the amplitudes of the one or more responses included in the second portion of the real AIR in accordance with the target attenuation function (Bryan, [0057]: "In additional or alternative embodiments, the impulse response system can generate a synthetic impulse response by modifying the reverberation time. For example, the impulse response system can revise a decay rate parameter based on a target decay rate parameter (e.g., for one or more frequency sub-bands or for the entire full-band)."; Here, changing the decay rate is seen as modifying the amplitudes of the responses in the second portion of the acoustic impulse response. Additionally, since changing the decay rate changes how the impulse response attenuates, changing the decay rate is seen as changing the attenuation function.).
Regarding claim 28, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Isik further teaches wherein the reverberated audio signal is generated by convolving the non-reverberated input audio signal with the one of the real AIR or the one of the one or more synthesized AIRs (Isik, Col. 9, lines 60-67: “In various embodiments, let s be the clean speech audio signal and x=s*h+n be the same signal with added noise n and reverberated version s*h, which is convolved with a room impulse response h, and let y be the denoised and/or dereverberated target signal. The neural model N takes as input the STFT of the reverberant and noisy example s*h+n and estimates the complex ratio mask that would give the target signal estimate”). The same motivation for claim 21 applies equally to claim 28.
Regarding claim 29, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Isik further teaches further comprising adding noise to a convolution of the non-reverberated input audio signal with the one of the real AIR or the one of the one or more synthesized AIRs to generate the reverberated audio signal (Isik, Col. 9, lines 60-67: “In various embodiments, let s be the clean speech audio signal and x=s*h+n be the same signal with added noise n and reverberated version s*h, which is convolved with a room impulse response h, and let y be the denoised and/or dereverberated target signal. The neural model N takes as input the STFT of the reverberant and noisy example s*h+n and estimates the complex ratio mask that would give the target signal estimate”). The same motivation for claim 21 applies equally to claim 29.
Regarding claim 30, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses further comprising generating additional synthesized AIRs by: identifying an updated first portion of the real AIR and an updated second portion of the real AIR; and modifying the updated first portion of the real AIR and/or the updated second portion of the real AIR (Bryan, [0029]: "the impulse response system can apply the scalar to the early response and smoothly transition the modified early response to the original late response to reduce discontinuity."; Here, Bryan discloses further modifying an already modified portion of the impulse response.).
Regarding claim 31, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Isik further teaches further comprising providing the plurality of training samples to the machine learning model to generate a trained machine learning model that takes, as the input, the test audio signal with reverberation and generates, as the output, the dereverberation mask that when applied to the particular reverberated audio signal, generates the particular predicted dereverberated audio signal (Isik, Col. 10, lines 25-30: “The first model may be a speech enhancement model that also does full dereverberation that is trained to estimate the reverb-only portion h*s−s, along with the clean signal s and noise n. This model uses the same architecture as discussed with regard to FIG. 4, but may use fewer filters, and early stopping to avoid overfitting.”; Col. 9, lines 41-44: “A real complex ratio mask 404 may be the output of the model along with imaginary complex ratio mask 408 which are used to generate enhanced audio data 406 through performance of inverse STFT 435.”). The same motivation for claim 21 applies equally to claim 31.
Regarding claim 34, the rejection of claim 31 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses wherein the real AIR is generated using a room acoustics model (Bryan, [0027]: "The early response can include a direct path arrival and early reflections imposed by the microphone-room geometry, while a late response can include information about the room volume and materials.").
Regarding claim 39, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses an apparatus including at least one processor and memory, the memory storing instructions that when executed by the at least one processor, causes the at least one processor to perform the method of claim 21 (Bryan, [0186]: " In particular, one or more of the processes described herein may be implemented at least in part as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices (e.g., any of the media content access devices described herein). In general, a processor (e.g., a microprocessor) receives instructions, from a non-transitory computer-readable medium, (e.g., memory), and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein.").
Regarding claim 40, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. Bryan further discloses one or more non-transitory media having software stored thereon, the software including instructions for controlling one or more devices to perform the method of claim 21 (Bryan, [0186]: " In particular, one or more of the processes described herein may be implemented at least in part as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices (e.g., any of the media content access devices described herein). In general, a processor (e.g., a microprocessor) receives instructions, from a non-transitory computer-readable medium, (e.g., memory), and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein.").
Claim(s) 22 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bryan, in view of Isik, as applied to claims 21, 25-31, 34, and 39-40 above, and further in view of Davidson et al. (US Pat. Pub. No. 2019/0364379 A1 hereinafter Davidson).
Regarding claim 22, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. However, Bryan, in view of Isik, fails to expressly recite wherein identifying the first portion of the real AIR that corresponds to early reflections and the second portion of the real AIR that corresponds to late reflections comprises selecting a random time value within a predetermined range, wherein the first portion comprises a portion of the real AIR prior to the random time value, and wherein the second portion comprises a portion of the real AIR after the random time value.
