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 .
DETAILED ACTION
This office action is in response to correspondence 07/29/26 regarding application 18/858,123, in which claims 1, 2, and 6-17 were amended. Claims 1-17 are pending in the application and have been considered.
Response to Arguments
The amended title of the invention overcomes the objection for not being descriptive. The objection to the specification is withdrawn.
Applicant has amended the claims to delete the claim limitations which previously invoked interpretation under 35 U.S.C. 112(f). The claims are no longer interpreted under 35 U.S.C. 112(f).
Amended claim 17 overcomes the 35 U.S.C. 101 rejection, and so it is withdrawn. Specifically, the claim as amended is directed to a non-transitory computer-readable storage medium, which is considered to fall under the statutory category of “manufacture” and is therefore eligible.
Applicant’s arguments on pages 12-22 regarding the 35 U.S.C. 102(a)(1) and 103 rejections based on Nanaguma, Nallasamy, Yoon, Baskar, Etayo, Curivan, Bhalla, Quidilig, and Zhang have been considered but are moot in view of the new grounds for rejections based in part on the newly cited reference to Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”. Proceedings of the 8th European Conference on Speech Communication and Technology (Eurospeech 2003), September 1-4 2003, pp. 1201-1204, Geneva, Switzerland), which was NPL reference number 7 on the 10/18/2024 IDS. Goto describes text entry by voice dictation and voice commands, so that, for example, if a user says “new line” with a high pitch while dictating, it is immediately accepted as a voice command, page 1203, Section 4; this is considered a scenario where the user has already dictated some text, therefore the high pitch utterance “new line” temporally immediately follows the preceding dictated text. This is considered analogous to the description at paragraphs [0070] [0073] of Applicant’s original specification, the difference being that Goto uses “high pitch” instead of whispering. Therefore, even though the commands of Goto are based on high pitched speech instead of whispering, Goto is considered relevant to the amended claims, and new 35 U.S.C. 103 rejections based in part on Goto are made in response to Applicant’s amendments.
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 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 of this title, 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.
Claims 1, 7-9, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”. Proceedings of the 8th European Conference on Speech Communication and Technology (Eurospeech 2003), September 1-4 2003, pp. 1201-1204, Geneva, Switzerland), which was NPL reference number 7 on the 10/18/2024 IDS.
Consider claim 1, Nanaguma discloses an information processing device (voice-content control device processes voice information, [0006]) comprising:
circuitry (CPU, [0022]) configured to:
classify an uttered voice into a normal voice and a whisper on a basis of a voice feature amount (voice classifying unit analyzes voice V1 and determines the voice as a whisper or not a whisper by comparing a peak frequency to a threshold, [0039], [0040]);
recognize the whisper classified within the uttered voice (voice analyzing unit converts the voice V1 into text, [0023]); and
control processing based on a recognition result (voice content generating unit generates output sentences based on classification and intention information from the recognized whisper, [0044-0045]).
Nanaguma does not specifically mention recognizing within the uttered voice according to a temporal relation to a portion of the uttered voice including the normal voice.
Goto discloses recognizing within an uttered voice according to a temporal relation to a portion of the uttered voice including the normal voice (if a user says “new line” with a high pitch while dictating, it is immediately accepted as a voice command, page 1203, Section 4; this is considered a scenario where the user has already dictated some text, therefore the high pitch utterance “new line” temporally immediately follows the preceding dictated text).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma by recognizing the whisper classified within the uttered voice, as in Nanaguma, according to a temporal relation to a portion of the uttered voice including the normal voice as in Goto in order to make better use of nonverbal speech information intentionally controlled by a user, as suggested by Goto (Section 1, page 1201). Doing so would have led to predictable results of a more user-friendly speech interface, as suggested by Goto (Section 1, page 1201). The references cited are analogous art in the same field of speech processing.
Consider claim 16, Nanaguma discloses an information processing method (voice-content control method processes voice information, [0007]) comprising:
classifying an uttered voice into a normal voice and a whisper on a basis of a voice feature amount (voice classifying unit analyzes voice V1 and determines the voice as a whisper or not a whisper by comparing a peak frequency to a threshold, [0039], [0040]);
recognizing a whisper classified within the uttered voice (voice analyzing unit converts the voice V1 into text, [0023]); and
controlling processing based on a recognition result (voice content generating unit generates output sentences based on classification and intention information from the recognized whisper, [0044-0045]).
Goto discloses recognizing within an uttered voice according to a temporal relation to a portion of the uttered voice including the normal voice (if a user says “new line” with a high pitch while dictating, it is immediately accepted as a voice command, page 1203, Section 4; this is considered a scenario where the user has already dictated some text, therefore the high pitch utterance “new line” temporally immediately follows the preceding dictated text).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma by recognizing the whisper classified within the uttered voice, as in Nanaguma, according to a temporal relation to a portion of the uttered voice including the normal voice as in Goto for reasons similar to those for claim 1.
