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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/19/2026 has been entered.
Response to Arguments
1. Regarding the rejection of claims 1-6 and 9-19 under 35 U.S.C. § 101, Applicant's arguments filed 02/19/2026 have been fully considered but they are not persuasive.
Step 2A Prong 1:
Applicant argues first that amended claims 1 and 18 are not directed to mental processes. Specifically, Applicant argues that the claims recite complex processes that cannot be performed practically in the mind, arguing that amendments regarding the input text being an e-book or website and regarding the input text including meta information, preclude the claims from being practiced by a person mentally. Furthermore, Applicant argues that the spaced repetition mechanism cannot be performed mentally, as well as the tracking of the “large number of visual aids” that can be used for translation. The Examiner respectfully disagrees with these arguments.
Each of the steps of the claimed process can be performed as a mental process with the aid of pen and paper. A person can first read input text along with meta-information, which broadly reads on any form of information regarding the text, such as an author of the text. This meta-information is not constrained to the narrow definition of “non-human readable structural data” argued under its BRI, and thus a person can indeed read input text and pre-process it (e.g. select words that are suitable to translate based on meta-information). Further a person can select words from these pre-processed words based on a broadly recited selection criteria, such as selecting words with closely related emojis. A person can then translate the word selection into at least two graphical symbols (e.g. can draw pictures/emojis representing words) based on a context (e.g. by considering the sentence as a whole in determining the meaning of a potentially ambiguous word like ‘right’). Further, a person can display this picture to the user in order to help them learn a foreign language (e.g. drawing an apple for a foreign language text ‘la pomme’) or complex words (e.g. representing compound words with a series of drawings). The additional limitation of the text forming content of e-books and websites is considered under Step 2A Prong 2 analysis.
Furthermore, the broadly recited spaced repetition mechanism can also be implemented as a mental process. A person can tutor a person to learn a language by using the translation word selection, selecting words to translate more frequently which are more difficult for the user, compared to easier words. Furthermore, the Examiner finds unpersuasive the argument that a person cannot remember the “sheer number of available emojis”.
Therefore, the claims are directed to mental processes.
Step 2A Prong 2:
Applicant further argues that the claims integrate the abstract ideas into a practical application through an improvement to a technology. Specifically, Applicant argues that the claims achieve an improvement to a technology via automated translation of text, addressing a problem of this translation being previously done manually with humans. The Examiner respectfully disagrees. Under Step 2A Prong 2 analysis, any additional elements are considered with respect to the claim as a whole to determine if they integrate the judicial exception into a practical application. The only additional limitations recited in claims 1 and 18 amount to mere instructions to implement the judicial exception using a generic computer. The various modules recited (pre-processing module, selection module, translation module, display modules) do not contain any specific architectures/components/interconnections which would demonstrate a specific technical system. The artificial intelligence language model recited is a further generic computer component that also lacks a specific architecture/component/interconnections, and amounts to merely utilizing a generic model to perform a task a person can do, which is write down a picture corresponding to a word. The additional limitation of the input text coming from content of an e-book or website also amounts to merely stating that the mental process be implemented in a computer context. Even when viewed in combination, mere instructions to implement the judicial exception using a generic computer do not integrate the judicial exception into a practical application as they do not impose any meaningful limits on practicing the abstract ideas. Therefore, the claims are directed to abstract ideas.
Hence, Applicant’s arguments are not persuasive.
Note:
The Examiner notes that incorporating further structural language from the specification into the claim would help for overcoming the 101 rejection. Specifically, incorporating language starting on pg. 5 line 11 of the specification would help to integrate the judicial exception into a practical application: “The triggering action may for instance be a cursor hovering operation such that the emojis only made visible once the reader or user hovers a cursor over the word or words to be translated. In this case, the emojis may optionally again disappear as soon as the cursor is moved away from the location of the word or words to be translated. Eye tracking functionality may also or instead be added so that the translation, i.e., the emojis, are only made visible as soon as the eye tracking algorithm detects that the reader is looking at the translation. If the reader is no longer looking at the translation, then the translation may be hidden.”
