DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “201” has been used to designate both the vector embedding model and query sign language dictionary. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 1-8 are objected to because of the following informalities:
MPEP 608.01(m) describes the requirements for claim form, particularly noting- "each claim must be the object of a sentence" and "[e]ach claim begins with a capital letter and ends with a period." Claims 1 and 7 begin with a capital letter, but feature a capital letter at the start of each claim limitation where each capital letter should be corrected to be lowercase. Also, since claims 1 and 7 feature1 a collection of clauses in a combination, the word --and-- should be inserted between the feedback loop system and non-matching word handling unit limitations in claim 1 and prior to the handling non-matching word step in claim 7. Claims 5-6 and 8 contain similar grammatical issues and are similarly objected to. The dependent claims inherit the objected to limitations of their respective parent claims, and thus, have also been objected to due to minor informalities by virtue of their dependency.
In claim 7, the acronym "LLM" should be expanded in order to better establish its meaning in the claim (e.g., see claim 1 acronym expansion).
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-8 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites a "method for implementing an automatic sign language video conversation by translating complete sentences into Sign Language using word embeddings comprising…" a series of modules, engines, models, and units. It is thus, unclear what method is being claimed due to a lack of any corresponding steps or acts. For claim interpretation in the interest of compact prosecution, due to the preamble statement of statutory class as a "method", each claim element will be construed as the step without the recited structural element. For example, in the case of the "Input Capture Unit", that term will be construed as being deleted leaving only the method step "capturing video input from a user performing sign language gestures." This claim interpretation is reflected in the restructuring of the claim language in the below prior art rejections.
If the Applicant does intend to recite claim 1 as a system as was not indicated in the preamble, the Applicant should be aware that many of these terms would relate to computer-implemented 35 U.S.C. 112(f) claim interpretation that requires reading in from the specification a corresponding algorithm for achieving the high level function and a computer processor (In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function. See, e.g., Noah Systems Inc. v. Intuit Inc., 675 F.3d 1302, 1312, 102 USPQ2d 1410, 1417 (Fed. Cir. 2012); Aristocrat, 521 F.3d at 1333, 86 USPQ2d at 1239). In some cases, such an interpretation could result in the lack of an underlying algorithm further leading to indefiniteness under 35 U.S.C. 112(b). Caution is thus recommended if Applicant is considering amending the claim into a system claim and continuing to use generic placeholders for structures such as “unit” and module (see MPEP 2181(I) and 2181(II)(B)). If the Applicant is interested in a system claim such system could be recited as comprising a “processor and a memory storing program instructions for execution by the processor to perform a method comprising” the functional steps of claim 1 (e.g., “capturing video input from a user performing sign language gestures, converting the sampled video images containing sign language gestures into corresponding sign language words, etc.) while avoiding the use of the generic terms “unit” and “module” so as to avoid claim construction under 35 U.S.C. 112(f).
Dependent claims 2-6 and 8 inherit and fail to resolve the indefinite claim language of parent claim 1 by adding any steps or acts that comprise the method, and thus, have also been rejected under 35 U.S.C. 112(b) for being indefinite.
Regarding Claim 2, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). For claim interpretation these limitations will be interpreted as being optional.
In Claim 7, Line 2, "the method of translating..." lacks antecedent basis and it is unclear what method is being referenced by this limitation. For the purposes of claim interpretation in the interest of compact prosecution, "the method of translating" will be construed as --a method of translating--.
In addition to the above indefiniteness issues, the claims are replete with 35 U.S.C. 112(b) issues related to antecedent basis where it is unclear what preceding term is being reference by the term introduced by a definite article (i.e., the). Each of these terms will be listed below and described how the term will be construed for the purposes of claim interpretation in the interest of compact prosecution in parentheses:
Claim 1: "the sampled video images" (line 6: --the sampled video--), "sign language gestures" (lines 6-7: term already mentioned in line 3 so will be construed as --the sign language gestures--), "the reconstructed sentence" (line 11: "the converted sentence"), "the use of existing words" (lines 14-15: --use of existing words--), "the provided dictionary" (line 15: --a provided dictionary--), "representing it" (line 16: unclear what is being referenced by it (the tokenized sentence, the simplified sentence, or something else), will be construed as --the simplified sentence--), "the sign language words" (line 23: there are multiple preceding instances of the sign language words so it is unclear which one is being referenced; will be construed as --the sequence of sign language words--), "the sequence of sign language images" (line 25: --a sequence of the images of sign language gestures--, "them" (line 26: unclear what "them" is referencing, will be construed as --the user--), "the capability" (line 29: --a capability--), "the word" (line 29: -a corresponding word--), and "the dictionary (line 30: unclear whether the dictionary refers to the predefined sign language dictionary, the provided dictionary, or some other dictionary; construed as --the predefined sign language dictionary--).