Consider claim 17, Nanaguma discloses a non-transtory computer-readable storage medium having embodied thereon a computer program (non-transitory storage medium storing a voice-content control program executed by a computer to process voice information, [0008]), which when executed by a computer causes the computer to execute a method, the method comprising:
classifying an uttered voice into a normal voice and a whisper on a basis of a voice feature amount (voice classifying unit analyzes voice V1 and determines the voice as a whisper or not a whisper by comparing a peak frequency to a threshold, [0039], [0040]);
recognizing a whisper classified within the uttered voice (voice analyzing unit converts the voice V1 into text, [0023]); and
controlling processing based on a recognition result (voice content generating unit generates output sentences based on classification and intention information from the recognized whisper, [0044-0045]).
Goto discloses recognizing within an uttered voice according to a temporal relation to a portion of the uttered voice including the normal voice (if a user says “new line” with a high pitch while dictating, it is immediately accepted as a voice command, page 1203, Section 4; this is considered a scenario where the user has already dictated some text, therefore the high pitch utterance “new line” temporally immediately follows the preceding dictated text).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma by recognizing the whisper classified within the uttered voice, as in Nanaguma, according to a temporal relation to a portion of the uttered voice including the normal voice as in Goto for reasons similar to those for claim 1.
Consider claim 7, Nanaguma discloses the circuitry is further configured to
recognize a normal voice, and
perform processing corresponding to a recognition result of the whisper on a recognition result of the normal voice (voice analyzing unit converts voice V1 to text and voice-content generating unit performs processing based on whether the voice was classified as a whisper or normal voice, [0023], [0024], [0039]).
Consider claim 8, Nanaguma discloses the circuitry is further configured to
execute processing of a whisper command recognized on a text obtained by converting the normal voice (voice analyzing unit converts whispered and normal voices V1 to text and voice-content generating unit performs different processing based on whether the voice was classified as a whisper or normal voice, [0023], [0024], [0039], such as processing commands to control lighting unit 14, [0061]).
Consider claim 9, Nanaguma discloses the circuitry is further configured to
execute at least one of input of a symbol or a special character for the text, selection of a text conversion candidate, deletion of the text, or line feed of the text on a basis of the whisper command (voice-content generating unit generates either of candidates “Yes, the processing has been accepted”, or “Yes” based on classification of the input voice V1 [0060], which are converted into voice data and output, [0061]).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003) in further view of Nallasamy et al. (US 20160358600 A1).
Consider claim 2, Nanaguma discloses the circuitry classifies the uttered voice into a normal voice and the whisper (voice classifying unit analyzes voice V1 and determines the voice as a whisper or not a whisper by comparing a peak frequency to a threshold, [0039], [0040]), and circuitry recognizes a whisper (voice analyzing unit converts the whispered voice V1 into text, [0023]).
Nanaguma and Goto do not specifically mention a first learned neural network and a second learned neural network.
Nallasamy discloses a first learned neural network and a second learned neural network (first acoustic model is a first neural network acoustic model, and second acoustic model is a second neural network acoustic model, [0256], adapted to speakers by training, [0247]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto by utilizing a first learned neural network and a second learned neural network in order to better represent the characteristics of the speakers voice in the acoustic model training data, as suggested by Nallasamy ([0003]). Doing so would have led to predictable results of improved speech recognition accuracy, as suggested by Nallasamy ([0003]). The references cited are analogous art in the same field of speech recognition.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Nallasamy et al. (US 20160358600 A1), in further view of Yoon et al. (“HuBERT-EE: Early Exiting HuBERT for Efficient Speech Recognition”. arXiv:2204.06328v1 [cs.CL] 13 Apr 2022, which was already listed on Applicant’s 10/18/24 IDS).
Consider claim 3, Nanaguma and Goto do not, but Nallasamy discloses a second learned neural network (second acoustic model is a second neural network acoustic model, [0256], adapted to speakers by training, [0247]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto by including a second learned neural network for reasons similar to those for claim 2.
Nanaguma, Goto, and Nallasamy do not specifically mention the second learned neural network includes wave2vec2.0 or HuBERT.
Yoon discloses a learned neural network includes wave2vec2.0 or HuBERT (HuBERT, , Figure 1, page 2; the examiner notes the claim language requiring wave2vec2.0 or HuBERT in the alternative).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma, Goto, and Nallasamy such that the second learned neural network includes wave2vec2.0 or HuBERT in order to increase recognition efficiency, as suggested by Yoon (page 1, introduction). The references cited are analogous art in the same field of speech recognition.
