DETAILED ACTION
Notice of 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 .
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 1-3, 5-7, 10, 15-17,19-21, 24 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Bharath et al. ( US 20180225721 A1), hereinafter referenced as Bharath, in view of Wu et al. ( WO 2023241415 A1), hereinafter referenced as Wu.
Regarding Claim 1, Bharath teaches a method for automatically generating a target media, the method comprises: receiving, by a processing unit, at least one of a media content data, an entity data, and one or more target audience parameters ( Bharath: Para.[0027],[0033]- [0035], Figs. 1, 2, The components of the content server 130 include a content store 131, a content selection server 133, an ad construction server 135. The ad construction server 135 receives user information text 220 which is derived from user information such as user profile data, the news text 230 is text derived from an informational notice (e.g., a news report, scores from a sports game). Para.[0093], Fig. 9, processor 902);
[generating,] by the processing unit, a background music based on at least one of the media content data, the entity data, the one or more target audience parameters, and a transcript ( Bharath: Para.[0042], Fig. 3, the ad audio generator 330 may combine the audio version of the personalized text ad with background music or sound effects. For example, if the personalized text ad includes a traffic report, the ad audio generator 330 overlays helicopter noises over the portion of the personalized text ad containing the traffic report. Para.[0093], Fig. 9, processor 902);
generating, by the processing unit, an audio speech based on at least one of the media content data, the entity data, the one or more target audience parameters, the transcript, and the background music ( Bharath: Para.[0041], Fig. 3, The ad audio generator 330 converts a personalized text ad to an audio advertisement using a text-to-speech (TTS) algorithm. The ad audio generator 330 may use various TTS algorithms. The ad audio generator 330 generates the audio advertisement based on vocal parameters received from the ad selection server 137. Vocal parameters may specify a prepackaged voice (e.g., male or female, a silky voice, a gravelly voice) or may indicate more nuanced variables that control how the TTS algorithm synthesizes audio);
and generating automatically, by the processing unit, the target media based on at least the background music, and the audio speech ( Bharath: Para.[0073]-[0075], Fig. 6, The ad construction server 135 generates 630 personalized text ads relevant to the user of the client device 110 based on the audio content 610, selected by the content selection server 133).
Bharath, while teaching the method of claim 1, fails to explicitly teach the claimed, generating, by the processing unit, a background music based on at least one of the media content data, the entity data, the one or more target audience parameters, and a transcript.
However, Wu does teach the claimed, generating, by the processing unit, a background music based on at least one of the media content data, the entity data, the one or more target audience parameters, and a transcript ( Wu: Page 4, Para.[9],[10], Page 5, Para.[1]-[3], Fig. 1, chapters of the e-book may be provided to the soundtrack system 110, which may be implemented on a single device or a cluster of multiple devices, for example, on a cloud-based server as a cloud service that generates background music from text and is used to generate background music for the text . Each chapter of the e-book may include several plots. Different plots may contain different emotional information, such as tension, warmth, threat, etc., so appropriate music types need to be selected to match. The soundtrack system 110 is designed to include a plot division module 112, a plot classification module 114, and a music determination module 116. The plot division module 112 uses the paragraphs of the text 101 as the division granularity to divide the text into several plot units. The plot classification model 114 determines a category for each divided plot unit, and the category reflects the emotional information contained in the plot. The music determination module 116 determines music that matches the plot unit according to the category of the plot unit, selects a piece of music with the same emotional information from the music library, or generates a piece of such music).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Wu’s teaching of generating background music of a text, and an electronic device, into the system and method of dynamically generating audio in advertisements, taught by Bharath, because, by determining music matching at least one episode unit based on the episode category, the plot in the text can be automatically and accurately determined and matching background music selected for the plot, thereby improving the effect of audiobooks.(Wu, Page. 2, Para.[5],[6]).
Claim 15 is system claim comprises: a processing unit; and a storage unit connected to at least the processing unit, wherein the processing unit is configured to ( Bharath: Para.[0093], Fig. 9, processor 902, storage device 908), perform the steps in method claim 1 above and as such, claim 15, is similar in scope and content to claim 1 and therefore, claim 15 is rejected under similar rationale as presented against claim 1 above.