Claim 5: "the form of word embeddings" (lines 3-4: --a form of the word embeddings--) and "the final sequence of sign language words" (line 6: --a final sequence of sign language words--).
Claim 6: "user feedback" (line 4: already introduced in parent claim 5; construed as --the user feedback--).
Claim 7: "the sequence of sign language images" (line 9: it appears that the previous limitation should have read --generating the sequence of sign language images-- which would correct this antecedent basis issue), "the user" (line 9: --a user--), and "by spelling them out or substituting with sign language" (line 10: unclear what is meant by "them" or what is substituted; will be construed as --by spelling out the non-matching words or substituting the non-matching words with corresponding sign language--).
Claim 8: "the necessary sign language image" (lines 6-7: --a necessary sign language image--) and "the client" (line 8: --the user--).
Dependent claims 2-6 and 8 inherit and fail to resolve the indefinite claim language of parent claim 1 by resolving antecedent basis issues, and thus, have also been rejected under 35 U.S.C. 112(b) for being indefinite by virtue of their dependency.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6 and 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because Claim 1 is a method claim defined as comprising a number of units, modules, engines, and models. Per MPEP 2106.03(I)- a method or process claim “defines "actions", i.e., an invention that is claimed as an act or step, or a series of acts or steps.” Claim 1 does not comprise any steps and thus does not properly fall within the process statutory class under 35 U.S.C. 101. Since claim 1 also does not claim an apparatus, machine, manufacture, or composition of matter, claim 1 does not properly fall within at least one of the statutory categories of invention. Accordingly, claim 1 is directed towards non-statutory subject matter under 35 U.S.C. 101. The claims further dependent on claim 1 (2-6 and 8) fail to add any steps or acts to method claim 1, and thus, are also directed towards non-statutory subject matter under 35 U.S.C. 101 for not falling within at least one statutory category of invention. Note that claim 7 is directed towards at least a product of manufacture in the form of a non-transitory computer-readable storage medium storing executable instructions and so was not included in this particular rejection.
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea under the broadest reasonable interpretation (BRI) without significantly more.
Independent Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims regard a process that, as drafted under the, covers performance of the limitations as a mental process, but for the recitation of generic computer memory. For example, under the BRI, a human could perform the following:
Receiving an input sentence (a human could read and mentally understand a sentence);
Simplifying the sentence using a pre-trained LLM (use of the LLM, a human here need only read and understand the results of a simplified sentence in a natural language);
Tokenizing and representing the sentence with word embeddings (a human can parse a sentence on paper and annotate the sequence with word attributes constituting a vector/embedding);
Mapping the embeddings to sign language words (a human with an understanding of sign language can look to a table/dictionary/personal knowledge and map the word semantics to a sequence of sign);
Generating the sequence of sign language words (a human can write out the sequence of signs/glosses to be used using pen and paper);
Constructing a video from the sequence of sign language images to be displayed to the user (a human can act out a sequence of sign gestures while manually hitting a record button);
Handling non-matching words by spelling them out or substituting with sign language when available (a human can mentally decide upon finger spellings and act out such motions using gestures).
This judicial exception is not integrated into a practical application. Outside of the identified abstract idea, the claimed invention only recites a computer program stored on a non-transitory computer-readable medium that amounts to no more than mere instructions to implement an otherwise abstract idea using generic computer components. The computer is not improved as a tool, only used for its ordinary purpose of executing a program as a tool.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The above identified additional generic computer components are no more than mere instructions to apply the exception using generic computer components that are well-known, routine, and conventional as is evidenced by Bancorp Services v. Sun Life (Fed. Cir. 2012) and Alice Corp. v. CLS Bank (2014).
