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 Arguments
Applicant's amendments filed on 9/4/2025 overcome all the rejections set forth in the previous Office Action, except the rejection of claims 8-11 under 35 USC §112 (b) or 35 USC §112 (pre-AIA ), second paragraph. After initial review of the amendments and remarks, examiner determined that the above 112 issue with claims 8-11 is the only issue for the claimed invention and initiated an interview to expedite the prosecution. See interview summary for details. However, after further review and consideration, examiner finds that applicant's arguments filed 9/4/2025 are not persuasive. The examiner has thoroughly reviewed applicants' arguments but firmly believes that the cited references reasonably and properly met the claim limitations as previously filed, and as to all the arguments on the amended claim limitations the responses will be detailed in the rejection section below. Furthermore, the amendments necessitate new grounds of rejections as to be detailed below.
On pages 12-14 of the Remarks, regarding the amended claim 1 and particularly new limitations of the amended claim 1, which are similar to those of the previous claim 15, applicant argues that “Chen fails to disclose or suggest not only "determining a target region in the target key video frame," but also "extracting the corresponding high-frequency word from the high-frequency word cache module for performing speech-to-text conversion,"” “Yu does not disclose or suggest "determining, by processing the target content, a high-frequency word of a target video to which the target key video frame belongs, and storing the high- frequency word in a high-frequency word cache module" and "extracting the corresponding high-frequency word from the high-frequency word cache module for performing speech-to-text conversion,"” and “Deng teaches neither the limitations of determining the target region in the target video frame to further determine the high-frequency word in the target video by processing the target content of the target region, nor the limitations of using the high-frequency word stored in the high-frequency word cache module for subsequent speech-to-text conversion. Thus, Deng discloses a completely different word extraction process compared with that of the present application under a different scenario.” The requirements for a proper response to a rejection may be found in 37 CFR 1.111(b) and MPEP § 714.02; see also 707.07(a). The remarks do not provide any specific reasons as to why either the findings of fact or the legal conclusion of obviousness is allegedly in error. Thus, the remarks in response to the obviousness rejection do not comply with 37 CFR 1.111(b) and MPEP § 714.02. First of all, in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). For example, Chen and Yu are not relied upon to teach claim limitations alleged by applicant as not disclosed by them, respectively, and Deng is not relied upon to teach “the limitations of determining the target region in the target video frame to further determine the high-frequency word in the target video by processing the target content of the target region” as asserted by applicant. Secondly, the remarks do not provide any specific reasons as to why Deng fails to teach “the limitations of using the high-frequency word stored in the high-frequency word cache module for subsequent speech-to-text conversion” in light of cited Figs 1-5 and particularly Figs. 1 and 4. However, Applicant’s reply is considered to be a bona fide attempt at a response and is being accepted as a complete response.
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 8-11 are 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 pre-AIA the applicant regards as the invention.
Claim 8 recites “foreground confidence information and confidence information of the text box region.” However, it is unclear what this claim limitation means. In particular, it is unclear what it means by “foreground confidence information”. It is also unclear what it means by “confidence information of the text box region”. The claim 8 is indefinite since the metes and bounds of the claim cannot be defined due to the lack of clarify for the claimed invention. During the interview on 9/25/2025, examiner proposed to amend claim 8 in similar way as claim 6 to clarify the similar claim limitations. For the rest of this office action, to advance the prosecution, examiner will interpret the above limitations in claim 8 similarly as those similar limitations in the amended claim 6.
Claims 9-11 depend on claim 9 and are therefore rejected for the same reason as for claim 8.
References Cited in Prior Art Rejections
The following references are cited in the prior art rejections set forth below and are referred to as noted:
Chen et al., US 20180151199 A1, published on 2018-05-31, hereinafter Chen.
Yu et al., US 20020126203 A1, published on 2002-09-12, hereinafter Yu.
Deng, CN 108984529 A, published on 2018-12-11 (machine translation), hereinafter Deng.
Shi et al., US 20200394414 A1, published on 2020-12-17, hereinafter Shi.
Ren, CN 111274985 A, published on 2020-06-12 (machine translation), hereinafter Ren.
Grant, US 20130328902 A1, published on 2013-12-12, hereinafter Grant.