Claims 4-6 are rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in view of Nallasamy et al. (US 20160358600 A1), in further view of Baskar et al. (“Speaker adaptation for Wav2vec2 based dysarthric ASR”. arXiv:2204.00770v1 [cs.SD] 2 Apr 2022).
Consider claim 4, Nanaguma discloses whispering (voice classifying unit analyzes voice V1 and determines the voice as a whisper, [0039], [0040]).
Nanaguma and Goto do not specifically mention the second learned neural network is pre-trained.
Nallasamy discloses a second learned neural network is pre-trained (second acoustic model is a second neural network acoustic model, [0256], adapted to speakers by training, [0247]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that the second learned neural network is pre-trained for reasons similar to those for claim 2.
Nanaguma, Goto, and Nallasamy do not specifically mention pretraining with a normal voice corpus and then fine tuning by whispering is performed.
Baskar discloses pretraining with a normal voice corpus and then fine tuning is performed (pre-training and then finetuning with the wav2vec2 adapter, pages 2-3, Section 3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma, Goto, and Nallasamy by pretraining with a normal voice corpus and then fine tuning using the whispering of Nanaguma in order to improve accuracy of ASR for dysarthric speech, as suggested by Baskar (page 1, Section 1). The references cited are analogous art in the same field of speech recognition.
Consider claim 5, Nanaguma discloses whispering (voice classifying unit analyzes voice V1 and determines the voice as a whisper, [0039], [0040]).
Nanaguma, Goto, and Nallasamy do not specifically mention the fine tuning includes first-stage fine tuning using a general-purpose corpus and second-stage fine tuning using a database for each user.
Baskar discloses the fine tuning includes first-stage fine tuning using a general-purpose corpus and second-stage fine tuning using a database for each user (two-stages of fine tuning to the general dysarthric speech and to speaker dependent data, Section 3.2.3, Section 4, pages 2-3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma, Goto, and Nallasamy such that the fine tuning includes first-stage fine tuning using a general-purpose corpus as in Baskar of the whispers in Nanaguma, and second-stage fine tuning using a database for each user as in Baskar of the whispers in Nanaguma for reasons similar to those for claim 4.
Consider claim 6, Nanaguma and Goto do not, but Nallasamy discloses the second learned neural network includes a layer, and the first learned neural network is configured to share the layer with the second learned neural network (first and second acoustic model NNs share a same layer, [0256]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that the second learned neural network includes a layer, and the first learned neural network is configured to share the layer with the second learned neural network for reasons similar to those for claim 4.
Nanaguma, Goto, and Nallasamy do not specifically mention a feature extraction layer and a transformer layer.
Baskar discloses a feature extraction layer and a transformer layer (Wave2vec2 CNN feature extractor and transformer context encoder, Figure 1, page 2).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma, Goto, and Nallasamy such that the second learned neural network of Nallasamy includes a feature extraction layer and transformer layer as in Baskar, and the first learned neural network is configured to share the feature extraction layer with the second learned neural network for reasons similar to those for claim 4.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Etayo et al. (US 11848019 B2).
Consider claim 12, Nanaguma and Goto do not, but Etayo discloses the circuitry is further configured to remove a voice classified as a whisper from an original uttered voice and transmit the uttered voice from which the voice classified as the whisper has been removed to an external device (filtering out portions of the audio classified as whispered speech before transmitting the audio signal, Col 11 lines 17-31).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that the circuitry is further configured to remove a voice classified as a whisper from an original uttered voice and transmit the uttered voice from which the voice classified as the whisper has been removed to an external device in order to prevent the audience from hearing private speech, predictably improving the audience experience, as suggested by Etayo (Col 1 lines 37-49). The references cited are analogous art in the same field of speech processing.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Etayo et al. (US 11848019 B2), in further view of Currivan et al. (US 20100202689).
Consider claim 13, Nanaguma and Goto do not, but Etayo discloses the circuitry is further configured to perform processing of a section classified as a whisper (filtering out portions of the audio classified as whispered speech before transmitting the audio signal, Col 11 lines 17-31).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that the circuitry is further configured to perform processing of a section classified as a whisper for reasons similar to those for claim 12.
Nanaguma, Goto, and Etayo do not specifically mention replacing a lip portion of a video of a speaker with a video in which the speaker is not uttering.
Currivan discloses replacing a lip portion of a video of a speaker with a video in which the speaker is not uttering (a person’s lips may be replaced using the object based video segmentation, which replaces the lips of the speaker with those of an avatar, [0014]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma, Goto, and Etayo by replacing a lip portion of a video of a speaker with a video in which the speaker is not uttering in order to avoid a less than desirable appearance from being transmitted by the user, as suggested by Currivan ([0004]). The references cited are analogous art in the same field of speech processing.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Currivan et al. (US 20100202689).