Accordingly, claim 7 is not directed towards patent eligible subject matter under 35 U.S.C. 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5 and 7-8 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Meged, et al. (U.S. PG Publication: 2025/0308409 A1).
With respect to Claim 1, Meged discloses:
A method for implementing an automatic sign language video conversation by translating complete sentences into Sign Language using word embeddings, comprising:
capturing video input from a user performing sign language gestures (recording a signer making gestures/movements in motion capture (MoCap), Paragraphs 0190 and 0193);
sampling the captured video to identify individual sign language words (recorded gestures are "digitally translated" leveraging computer vision for each gloss for the sign language interpretation, Paragraphs 0190 and 0193);
converting the sampled video images containing sign language gestures into corresponding sign language words (translation of input signs for an LLM of a personal assistant, Paragraphs 0024-0025; translation involves generating a gloss corresponding to a word or words in an input to convert or translate a video/sign language input for processing by an LLM, Paragraphs 0019, 0111, 0118-0119, 0169, and 0188);
converting the identified sign language words into a coherent sentence (pre-processing a sequence of input words into a sentence such as a question or a request for information for understanding by an LLM, Paragraphs 0019, 0024-0025, 0111, 0117, and 0169);
utilizing a fine-tuned large language model (LLM) trained on specific data to generate responses based on the reconstructed sentence (examples of fine-tuned LLMs to generate responses using the formatted input such as an answer to a question or requested information, Paragraphs 0024-0025);
utilizing a pre-trained large language model (LLM) accessed via an application programming interface (API) (use of an API in sign language generation processing, Paragraphs 0021-0022, 0024, and 0097) to simplify the reconstructed sentence, focusing on key verbs and nouns, and removing complex or unnecessary phrases, and ensuring the use of existing words in the provided dictionary ("input is pre-processed and restructured" where pre-processing involves conversion into "language that's more accessible" and "easier...to understand" and wherein pre-processing can involve the use of "models like BERT or GPT" that are specific examples of pre-trained large language models, Paragraphs 0114-0117; see that generation involves a focus on verbs/actions and important nouns in the sentence as well as the removal of complex terms/words (e.g., "condition") and ensuring the use of dictionary terms such as via the use of exiting synonyms, 0114-0116, 0123, 0125, and 0141-0146);
tokenizing the simplified sentence and representing it using word embeddings that capture semantic relationships between words (identification of "each word in the input" constituting a token and the generation of semantic/word sense/contextual embeddings for disambiguation, Paragraphs 0011, 0117, 0127-0128, 0134, and 0169);
mapping the word embeddings to a predefined set of sign language words using a trained model, accommodating variations in sentence structure and context (linguistic elements in the form of words utilizing the contextual embeddings are translated into a gloss ("written text to capture the essence of sign language" or "sign language words" as claimed) where "each gloss corresponds to a specific word or to a sequence of words from the...pre-processed input, Paragraphs 0117-0120, 0122, and 0126-0128; note the varying accommodating approaches for various sentence structure and context via homographs, context, intensity based upon context, etc., in Paragraphs 0127-0128, 0146-0148, and 0158);
converting the mapped embeddings into a sequence of sign language words (generation of "Visual generation guidance can include one or more directives pertaining to the generation of visual signs based on notation extending to a gloss sequence," Paragraphs 0172-0174 and 0196);
mapping the sign language words to images of sign language gestures using a predefined sign language dictionary (use of existing visual data dictionaries in performing mapping/selection of an optimal visual image sequence, Paragraphs 0188 and 0193-0196);
constructing a video from the sequence of sign language images to be displayed to the user, enabling them to see the complete sentence ("provide a visual character, such as an avatar 120 to perform the representation by displaying a video of the avatar 120 presenting the visual signs based on the guidance," Paragraphs 0098, 0101, and 0204 (discussing rendering or construction of such a video));
refining translations based on user input and contextual information (user preferences on avatar presentation and user input contextual information for ensuring that the sign language is translated correctly, Paragraphs 0026, 0113, 0120, and 0201);
spelling out words that do not have corresponding sign language words, with the capability to replace spelling with the sign when the word is added to the dictionary ("visual spelling" used in situations "where words without representation as a gloss in sign language are identified," Paragraph 0147; techniques such as finger spelling is used in situations "where words without representation as a gloss in sign language are identified" where words may be identified in the future when added via visual data capture and "creating new glosses," Paragraphs 0141, 0147, and 0188-0193).