Lin et al., US 20220254143 A1, published on 2022-08-11, hereinafter Lin.
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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1, 3-4, 12, 17-18 and 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, in view of Yu, and further in view of Deng.
Regarding claim 1, Chen discloses a hot word extraction method, (Chen: [0035-0036]) comprising:
determining a target key video frame; (Chen: “[0035] … extract the at least one keyframe from the target video”.)
determining target content in the target key video frame Chen: “[0036] … detect whether each of the at least one keyframe includes content within a set of target content.”)
determining, by processing the target content, a high-frequency word of a target video to which the target key video frame belongs, and storing the high-frequency word in a high-frequency word cache module; (Chen: “[0036] … generate a label indicating the certain content for the keyframe.” “[0053] The target label is a label matching the keyword.” Either a label or a target label is interpreted as the claimed “high-frequency word”. Storing is implied by “each label recorded” in [0052, 0055].) and
Chen does not disclose explicitly determining a target region in the target key video frame, and determining target content in the target key video frame based on the target region. However Yu teaches, in an analogous art of video processing and more specifically video summarization, determining a target region in a video frame and determining target content in the video frame based on the target region. (Yu: video frames in Figs. 1 and 4, step 11 in Fig. 3, text area in Figs. 4-5. “[0046] … Candidate areas are extracted… Among the candidate areas, an area is extracted as a text area, which has an aspect ratio satisfying that of a text”. “[0049] … If the size and position of the extracted text areas have similar and the difference between edge histogram values of the text areas is smaller than a predetermined threshold valve, the currently extracted text area is judged as the same as the previously extracted text area.” The disclosed “text” is interpreted as the claimed “target content”.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen’s disclosure with Yu’s teachings by combining the hot word extraction method (from Chen) with the technique of determining a target region and target content in a video frame (from Yu) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen and the technique of determining a target region and target content in the video frame would continue to function as taught by Yu. In fact, the inclusion of Yu's technique of determining a target region and target content in the video frame would provide a practical and/or alternative implementation of the hot word extraction method and would enable a better and more effective hot word extraction method by limiting further processing to extracted areas rather than the entire image and thus saving processing resources.
Chen {modified by Yu} does not disclose explicitly Deng teaches, in an analogous art of determining high-frequency words based on voice or speech recognition, storing the high-frequency word in a high-frequency word cache module; in response to detecting triggering of a speech-to-text operation, collecting to-be-converted speech information, and in response to the to-be-converted speech information comprising a high-frequency word stored in the high-frequency word cache module, extracting the corresponding high-frequency word from the high-frequency word cache module for performing speech-to-text conversion. (Deng: Figs. 1-5, pages 3 and 5-9. For example, storing hot or high-frequency words is implied by “in step S110, real-time response to detecting a hearing system user to speech recognition in the character modification operation, finding word and added to the hot word. … step S110 is the hot word constructing step.” (page 5) And triggering is implied by “step S120, the court trial voice real time identification.” (page 6) Furthermore, “collecting” and “in response to .., extracting …” are implied by “step S130, the real time for the identified word to word matching operation, and word replacement” and steps in Fig. 4 as discussed in detail in pages 6-7.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen {modified by Yu}’s disclosure with Deng’s teachings by combining the hot word extraction method (from Chen {modified by Yu}) with the technique of collecting speech information in response to detecting triggering of a speech-to-text operation and extracting a high-frequency word in the speech information from stored high-frequency words in response to the speech information comprising the high-frequency word for performing speech-to-text conversion (from Deng) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen {modified by Yu} and the technique of collecting speech information in response to detecting triggering of a speech-to-text operation and extracting a high-frequency word in the speech information from stored high-frequency words in response to the speech information comprising the high-frequency word for performing speech-to-text conversion would continue to function as taught by Deng. In fact, the inclusion of Deng's technique would provide a practical and alternative implementation of the hot word extraction method and as a result would enable a better and more flexible hot word extraction method due to additional information made available for the high-frequency word extraction and the alternative implementation enabled by Deng’s technique. Furthermore, if applicant disagrees with examiner’s interpretation that Chen discloses the claimed “high-frequency word”, the combination of Chen, Yu and Deng teaches the claimed “high-frequency word” as discussed above regarding Deng’s explicit disclosure of “hot word”. (Deng: Figs. 1-5, pages 3 and 5-9.)