Claim 29 is non-transitory computer readable storage medium claim storing one or more instructions for automatically generating a target media, the instructions include executable code which, when executed by one or more units of a system, causes a processing unit of the system to ( Bharath: Para.[0093],[0094], Fig. 9, the storage device 908 is a non-transitory computer-readable storage medium such as a hard drive, compact disk read-only memory (CD-ROM), DVD, or a solid state memory device. The memory 906 holds instructions and data used by the processor 902) perform the steps in method claim 1 above and as such, claim 15, is similar in scope and content to claim 1 and therefore, claim 15 is rejected under similar rationale as presented against claim 1 above.
Regarding Claim 2, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the target media is one of an audio advertisement (ad) and an audio-visual ad ( Bharat: Para. [0075],[0076],Fig. 6, The ad construction server 135 generates 630 personalized text ads relevant to the user of the client device. The advertisement may be an audio version of the personalized text ad generated by the ad selection server 137 or may be a text advertisement and vocal parameters to configure a TTS algorithm on the client device 110 to generate an audio version of the personalized text ad. The client device 110 plays 650 the audio version of the personalized text ad).
Claim 16 is system claim performing the steps in method claim 2 above and as such, claim 16, is similar in scope and content to claim 2 and therefore, claim 16 is rejected under similar rationale as presented against claim 2 above.
Regarding Claim 3, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the media content data comprises at least one of an advertisement data and one or more input parameters ( Bharat: Para.[0055], [0058],Fig. 4, The ad text assembler 450 of ad construction server 135, takes as input advertisement text from the ad collector 430).
Claim 17 is system claim performing the steps in method claim 3 above and as such, claim 17, is similar in scope and content to claim 3 and therefore, claim 17 is rejected under similar rationale as presented against claim 3 above.
Regarding Claim 5, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the entity data is a data related to one or more entities, and wherein each entity from the one or more entities is one of a brand entity and a product entity ( Bharat: Para.[0050], preference data may include a particular product, a particular brand).
Claim 19 is system claim performing the steps in method claim 5 above and as such, claim 19, is similar in scope and content to claim 5 and therefore, claim 19 is rejected under similar rationale as presented against claim 5 above.
Regarding Claim 6, Bharat in view of Wu teach the method as claimed in claim 5. Bharat further teaches, wherein the entity data comprises at least one of an entity name of the one or more entities, an entity description of the one or more entities, one or more keywords associated with the one or more entities, and an URL associated with the one or more entities ( Bharat: Para.[0079], the ad construction server 135 (e.g., the ad collector 430) receives advertisement text and targeting criteria from an advertiser. The advertisement text comprises a company name, a product name, or a tagline, for example. The targeting criteria specify characteristics of users in the target audience or characteristics (e.g., keywords) in news text or content text to be paired with the advertisement text).
Claim 20 is system claim performing the steps in method claim 6 above and as such, claim 20, is similar in scope and content to claim 6 and therefore, claim 20 is rejected under similar rationale as presented against claim 6 above.
Regarding Claim 7, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the one or more target audience parameters comprise at least one of a target gender parameter and a target age group parameter ( Bharat: Para.[0045],[0046], Fig. 4, the ad construction server receives user profile data, such as age. The ad construction server 135 constructs personalized text ads for a given target audience such as individuals having a certain age range).
Claim 21 is system claim performing the steps in method claim 7 above and as such, claim 21, is similar in scope and content to claim 7 and therefore, claim 21 is rejected under similar rationale as presented against claim 7 above.
Regarding Claim 10, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the audio speech is generated in one or more voice types, wherein the one or more voice types comprises at least one of a male voice type, a female voice type and a child voice type ( Bharat: Para.[0041], Vocal parameters affect the audio output synthesized by the TTS algorithm. Vocal parameters may specify a prepackaged voice such as male or female, a silky voice, a gravelly voice).
Claim 24 is system claim performing the steps in method claim 10 above and as such, claim 24, is similar in scope and content to claim 10 and therefore, claim 24 is rejected under similar rationale as presented against claim 10 above.
Claims 4 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Bharath et al. ( US 20180225721 A1), hereinafter referenced as Bharath, in view of Wu et al. ( WO 2023241415 A1), hereinafter referenced as Wu, further in view of Bittner et al. ( US 20190355372 A1), hereinafter referenced as Bittner.
Regarding Claim 4, Bharat in view of Wu teach the method as claimed in claim 3. Bharat in view of Wu fail to explicitly teach the claimed, wherein the one or more input parameters are received in a manual input, and the one or more input parameters comprise at least one of one or more media tone parameters, an input time duration parameter, and one or more action call parameters.