Consider claim 14, Nanaguma discloses a voice classified as a normal voice by the recognition unit and a voice classified as a whisper by the recognition unit (voice classifying unit analyzes voice V1 and determines the voice as a whisper or not a whisper by comparing a peak frequency to a threshold, [0039], [0040]).
Nanaguma and Goto do not specifically mention generating a voice of a first avatar and generating a voice of a second avatar.
Currivan discloses generating a voice of a first avatar and generating a voice of a second avatar (tracking and voice algorithms generate avatars with voices corresponding to the user’s speech, [0018], Fig 2B).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto by generating a voice of a first avatar and generating a voice of a second avatar in order to enhance user communications, as suggested by Currivan ([0004]). The references cited are analogous art in the same field of speech processing.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Bhalla et al. (US 20210027802).
Consider claim 15, Nanaguma and Goto do not, but Currivan discloses a microphone and a speaker mounted on a mask worn by a speaker (glasses and headset include microphone that detects whisper, [0013], and speaker inherent in headset device or earbuds, [0015]; these mask parts of the face and ears); and an amplifier that amplifies a voice signal classified as a normal voice, wherein the voice signal amplified by the amplifier is output from the speaker (audio classified as a whispered is reproduced at a second decibel level greater than a first decibel level, i.e. amplified, [0048-0050]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto by including a microphone and a speaker mounted on a mask worn by a speaker; and an amplifier that amplifies a voice signal classified as a normal voice, wherein the voice signal amplified by the amplifier is output from the speaker in order to protect private information, as suggested by Bhalla ([0003]). The references cited are analogous art in the same field of speech processing.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Quidilig et al. (US 20120004910 A1).
Consider claim 10, Nanaguma discloses a whisper (voice classifying unit analyzes voice V1 and determines the voice as a whisper, [0039], [0040]).
Nanaguma and Goto do not specifically mention a plurality of characters is uttered in a normal voice and then a predetermined command is uttered in a whisper, the circuitry recognizes that the whisper is a command to instruct to input a spelling of a word, and the circuitry is further configured to generate a word by concatenating the plurality of characters in an order of the utterance.
Quidilig discloses a plurality of characters is uttered in a normal voice and then a predetermined command is uttered, the circuitry recognizes a command to instruct to input a spelling of a word, and the circuitry generates a word by concatenating the plurality of characters in an order of the utterance (“spell that” command, Table 3m, [0069]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that when a plurality of characters is uttered in a normal voice and then a predetermined command is uttered, the circuitry recognizes a command to instruct to input a spelling of a word, and the circuitry generates a word by concatenating the plurality of characters in an order of the utterance in order to correct errors or mistakes in the speech to text process, as suggested by Quidilig ([0068]). The references cited are analogous art in the same field of speech recognition.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Nanaguma (US 20190279611 A1) in view of Goto et al. (“Speech Shift: Direct Speech-Input-Mode Switching through Intentional Control of Voice Pitch”, 2003), in further view of Zhang et al. (“Voicemoji: Emoji Entry Using Voice for Visually Impaired People”. CHI ’21, May 8–13, 2021, Yokohama, Japan).
Consider claim 10, Nanaguma discloses recognizing a whisper command (voice classifying unit analyzes voice V1 and determines the voice as a whisper, [0039], [0040], such as a command to control lighting unit 14, [0061]).
Nanaguma and Goto do not specifically mention in response to the recognition unit recognizing a command instructing emoji input, the control unit converts a normal voice immediately before into an emoji.
Zhang discloses in response to the recognition unit recognizing a command instructing emoji input, the control unit converts a normal voice immediately before into an emoji (recognizing “insert ____ emoji”, and converting the word “raining” immediately before “emoji” into the raining emoji, Figure 1, page 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Nanaguma and Goto such that in response to the recognition unit recognizing a whisper command as in Nanaguma instructing emoji input as in Zhang, the control unit converts a normal voice immediately before the whisper of Nanaguma into an emoji of Zhang in order to assist people with visual impairments to input emojis, as suggested by Zhang (Abstract, page 1). The references cited are analogous art in the same field of speech recognition.
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 Jesse Pullias whose telephone number is 571/270-5135. The examiner can normally be reached on M-F 8:00 AM - 4:30 PM. The examiner’s fax number is 571/270-6135.
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, Andrew Flanders can be reached on 571/272-7516.
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.
/Jesse S Pullias/
Primary Examiner, Art Unit 2655 09/01/26
Prosecution Insights