Therefore, it would have been obvious to combine Chen with Yu and Deng to obtain the invention as specified in claim 1.
Regarding claim 3, Chen {modified by Yu and Deng} discloses the method according to claim 1, further comprising: generating the target video based on a real-time interactive interface to determine the target key video frame from the target video. (Chen: Figs. 3-7, [0035]. Yu: Figs. 1 and 4)
Regarding claim 4, Chen {modified by Yu and Deng} discloses the method according to claim 3, further comprising: in response to detecting a control triggering screen sharing, desktop sharing, or target video playing, collecting a to-be-processed video frame in the target video to determine the target key video frame from the to-be-processed video frame. (Chen: Figs. 3-7, [0031-0032, 0034-0035]. Yu: Figs. 1 and 4.)
Regarding claim 12, Chen {modified by Yu and Deng} discloses the method according to claim 1, wherein the target region comprises a target text line region, and determining the target content in the target key video frame based on the target region comprises: extracting a character in the target text line region based on an image recognition technology, and taking the text as the target content. (Chen: [0036, 0038]. Yu: Figs. 4-8)
The device (Chen: Fig. 10, [0104]) claims 17 and 20-21 are similarly rejected as the method claims 1 and 3-4.
The CRM (Chen: Fig. 10, [0105]) claim 18 is similarly rejected as the method claim 1.
Claims 2 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Chen {modified by Yu and Deng} as applied to claims 1 and 17, respectively, and further in view of Shi.
Regarding claim 2, which depend on claim 1, Chen {modified by Yu and Deng} does not disclose explicitly but Shi teaches, in an analogous art of video processing for keyframe determination or scheduling, wherein determining the target key video frame comprises: acquiring a current video frame and at least one historical key video frame before the current video frame; determining a similarity value between the current video frame and each historical key video frame among the at least one historical key video frame; and in response to the similarity value being less than or equal to a preset similarity threshold, generating the target key video frame based on the current video frame. (Shi: [0091])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen {modified by Yu and Deng}’s disclosure with Shi’s teachings by combining the hot word extraction method (from Chen {modified by Yu and Deng}) with the technique of determining the target key video frame (from Shi) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen {modified by Yu and Deng} and the technique of determining the target key video frame would continue to function as taught by Shi. In fact, the inclusion of Shi's technique of determining the target key video frame would provide a practical and/or alternative implementation of the hot word extraction method and thus would enable a better and more effective hot word extraction method.
Therefore, it would have been obvious to combine Chen {modified by Yu and Deng} with Shi to obtain the invention as specified in claim 2.
The device (Chen: Fig. 10, [0104]) claim 19 is similarly rejected as the method claim 2.
Claims 5, 8-11, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Chen {modified by Yu and Deng} as applied to claims 1 and 17, and further in view of Ren.
Regarding claim 5, Chen {modified by Yu and Deng} discloses the method according to claim 1, wherein determining the target region in the target key video frame comprises: Yu: “[0046]… Candidate areas are extracted based upon a property that horizontal and vertical edge histograms are concentrically appeared and information that the edge histogram is repeatedly varied in size according to a space of the character.”)
Chen {modified by Yu and Deng} does not disclose explicitly inputting the target key video frame into a pre-trained image feature extraction model to obtain an output result, which, however, is well known and commonly practiced in the art of image or video frame processing for image feature extraction as evidenced by the prior art of Ren. (Ren: Fig. 1, paragraphs 4-6 on page 5)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen {modified by Yu and Deng}’s disclosure with Ren’s teachings by combining the hot word extraction method (from Chen {modified by Yu and Deng}) with the technique of inputting the target key video frame into a pre-trained image feature extraction model to obtain an output result (from Ren) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen {modified by Yu and Deng} and the technique of inputting the target key video frame into a pre-trained image feature extraction model to obtain an output result would continue to function as taught by Ren. In fact, the inclusion of Ren's technique of inputting the target key video frame into a pre-trained image feature extraction model to obtain an output result would provide a practical implementation of the hot word extraction method and thus would enable a better and more effective hot word extraction method.