With respect to Claim 2, Meged further discloses:
The method of claim 1, wherein the word embedding model is a pre-trained model selected from the group consisting of NLP embedding models, such as Word2Vec, GloVe, and BERT, and is fine-tuned on a corpus of text to capture language-specific nuances (see known LLM BERT that is fine-tuned to process text and handle language nuances such as normalization, disambiguation, and context, Paragraphs 0024, 0117, and 0128).
With respect to Claim 3, Meged further discloses:
The method of claim 1, wherein the mapping algorithm developed for translating word embeddings into corresponding sign language words considers semantic similarity and grammatical structure specific to Sign Language (mapping includes "cultural nuances and context-specific interpretations, which can be used to guide the translation process" along with "contextual" understanding and "semantic analysis", Paragraphs 0117, 0128, 0134 (defining semantic matching related to sign language), 0135-0137, and 0143-0144).
With respect to Claim 4, Meged further discloses:
The method of claim 1, enabling seamless translation from input sentence to sign language output (note claim interpretation as a method per the 35 U.S.C. 112(b) rejection where method steps are addressed; virtual assistant platform enabling seamless conversation from user sentence input to sign language output via a visual avatar, Paragraphs 0024-0025; Fig. 2).
With respect to Claim 5, Meged further discloses:
Storing (process implementation using a processor and associated memory, Paragraphs 0091-0092 and 0103-0104, wherein throughout the processing steps, the resulting data would require storage at least temporarily in order to proceed with the further processing steps/analysis) intermediate data representing the simplified sentence ("input is pre-processed and restructured" where pre-processing involves conversion into "language that's more accessible" and "easier...to understand", Paragraphs 0114-0117);
Word Embeddings Data: data representing the tokenized sentence in the form of word embeddings (identification of "each word in the input" constituting a token and the generation of semantic/word sense/contextual embeddings for disambiguation, Paragraphs 0011, 0117, 0127-0128, 0134, and 0169);
data reflecting the mapping of word embeddings to sign language words (linguistic elements in the form of words utilizing the contextual embeddings are translated into a gloss ("written text to capture the essence of sign language" or "sign language words" as claimed) where "each gloss corresponds to a specific word or to a sequence of words from the...pre-processed input, Paragraphs 0117-0120, 0122, and 0126-0128);
data representing the final sequence of sign language words (visual data corresponding to the gloss sequence and how to present it, Paragraphs 0197; Fig. 3, Element 370);
a table mapping individual letters to their corresponding sign language images (mapping of letters to glosses and images in finger spelling, Paragraphs 0147 and 0170-0172);
a table mapping words to their corresponding language images (visual data pertaining to a plurality of glosses such as the word he or left mapped to corresponding sign images, Paragraphs 0194-0195);
Data related to interactions with human agents and user feedback (stored preferences that the user can select "relate" to their preferences for interactions with humanoid agents and feedback to the type of avatar that is preferred, Paragraph 0201; Fig. 1C).