2. Regarding the rejections under 35 U.S.C. § 103, Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
3. Claims 2 and 19 are objected to because of the following informalities:
Claims 2 and 19: “further comprises a pre-processing module”, should instead be “further comprises the pre-processing module”, as antecedent basis is given for this term in amended claim 1 and amended claim 18 respectively.
Appropriate correction is required.
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.
4. Claims 1-6 and 9-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1, “A computer-implemented method” is recited, which is directed to one of the four statutory categories of invention (process) (Step 1: YES). However, the claims limitations, under their broadest reasonable interpretation, recite mental processes which fall into the category of abstract idea (Step 2A Prong 1: YES).
The following limitations, under their broadest reasonable interpretation, recite mental processes:
receiving input text comprising meta-information indicating a parameter of the input text: a person reads text along with meta information
pre-processing the input text to identify a set of words in the input text element suitable for translation to thereby obtain a pre-processed text element: a person looks over the text and picks out words that are suitable (e.g. words they can represent with pictures/emojis)
selecting one or more words out of the pre-processed input text element to be translated to obtain a word selection, the selection being carried out based on one or more selection criteria: a person selects one or more words in an input text to be translated using one or more selection criteria.
marking the word selection: a person writes down a note using pen and paper marking the selection of the word
translating the word selection identified by the marking into at least a set of graphical symbols …considering the context of the word selection in the pre-processed text element to dynamically translate the word selection based on the context to obtain a translated word selection, wherein a given word in the word selection is translated into a sequence of at least two graphical symbols: a person translates the selection words into a set of at least two graphical symbols using context in the sentence to obtain a translation using pen and paper.
displaying the input text element as translated to a user providing the user with an intuitive visual reading aid thereby helping the user to understand complex or foreign-language input text elements, wherein the input text element as translated comprises the translated word selection: a person writes down the translation using pen and paper, and shows the paper to the user, which helps the user with complicated/foreign words.
wherein the one or more selection criteria relate to one or more of the following aspects: difficulty of the respective word in the input text element to be read or understood by the user, and a spaced repetition mechanism according to which a given word out of the pre- processed text element is selected at uneven intervals: a person selects by considering selection criteria, where the criteria is based on difficulty of the word to be read or understood by user, and spaced repetition.
Claim 1 does not contain any additional elements which integrate the judicial exception into a practical application (Step 2A Prong 2: NO). The only additional limitations are “in a system…the system comprising a pre-processing module, a selection module, a translation module, and a display model”, and “translating…by using an artificial intelligence language model”, and “wherein the input text element forms a content of an e-book or a website”. These limitations are recited broadly and amounts to mere instructions to implement the judicial exception using a generic computer. Even when viewed in combination, mere instructions to implement the judicial exception using a generic computer do not integrate the judicial exception into a practical application as they do not impose any meaningful limits on practicing the abstract idea. Accordingly, claim 1 is directed to an abstract idea (Step 2A: YES).
Claim 1 does not contain any additional elements which amount to significantly more than the judicial exception (Step 2B: NO). As discussed above, the only additional limitation is mere instructions to implement the judicial exception using a generic computer. Even when viewed in combination, mere instructions to implement the judicial exception using a generic computer do not amount to significantly more than the judicial exception as they do not provide an inventive concept. Therefore, claim 1 is not patent eligible.
Regarding dependent claims 2-6, and 9-16, “The method” is recited, which is directed to one of the four statutory categories of invention (process) (Step 1: YES). However, the claims limitations, under their broadest reasonable interpretation, recite further mental processes in addition to those recited in independent claim 1, which fall into the category of abstract idea (Step 2A Prong 1: YES).