Therefore, it would have been obvious to combine Chen {modified by Yu and Deng} with Ren to obtain the invention as specified in claim 5.
Regarding claim 8, Chen {modified by Yu and Deng and Ren} discloses the method according to claim 5, wherein the at least one target region comprises a target text box region, and determining the at least one target region in the target key video frame based on the output result comprises: determining association information of the target key video frame based on the output result; and determining the target text box region in the target key video frame based on the association information, wherein the association information comprises position coordinate information of a text box region in the target key video frame, foreground confidence information and confidence information of the text box region. (Yu: step 11 in Fig. 3, text box area in Figs. 4-8. The disclosed “an aspect ratio satisfying that of a text” and “a small amount of motion and a color with brightness highly different from that of the background” [0046] are interpreted as confidence information of a text and foreground confidence information, respectively. “[0049] … the size and position of the extracted text areas” is interpreted as the “association information”.) (Ren: Fig. 1, paragraphs 4-6 on page 5)
Regarding claim 9, Chen {modified by Yu and Deng and Ren} discloses the method according to claim 8, wherein determining the at least one target region in the target key video frame comprises: processing the target key video frame based on a text line extraction model, and outputting a first feature matrix corresponding to the target key video frame; determining, based on the first feature matrix, at least one discrete text character region comprising character content and in the target key video frame, wherein the first feature matrix comprises coordinate information of a discrete text character region of the at least one discrete text character region and foreground confidence information; determining at least one to-be-determined text line region in the discrete text character region according to preset text character line spacing; and determining a target text line region in the target key video frame based on the target text box region and the at least one to-be-determined text line region. (Yu: step 11 in Fig. 3, text box area in Figs. 4-8. Ren: Fig. 1, paragraphs 4-6 on page 5)
Regarding claim 10, Chen {modified by Yu and Deng and Ren} discloses the method according to claim 9, wherein determining the target text line region in the target key video frame based on the target text box region and the at least one to-be-determined text line region comprises: determining the target text line region from all of the at least one to-be-determined text line region based on the at least one to-be-determined text line region in the target text box region and an image resolution of a to-be-determined text line region of the at least one to-be- determined text line region. (Yu: step 11 in Fig. 3, text box area in Figs. 4-8. [0046, 0049]. Ren: Fig. 1, paragraphs 4-6 on page 5. This is at least self-evident when “the at least one to-be-determined text line region” has only one to-be-determined text line region.)
Regarding claim 11, Chen {modified by Yu and Deng and Ren} discloses the method according to claim 9, further comprising determining the text line extraction model, wherein determining the text line extraction model comprises: acquiring training sample data, wherein the at least one discrete text character region in the video frame, coordinates of a text character region, and confidence of the text character region are pre-marked in the training sample data; and the text character region is a discrete region segmented from a continuous text line region; training a to-be-trained text line extraction model based on the training sample data to acquire a training feature matrix corresponding to the training sample data; performing processing based on a loss function, a standard feature matrix in the training sample data, and the training feature matrix, and correcting a model parameter in the to-be- trained text line extraction model based on a processing result; and taking a loss function convergence as a training target to acquire the text line extraction model through training. (Ren: Fig. 5 and related paragraphs. )
The reasoning and motivation to combine are similar to those of claim 5.
Claim 22 is similarly rejected as claim 5.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Chen {modified by Yu and Deng and Ren} as applied to claim 5 and further in view of Grant.
Regarding claim 6, Chen {modified by Yu and Deng and Ren} discloses the method according to claim 5, wherein the at least one target region comprises a Yu: video frames in Figs. 1 and 4, step 11 in Fig. 3, text area in Figs. 4-8. The disclosed “an aspect ratio satisfying that of a text” and “a small amount of motion and a color with brightness highly different from that of the background” [0046] are interpreted as confidence information of a text and foreground confidence information, respectively. “[0049] … the size and position of the extracted text areas” is interpreted as the “association information”.) (Ren: the image feature extraction module 4 in Fig. 1, 3rd paragraph from bottom of page 5)
Although the text area as disclosed by Yu and shown in Figs. 4-8 of Yu may well include an address bar region, Yu does not explicitly disclose it. However, Grant teaches, in an analogous art of real-time video image processing, an address bar region as a text area. (Grant: [0046])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen {modified by Yu and Deng and Ren}’s disclosure with Grant’s teachings by combining the hot word extraction method (from Chen {modified by Yu and Deng and Ren}) with the technique of having an address bar region as a text region (from Grant) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen {modified by Yu and Deng and Ren} and the technique of having an address bar region as a text region would continue to function as taught by Grant. In fact, the inclusion of Grant's technique of having an address bar region as a text region would provide a practical implementation of the hot word extraction method in a case where a text region includes an address bar region or online search region and would broaden the application of the hot word extraction method.