However, Bittner does teach the claimed, wherein the one or more input parameters are received in a manual input, and the one or more input parameters comprise at least one of one or more media tone parameters, an input time duration parameter, and one or more action call parameters ( Bittner: Para.[0114],[0115], Fig. 3D, illustrates a graphical user interface 300D that is used to render fields related to creative voiceover. Voiceover input data enables an operator the ability to write a script ( manual input) to be used as a voiceover. The input that is received by script section 326 are communicated over a network to another system that presents the script to a voiceover actor who reads the script according to the parameters input through the user interfaces. Para.[0066], [0068], Fig. 2, the input data can be provided through input interface 202 includes, for example, background media content, a script for a voiceover, a tone of a voiceover, one or more targeting parameters, one or more timing parameters. Examples of such information includes a name of a song or track identifier (ID), voiceover script ID, emotional tone and rhythm, time(s) and date(s), images, and other metadata, correspondingly).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Bittner’s teaching of automated voiceover mixing, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu, because, automated voiceover mixing for media content would personalize or localize the created advertisement and would be most effective.(Bittner, Para.[0004]-[0009]).
Claim 18 is system claim performing the steps in method claim 4 above and as such, claim 18, is similar in scope and content to claim 4 and therefore, claim 18 is rejected under similar rationale as presented against claim 4 above.
Claims 8, 9, 22 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Bharath et al. ( US 20180225721 A1), hereinafter referenced as Bharath, in view of Wu et al. ( WO 2023241415 A1), hereinafter referenced as Wu, further in view of Rose et al. ( US 20230040015 A1), hereinafter referenced as Rose.
Regarding Claim 8, Bharat in view of Wu teach the method as claimed in claim 1. Bharat in view of Wu fail to explicitly teach the claimed, wherein the transcript is generated based on at least one of the media content data, the entity data, and the one or more target audience parameters.
However, Rose does teach the claimed, wherein the transcript is generated based on at least one of the media content data, the entity data, and the one or more target audience parameters ( Rose: Para.[0037],[0038], Fig. 2A, the script generator 200 is configured to determine/generate the voiceover script 252 for conversion into corresponding synthesized voiceover speech of the voiceover advertisement based on the advertising campaign attributes 106. The advertising campaign attributes 106 of the target advertisement 104 include a landing page uniform resource locator (URL) 204. The landing page URL 204 may be any webpage with content associated with the target advertisement 104 (e.g., content associated with a company, brand, or product of the target advertisement 104)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Rose’s teaching of generating synthesized voiceover speech for a target advertisement having one or more advertising campaign attributes, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu, because, well-crafted (i.e., scripted) audio in the advertisements would have a greater effectiveness with their target audience when compared to an advertisement without audio content.(Rose, Para.[0024]-[0027]).
Claim 22 is system claim performing the steps in method claim 8 above and as such, claim 22, is similar in scope and content to claim 8 and therefore, claim 22 is rejected under similar rationale as presented against claim 8 above.
Regarding Claim 9, Bharat in view of Wu teach the method as claimed in claim 1. Bharat in view of Wu fail to explicitly teach the claimed, the method further comprises utilizing, by the processing unit, one or more artificial intelligence (Al) based language models for generating the transcript, one or more Al based text- to-audio models for generating the background music, and one or more Al based text-to-speech models for generating the audio speech.
However, Rose does teach the claimed, the method further comprises utilizing, by the processing unit, one or more artificial intelligence (Al) based language models for generating the transcript, one or more Al based text- to-audio models for generating the background music, and one or more Al based text-to-speech models for generating the audio speech ( Rose: Para.[0034], Fig.2B, The script generator 200 may implement one or more language models for automatically generating the voiceover script 252 based on the one or more advertising campaign attributes 106. In some implementations, the script generator 200 includes one or more language models trained on captions of training voiceover speech extracted from a corpus of existing advertisements (e.g., training advertisements) 208, 208a-n).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Rose’s teaching of generating synthesized voiceover speech for a target advertisement having one or more advertising campaign attributes, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu, because, well-crafted (i.e., scripted) audio in the advertisements would have a greater effectiveness with their target audience when compared to an advertisement without audio content.(Rose, Para.[0024]-[0027]).
Claim 23 is system claim performing the steps in method claim 9 above and as such, claim 23, is similar in scope and content to claim 9 and therefore, claim 23 is rejected under similar rationale as presented against claim 9 above.