The following limitations, under their broadest reasonable interpretation, recite further mental processes:
Claim 2:
wherein the method further comprises the step of pre-processing… the input text element to identify a set of words in the input text element suitable for translation to thereby obtain a pre-processed text element, and wherein the one or more words are selected from the pre-processed text element: a person reads and preprocessed the input text to identify words that would be suitable to be translated, and then selects one or more words from the preprocessed text element
Claim 2 contains the additional limitation “comprises a pre-processing module…comprises the step of pre-processing by the pre-processing module”, which amounts to mere instructions to implement the judicial exception using a generic computer.
Claim 3:
wherein the word selection comprises one or more individual words and/or one or more sequences of consecutive individual words: a person selects one or more individual words and/or one or more sequences from the input text.
Claim 3 contains no additional limitations
Claim 4:
wherein the context of the respective selected word in the word selection comprises at least one word or sentence preceding the respective selected word and at least one word or sentence following the respective selected word: a person reads the input text, writing down context for a selected word by looking at least one word preceding and following the word.
Claim 4 contains no additional limitations
Claim 5:
wherein the translation of the word selection comprises …stochastically translating the word selection into a plurality of translation candidates each comprising a set of candidate graphical symbols, …assessing the translation quality of the translation candidates by using a utility function to assign a translation score to each one of the translation candidates, and …including only the translation candidate with the best utility score in the translated word selection.: a person translates the word selection into several candidates involving sets of graphical symbols, and assesses the quality of translation using a utility function as a set of rules to map each translation candidate to a certain translation score, and then selects the best translation as the candidate with the best utility score
Claim 5 contains the additional limitation of “the translation module”, which amounts to mere instructions to implement the judicial exception using a generic computer.
Claim 6:
wherein the utility function considers one or more of the following aspects: guessability of the meaning of a given translation candidate to the user, length of a given translation candidate, user's familiarity with a given translation candidate, and user's previous exposure to a given translation candidate..: a person determines a translation score for a candidate by rating each candidate based on a guessability, a length of the translation, a user familiarity with the candidate, and user’s previous exposure.
Claim 6 contains no additional limitations
Claim 9:
wherein the method further comprises …assessing the translation quality of the set of graphical symbols and if the translation quality is insufficient, then …forming a feedback loop to select one or more other words out of the pre-processed text element to obtain one or more other word selections, …translating the one or more other word selections into at least one or more other sets of graphical symbols, and once the translation quality of the respective set of graphical symbols is determined to be sufficient, only then including …the respective set of graphical symbols in the translated word selection.: a person assesses the quality of translation that they made, and if the translation quality is not sufficient, decides to select one or more other words and repeat the translation until the words that are selected result in a sufficient translation
Claim 9 contains the additional limitations “the translation module” and “the system”, which amount to mere instructions to implement the judicial exception using a generic computer.
Claim 10:
wherein the translation quality is assessed…: a person assesses the quality of translation that they made
Claim 10 contains the additional limitation “assessed…by an artificial intelligence engine configured to simulate a human reader”. This limitation is recited broadly and amounts to mere instructions to implement the judicial exception using a generic computer.
Claim 11:
wherein the displayed input text element as translated comprises the word selection that is used to obtain the respective set of graphical symbols included in the translated word selection.: a person displays text to the user on pen and paper, and includes the word that has been translated along with the graphical symbols
Claim 11 contains no additional limitations
Claim 12:
wherein the translated word selection replaces in the displayed input text element as translated the word selection that is used to obtain the respective set of graphical symbols: a person displays text to the user on pen and paper, and replaces the word that has been translated with the graphical symbols
Claim 12 contains no additional limitations
Claim 13:
wherein the translated word selection is only displayed …to the user if a given action is triggered: a person displays text to the user on pen and paper, only shows the user the translation if the user takes a specific action
Claim 13 the additional limitation “by the display module”, which amounts to mere instructions to implement the judicial exception using a generic computer.
Claim 14:
wherein the given action comprises …the user hovers a cursor above the word selection that is used to obtain the respective set of graphical symbols included in the translated word selection: a person shows the translation to the user in response to the user pointing to the word selection on the piece of paper.