Davidson teaches wherein identifying the first portion of the real AIR that corresponds to early reflections and the second portion of the real AIR that corresponds to late reflections comprises selecting a random time value within a predetermined range, wherein the first portion comprises a portion of the real AIR prior to the random time value, and wherein the second portion comprises a portion of the real AIR after the random time value (Davidson, [0106]: "Reflection control subsystem 111 identifies (i.e., chooses) a set of early reflection paths (comprising one or more early reflection paths) in response to the same sound source direction and distance which determine the direct response, and asserts control values indicative of each such set of early reflection paths to early reflection generation subsystem (generator) 113."; [0107]: "Late response control subsystem 110 asserts control signals to late response generator 114, in response to the same sound source direction and distance which determine the direct response, to cause generator 114 to output a late response portion of one of the candidate BRIRs which corresponds to the sound source direction and distance."; [0109]: "The subsystems of FIG. 6 indicated by dashed boxes (i.e., subsystems 111, 113, and 114) are stochastic elements, in the sense that each outputs a sequence of outputs (driven in part by random variables) in response to each sound source direction and distance asserted to subsystem 101."; Here Davidson is seen as disclosing a system that chooses a late and early section of an impulse response based on random variables.).
Bryan, Isik, and Davidson are analogous arts because they each belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan, as modified by the convolutional neural network of Isik, to incorporate the teachings of Davidson to randomly generate impulse responses. This allows the system to create a variety of different impulse responses (Davidson, [0110]). Creating a variety of impulse responses ensures that the system can generate a highly varied training dataset.
Regarding claim 24, the rejection of claim 21 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. However, Bryan, in view of Isik, fails to expressly recite wherein modifying the first portion of the real AIR comprises randomizing a time point of a response included in the first portion of the real AIR.
Davidson teaches wherein modifying the first portion of the real AIR comprises randomizing a time point of a response included in the first portion of the real AIR (Davidson, [0106]: "Reflection control subsystem 111 identifies (i.e., chooses) a set of early reflection paths (comprising one or more early reflection paths) in response to the same sound source direction and distance which determine the direct response, and asserts control values indicative of each such set of early reflection paths to early reflection generation subsystem (generator) 113."; [0109]: "The subsystems of FIG. 6 indicated by dashed boxes (i.e., subsystems 111, 113, and 114) are stochastic elements, in the sense that each outputs a sequence of outputs (driven in part by random variables) in response to each sound source direction and distance asserted to subsystem 101."; Here, Davidson is seen as disclosing a system that, based at least partially on random variables, chooses paths, and thus detection times, of reflections in an impulse response.).
Bryan, Isik, and Davidson are analogous arts because they each belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan, as modified by the convolutional neural network of Isik, to incorporate the teachings of Davidson to randomly generate impulse responses. This allows the system to create a variety of different impulse responses (Davidson, [0110]). Creating a variety of impulse responses ensures that the system can generate a highly varied training dataset.
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bryan, in view of Isik and Davidson, as applied to claims 22 and 24 above, and further in view of Mansour et al. (US Pat. No. 10,598,543 B1 hereinafter Mansour).
Regarding claim 23, the rejection of claim 22 is incorporated. Bryan, in view of Isik and Davidson, discloses all of the elements of the current invention as stated above. However, Bryan, in view of Isik and Davidson, fails to expressly recite wherein the predetermined range is from about 20 milliseconds to about 80 milliseconds.
Mansour teaches wherein the predetermined range is at least from 20 milliseconds up to 80 milliseconds (Mansour, Col. 9, lines 33-51: "As illustrated in the room impulse response chart 230, the direct sound 222 corresponds to a first peak of the room impulse response, which occurs at a first time (e.g., T.sub.1<10 ms) and has a relatively large amplitude (e.g., magnitude of the first peak is relatively high). The early reflections 224 correspond to a first series of peaks that occur after a short delay during a second time range (e.g., 10 ms<T.sub.2<50 ms) and have smaller amplitudes than the first peak. For example, the first early reflection 224a may correspond to a second peak of the microphone audio data (e.g., 18 ms) and the second early reflection 224b may correspond to a third peak of the microphone audio data (e.g., 23 ms). Finally, the late reflections 226 correspond to a second series of peaks that occur after a lengthy delay during a third time range (e.g., 50 ms<T.sub.3<250 ms) and have smaller amplitudes than the first series of peaks. For example, the first late reflection 226a may correspond to a fourth peak of the microphone audio data (e.g., 70 ms)."; Here, Mansour is seen as disclosing early reflections as happening in the range of 10 ms-50 ms, and late reflections as happening in the range of 50 ms-250 ms. Therefore, it would be obvious to split the impulse response at a time in a range of at least 20 ms to up to 80 ms.).
Bryan, Isik, Davidson, and Mansour are analogous arts because they each belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan, as modified by the convolutional neural network of Isik and the binaural room impulse response method of Davidson, to incorporate the teachings of Mansour to use a predetermined range of about 30 ms-80 ms. The predetermined range is typical for acoustic impulse responses (Mansour, Col. 9, lines 33-51). By using a typical range to randomly split an impulse response, the early and late portions of the response will be close to that of real responses.