Claims 11-14 and 25-28 are rejected under 35 U.S.C. 103 as being unpatentable over Bharath et al. ( US 20180225721 A1), hereinafter referenced as Bharath, in view of Wu et al. ( WO 2023241415 A1), hereinafter referenced as Wu, further in view of Facey et al. ( US 20220007065 A1), hereinafter referenced as Facey.
Regarding Claim 11, Bharat in view of Wu teach the method as claimed in claim 1. Bharat further teaches, wherein the target media is generated [in a predefined format] based on merging in a predefined manner the generated background music and the generated audio speech ( Bharat: Para.[0091], Figs. 1, 8, The ad selection server 137 selects 840 a voice for the text-to-speech (TTS) algorithm based on the obtained user information about the user of the client device 110, content of the personalized text ad, and content data describing digital audio content transmitted to the client device 110. Selecting 840 may refer to selecting a preset voice and/or to selecting vocal parameters to customize a voice generated by a TTS algorithm).
Bharat in view of Wu while teaching the method of claim 11, fails to explicitly teach the claimed, wherein the target media is generated in a predefined format.
However, Facey does teach the claimed, wherein the target media is generated in a predefined format ( Facey: Para.[0096], The audio creative 402 may include any object that contains all the data for rendering the audio advertisement. the object may be an audio file (e.g., MP3, WAV, WMA, or OGG format), an image for companion ad (e.g., GIF, JPEG, PNG, HTML, JavaScript, etc.), other data (e.g., metadata such as title, description, etc.) or interactive element for rendering the non-intrusive advertisement).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Facey’s teaching of including functionality for presenting audio/ digital content to digital works such as a game or application, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu , because, by efficiently presenting audio content with video content of a digital work at the same time is particular advantageous, especially with interactive content like games, as audio can be swapped in and out without disrupting user interaction significantly.(Facey, Para.[0006]-[0008]).
Claim 25 is system claim performing the steps in method claim 11 above and as such, claim 25, is similar in scope and content to claim 11 and therefore, claim 25 is rejected under similar rationale as presented against claim 11 above.
Regarding Claim 12, Bharat in view of Wu teach the method as claimed in claim 1. Bharat in view of Wu fail to explicitly teach the claimed, the method further comprises: generating a script, by the processing unit, based on one or more predefined protocol standards and the target media, wherein the script comprises a data related to one or more media files, and a pre- defined tag of each media file from the one or more media files, and streaming, by the processing unit to one or more user devices, the target media based on the script.
However, Facey does teach the claimed, the method further comprises: generating a script, by the processing unit, based on one or more predefined protocol standards and the target media, wherein the script comprises a data related to one or more media files, and a pre- defined tag of each media file from the one or more media files ( Facey: Para.[0119],[0125], MRAID ( Mobile Rich Media Ad Interface Definitions) allow developers to create rich media ads while controlling how the ads interact with the apps which the ads or other audio data are inserted. MRAID comprises a standardized set of commands ( script) designed to work with HTML5 and JavaScript, that developers use to communicate with each application’s native code which actions the advertisements perform. MRAID audio creatives are generated by wrapping the original/standard audio creatives (e.g. mp3, ogg, aac) into MRAID tags),
and streaming, by the processing unit to one or more user devices, the target media based on the script ( Facey: Para.[0125], The MRAID script may interact with or be dependent on the SDK ( software development kit) used to create the digital work (e.g. application or game). For example, the SDK may have access at device level to the device's audio functionality and the MRAID script may take advantage of this access directly or indirectly ( e.g. by issuing instructions to do so)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Facey’s teaching of including functionality for presenting audio/ digital content to digital works such as a game or application, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu , because, by efficiently presenting audio content with video content of a digital work at the same time is particular advantageous, especially with interactive content like games, as audio can be swapped in and out without disrupting user interaction significantly.(Facey, Para.[0006]-[0008]).
Claim 26 is system claim performing the steps in method claim 12 above and as such, claim 26, is similar in scope and content to claim 12 and therefore, claim 26 is rejected under similar rationale as presented against claim 12 above.