Therefore, it would have been obvious to combine Chen {modified by Yu and Deng and Ren} with Grant to obtain the invention as specified in claim 6.
Regarding claim 7, Chen {modified by Yu and Deng and Ren and Grant} discloses the method according to claim 6, wherein determining the target content in the target key video frame based on the target region comprises: acquiring a target uniform resource locator (URL) address from the target address bar region to acquire the target content based on the target URL address. (Yu: Figs. 4-8, [0046]. Grant: [0046])
Claims 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Chen {modified by Yu and Deng} as applied to claim 1 and further in view of Lin.
Regarding claims 13-14, which depend on claim 1, Chen {modified by Yu and Deng} does not disclose explicitly but Lin teaches, in an analogous art of image processing for finding keyword, wherein determining, by processing the target content, the high-frequency word of the target video to which the target key video frame belongs comprises: eliminating a preset character in the target content to acquire to-be-processed content; and performing word segmentation on the to-be-processed content to acquire at least one to- be-processed word, and acquiring, based on the at least one to-be-processed word, the high-frequency word of the video to which the target key video frame belongs, wherein acquiring, based on the at least one to-be-processed word, the high-frequency word of the video to which the target key video frame belongs comprises: determining an average word vector corresponding to all of the at least one to-be- processed word; for each to-be-processed word of the at least one to-be-processed word, determining a distance value between each word vector of the each to-be-processed word and the average word vector; and determining that a to-be-processed word corresponding to a word vector with a smallest distance value from the average word vector serves as a target to-be-processed word, and generating the high-frequency word of the target key video frame based on the target to-be-processed word, wherein the to-be-processed word is among the at least one to-be-processed word. (Lin: Figs. 2-5, [0054, 0133, 0135]. “[0133] … determining an average value of word vectors of the plurality of words as a center vector, determining a distance between each word vector in the word vectors and the center vector, and determining a word corresponding to a word vector having a smallest distance as the key word meeting the reference condition.” “[0135] … However, in addition to words used for describing the target item, the plurality of words may include a few interference words and words describing other items. Therefore, to filter out words describing the target item from the plurality of words, a center vector corresponding to the plurality of words may be further determined according to the word vectors of the plurality of words, and a word whose word vector is closer to the center vector indicates that the word describes the target item more accurately.” The keyword from Lin is interpreted as the high-frequency word claimed.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chen {modified by Yu and Deng}’s disclosure with Lin’s teachings by combining the hot word extraction method (from Chen {modified by Yu and Deng}) with the technique of determining the high-frequency word based on a distance from an average of word vectors (from Lin) to yield no more than predictable use of prior art elements according to their established functions since all the claimed elements, which are taught by prior art references, would continue to operate in the same manner, particularly, the hot word extraction method would still work in the way according to Chen {modified by Yu and Deng} and the technique of determining the high-frequency word based on a distance from an average of word vectors would continue to function as taught by Lin. In fact, the inclusion of Lin's technique of determining the high-frequency word based on a distance from an average of word vectors would provide a practical and an alternative implementation of the hot word extraction method and thus would enable a better and more flexible hot word extraction method.
Therefore, it would have been obvious to combine Chen {modified by Yu and Deng} with Lin to obtain the invention as specified in claims 13-14.
Conclusion
THIS ACTION IS MADE FINAL. 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 extension fee 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 FENG NIU whose telephone number is (571)272-9592. The examiner can normally be reached on Monday - Friday, 8am-5pm PT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chan Park can be reached on (571) 272-7409. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FENG NIU/Primary Examiner, Art Unit 2669
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