Claim(s) 32-33 and 35-38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bryan, in view of Isik, as applied to claims 21, 25-31, 34, and 39-40 above, and further in view of Kupryjanow et al. (US Pat. Pub. No. 2019/0043491 A1 hereinafter Kupryjanow).
Regarding claim 32, the rejection of claim 31 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. However, Bryan, in view of Isik, fails to expressly recite wherein the test audio signal is a live-captured audio signal.
Kupryjanow teaches wherein the test audio signal is a live-captured audio signal (Kupryjanow, [0019]: "The system or product is configured to perform pre-processing of far-field speech using deep-learning based time-frequency mask estimation and beamforming. In accordance with an embodiment, a methodology to implement these techniques includes performing de-reverberation processing on signals received from an array of microphones, the signals comprising speech and noise.").
Bryan, Isik, and Kupryjanow are analogous arts because they each belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan, as modified by the convolutional neural network of Isik, to incorporate the teachings of Kupryjanow to obtain a specific type of audio signal from a specific real world environment. This allows the system to be focused on improving a specific real world scenario for audio processing (Kupryjanow, [0002]). This ensures that the system can be optimized for a specific purpose.
Regarding claim 33, the rejection of claim 32 is incorporated. Bryan, in view of Isik and Kupryjanow, discloses all of the elements of the current invention as stated above. Bryan further discloses wherein the real AIR is a measured AIR measured in a physical room (Bryan, [0027]: "The early response can include a direct path arrival and early reflections imposed by the microphone-room geometry, while a late response can include information about the room volume and materials.").
Regarding claim 35, the rejection of claim 31 is incorporated. Bryan, in view of Isik, discloses all of the elements of the current invention as stated above. However, Bryan, in view of Isik, fails to expressly recite wherein the test audio signal is associated with a particular audio content type.
Kupryjanow teaches wherein the test audio signal is associated with a particular audio content type (Kupryjanow, [0019]: "The system or product is configured to perform pre-processing of far-field speech using deep-learning based time-frequency mask estimation and beamforming. In accordance with an embodiment, a methodology to implement these techniques includes performing de-reverberation processing on signals received from an array of microphones, the signals comprising speech and noise."; Here, the particular audio content type is far-field speech with noise.).
Bryan, Isik, and Kupryjanow are analogous arts because they each belong to the same field of audio processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the synthetic acoustic impulse response generation method of Bryan, as modified by the convolutional neural network of Isik, to incorporate the teachings of Kupryjanow to obtain a specific type of audio signal from a specific real world environment. This allows the system to be focused on improving a specific real world scenario for audio processing (Kupryjanow, [0002]). This ensures that the system can be optimized for a specific purpose.
Regarding claim 36, the rejection of claim 35 is incorporated. Bryan, in view of Isik and Kupryjanow, discloses all of the elements of the current invention as stated above. Kupryjanow further teaches wherein the particular audio content type comprises far-field noise (Kupryjanow, [0019]: "The system or product is configured to perform pre-processing of far-field speech using deep-learning based time-frequency mask estimation and beamforming. In accordance with an embodiment, a methodology to implement these techniques includes performing de-reverberation processing on signals received from an array of microphones, the signals comprising speech and noise."; Here, the particular audio content type is far-field speech with noise.). The same motivation for claim 35 applies equally to claim 36.
Regarding claim 37, the rejection of claim 35 is incorporated. Bryan, in view of Isik and Kupryjanow, discloses all of the elements of the current invention as stated above. Kupryjanow further teaches wherein the particular audio content type comprises audio content captured in an indoor environment (Kupryjanow, [0040]: "The reverberation filter models the acoustic echoes or reflections associated with an environment (e.g., rooms of various sizes and geometries), which may corrupt a signal captured from the far field of the microphones."; Here, Kupryjanow discloses a system that is based on audio in rooms.). The same motivation for claim 35 applies equally to claim 37.
Regarding claim 38, the rejection of claim 35 is incorporated. Bryan, in view of Isik and Kupryjanow, discloses all of the elements of the current invention as stated above. Kupryjanow further teaches further comprising obtaining a training set of a plurality of input audio signals each associated with the particular audio content type prior to generating the plurality of training samples (Kupryjanow, [0043]: "The availability of a large body of clean speech samples and a database of impulse responses and noise recordings, allows for the creation of a training data set with a large number of utterances and a great deal of variation in the type of disturbances."). The same motivation for claim 35 applies equally to claim 38.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TYLER J BECKER whose telephone number is (703)756-1271. The examiner can normally be reached M-Th, 7:15am-5:45pm PT.
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/TYLER BECKER/ Examiner, Art Unit 2657
/DANIEL C WASHBURN/ Supervisory Patent Examiner, Art Unit 2657
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