Regarding Claim 13, Bharat in view of Wu, further in view of Facey teach the method as claimed in claim 12. Facey further teaches, wherein the script is related to at least one of a set of bitrates, a set of media, and a set of uniform resource locators (URLs) ( Facey: Para.[0125],[0127], The MRAID script may interact with or be dependent on the SDK used to create the digital work (e.g. application or game). MRAID parameters may include URL to the creative audio file).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Facey’s teaching of including functionality for presenting audio/ digital content to digital works such as a game or application, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu, because, by efficiently presenting audio content with video content of a digital work at the same time is particular advantageous, especially with interactive content like games, as audio can be swapped in and out without disrupting user interaction significantly.(Facey, Para.[0006]-[0008]).
Claim 27 is system claim performing the steps in method claim 13 above and as such, claim 27, is similar in scope and content to claim 13 and therefore, claim 27 is rejected under similar rationale as presented against claim 13 above.
Regarding Claim 14, Bharat in view of Wu, further in view of Facey teach the method as claimed in claim 12. Facey further teaches, wherein a predefined protocol standard from the one or more predefined protocol standards is a Video Ad Serving Template (VAST) protocol standard ( Facey: Para.[0102], Fig. 4, The VAST (Video Ad Serving Template) tag 404 conforms to VAST protocol that defines the procedure of placement for linear audio ads (appear before, after or at the middle of audio content consumption), allowing an advertiser or game developer to select advertisements for placement in the video content ( e.g., video game)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Facey’s teaching of including functionality for presenting audio/ digital content to digital works such as a game or application, into the system and method of dynamically generating audio in advertisements, taught by Bharath in view of Wu, because, by efficiently presenting audio content with video content of a digital work at the same time is particular advantageous, especially with interactive content like games, as audio can be swapped in and out without disrupting user interaction significantly.(Facey, Para.[0006]-[0008]).
Claim 28 is system claim performing the steps in method claim 14 above and as such, claim 28, is similar in scope and content to claim 14 and therefore, claim 28 is rejected under similar rationale as presented against claim 14 above.
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant's disclosure.
Rowe et al. (US 20170223428 A1) teaches methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing customized television advertisements. In one aspect, television advertising templates are used for generating customized television advertisements. The television advertisement templates include targeting criteria specifying targeting conditions for the television advertising template, which are conditions for selecting the television advertisement template for an advertisement availability, and content selection criteria specifying availability content associated with an advertisement availability for use in selecting variable advertisement content elements for inclusion in a customized television advertisement generated from the television advertising template. The variable advertisement content elements can include video elements, audio elements, and text elements.
Boskovich et al. (US 20220030325 A1) teaches methods and apparatus for providing attribute-based search of media assets such as video and audio assets, and associated augmented reality functions including dynamic provision of relevant secondary content relating to the identified attribute(s). In one embodiment, media or content assets are ingested into a processing system and processed according to one or more attribute detection, identification, and characterization algorithms. Attributes detected may include for example the presence of tangible items such as clothing or chattels, particular persons such as celebrities, and/or certain contexts such as sporting activities and musical performances, as rendered within the media asset. In one implementation, the characterized assets are provided a unique ID, and stored so as to permit cross-correlation based on, e.g., the identified and characterized attributes. Secondary content (e.g., advertising or promotional content) is correlated to each identified asset, and dynamically served upon a user providing some threshold level of interaction with the attribute.
Candelore et al. (US 20230362452 A1) teaches a content distribution system and method for distribution-side generation of captions is disclosed. The content distribution system receives media content including video content and audio content associated with the video content and generates a first text based on a speech-to-text analysis of the audio content. The content distribution system further generates a second text that describes audio elements of a scene associated with the media content. The audio elements are different from a speech component of the audio content. The content distribution system further generates captions for the video content based on the first text and the second text and transmits the generated captions to an electronic device via an Over-the-Air (OTA) signal, via a cable, or via a streaming Internet connection.
Balasubramanian et al. (US 9113213 B2 ) teaches a system and method are described for delivering to a member of an audience supplemental information related to presented media content. Media content is associated with media metadata that identifies active content elements in the media content and supported intents associated with those content elements. A member of an audience may submit input related to an active content element. The audience input is compared to media metadata to determine whether supplemental information can be identified that would be appropriate to deliver to the audience member based on that person's input. In some implementations, audience input includes audio data of an audience's spoken input regarding the media content.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NADIRA SULTANA whose telephone number is (571)272-4048. The examiner can normally be reached M-F,7:30 am-5:00pm.
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, Paras D. Shah can be reached on (571) 270-1650. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/NADIRA SULTANA/Examiner, Art Unit 2653
Prosecution Insights