With respect to Claim 7, Meged discloses:
A non-transitory computer-readable storage medium storing executable instructions that, when executed by a processor (non-transitory computer-readable memory storing a program of instructions executable by a computer processor, Paragraph 0209), cause a system to perform the method of translating complete sentences into Sign Language using word embeddings, comprising:
Receiving an input sentence ("obtain input content for translation to sign language...can be text input such as a sentence," Paragraph 0111);
Simplifying the sentence using a pre-trained LLM ("input is pre-processed and restructured" where pre-processing involves conversion into "language that's more accessible" and "easier...to understand" and wherein pre-processing can involve the use of "models like BERT or GPT" that are specific examples of pre-trained large language models, Paragraphs 0114-0117);
Tokenizing and representing the sentence with word embeddings (identification of "each word in the input" constituting a token and the generation of semantic/word sense/contextual embeddings for disambiguation, Paragraphs 0011, 0117, 0127-0128, 0134, and 0169);
Mapping the embeddings to sign language words (linguistic elements in the form of words utilizing the contextual embeddings are translated into a gloss ("written text to capture the essence of sign language" or "sign language words" as claimed) where "each gloss corresponds to a specific word or to a sequence of words from the...pre-processed input, Paragraphs 0117-0120, 0122, and 0126-0128);
Generating the sequence of sign language words (generation of "Visual generation guidance can include one or more directives pertaining to the generation of visual signs based on notation extending to a gloss sequence," Paragraphs 0172-0174 and 0196);
Constructing a video from the sequence of sign language images to be displayed to the user ("provide a visual character, such as an avatar 120 to perform the representation by displaying a video of the avatar 120 presenting the visual signs based on the guidance," Paragraphs 0098, 0101, and 0204 (discussing rendering or construction of such a video));
Handling non-matching words by spelling them out or substituting with sign language when available (handling situations where a word/gloss does not have visual sign information by substituting sign language "synonyms" that "that can convey the same or very similar
meanings but have established signs in ASL," Paragraphs 0125; see also "visual spelling" used in situations "where words without representation as a gloss in sign language are identified," Paragraph 0147; although the limitation is recited in the alternative where the prior art needs to only teach at least one of the alternatives, the prior art discloses both alternatives).
With respect to Claim 8, Meged further discloses:
The method of claim 1, further comprising: a collection of labeled sign language images, each associated with corresponding sign language words ("Visual data 232 may store visual data pertaining to a plurality of glosses" (i.e., "sign language words"), Paragraph 0194);
training a computer vision model using the labeled sign language images to recognize and predict sign language words from new images (computer vision used for "sign language interpretation," Paragraphs 0188, 0192-0194, and 0202 wherein in order to be able to perform such interpretation, the model must first be trained in some manner, otherwise a computer would not be able to make an association between images and glosses/words);
utilizing the trained computer vision model to output the necessary sign language image corresponding to a given word, enabling the construction of an answer video to be displayed to the client (animation of the avatar using the computer vision model, Paragraph 0202; see also Paragraphs 0188 and 0192-0194; and digital assistant implementation providing answers or requested information, Paragraphs 0024-0025).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Meged, et al in view of Mishra (U.S. PG Publication: 2024/0304031 A1).
With respect to Claim 6, Meged discloses the virtual agent using bi-directional sign language communication as applied to Claim 5. Meged also disclsoes for storing ongoing translation data as a part of a processor-implemented process per the claim 5 rejection wherein ongoing translation data is stored as a part of a digital assistant/meeting session (Paragraph 0023-0025 and 0102). Meged does not specifically teach archiving completed translations, new words, human agent interaction, and user feedback for further refinement. Mishra, however, disclsoes archiving completed translations, new words, human agent interaction, and user feedback for further refinement (historical comm session database 248 storing completed translations in a session, user specific gestures having different word-based meanings, human agent interaction and user/agent feedback for model training/refinement, Paragraphs 0053-0054, 0059-0060, 0065, 0069 (words related to gestures), 0086, 0099, 0101, and 0104-0105).
Meged and Mishra are analogous art because they are from a similar field of endeavor in sign language communication systems. Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to utilize the archiving of historical data taught by Mishra in the sign language translation models of Meged to provide a predictable result of a model that is more accurate in detecting, identifying, and translating gestures of a particular user (Mishra, Paragraph 0054).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Thomson, et al. (U.S. PG Publication: 2025/0078574 A1)- teaches an IVR system that uses sign language for interaction using American sign language recognition (Paragraph 0484).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES S WOZNIAK whose telephone number is (571)272-7632. The examiner can normally be reached 7-3, off alternate Fridays.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant may 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 at (571)272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JAMES S. WOZNIAK
Primary Examiner
Art Unit 2655
/JAMES S WOZNIAK/Primary Examiner, Art Unit 2655
Prosecution Insights