Claim 14 contains the additional limitations “detection by the system” “hovers a cursor above”, which amounts to mere instructions to implement the judicial exception using a generic computer.
Claim 15:
wherein the graphical symbols are emojis.: a person draws emojis as the translation for the selected one or more words.
Claim 15 contains no additional limitations
Claim 16:
wherein in addition to the context, the dynamic translation of the word selection… considers one or more of the following aspects: user's age, user's nationality, user's geographical location, time of the day, user's cultural background, and user's language skills..: a person writes down information to aid in their decisions for translating, writing down information related to a user’s age, nationality, geographical location, time of day, cultural background, and language skills.
Claim 16 contains the additional limitation “by the translation module”, which amounts to mere instructions to implement the judicial exception using a generic computer.
Claims 2-6 and 9-16 do not contain any additional elements which integrate the judicial exception into a practical application (Step 2A Prong 2: NO). As discussed above, the only additional limitations amount to mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer does not integrate the judicial exception into a practical application. Accordingly, claims 2-6 and 9-16 are directed to an abstract idea (Step 2A: YES).
Claims 2-6 and 9-16 do not contain any additional elements which integrate the judicial exception into a practical application (Step 2B: NO). As discussed above, the only additional limitations amount to mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not amount to significantly more than the judicial exception. Therefore, claims 2-6 and 9-16 are not patent eligible.
Regarding claim 17, “A non-transitory computer program product” is recited, which is directed to one of the four statutory categories of invention (article of manufacture). However, the claims limitations, under their broadest reasonable interpretation, recite mental processes which fall into the category of abstract idea.
The following limitations, under their broadest reasonable interpretation, recite mental processes:
implementing the steps of the method according to claim 1: the method of claim 1 recites mental processes (see above analysis for Claim 1).
Claim 17 does not contain any additional elements which integrate the judicial exception into a practical application. The only additional limitation is “A non-transitory computer program product comprising instructions for implementing…when loaded and run on computer means of a data processing device”. This limitation is recited broadly and amounts to mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not integrate the judicial exception into a practical application. Accordingly, claim 17 is directed to an abstract idea.
Claim 17 does not contain any additional elements which amount to significantly more than the judicial exception. As discussed above, the only additional limitation is mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not amount to significantly more than the judicial exception. Therefore, claim 17 is not patent eligible.
Regarding claim 18, “An apparatus” is recited, which is directed to one of the four statutory categories of invention (machine) (Step 1: YES). However, the claims limitations, under their broadest reasonable interpretation, recite limitations similar to those in method claim 1, and thus also recites mental processes which fall into the category of abstract idea (Step 2A Prong 1: YES) (see above analysis for claim 1).
Claim 18 does not contain any additional elements which integrate the judicial exception into a practical application. The only additional limitations are “An apparatus”, “a pre-processing module”, “a selection module”, “a translation module”, “by using an artificial intelligence language mode”, and “a display module”, and “configured to perform operations comprising”. These limitations are recited broadly and amounts to mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not integrate the judicial exception into a practical application. Accordingly, claim 18 is directed to an abstract idea.
Claim 18 does not contain any additional elements which amount to significantly more than the judicial exception. As discussed above, the only additional limitations are mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not amount to significantly more than the judicial exception. Therefore, claim 18 is not patent eligible.
Regarding dependent claim 19, “The apparatus” is recited, which is directed to one of the four statutory categories of invention (machine) (Step 1: YES). However, the claims limitations, under their broadest reasonable interpretation, recite limitations similar to those in method claim 2, and thus also recites mental processes which fall into the category of abstract idea (Step 2A Prong 1: YES) (see above analysis for claim 2).
Claim 19 does not contain any additional elements which integrate the judicial exception into a practical application. The only additional limitations are “a pre-processing module configured to perform operations comprising”. These limitations are recited at a high level of generality, and amount to mere instructions to implement the judicial exception using a generic computer. Mere instructions to implement the judicial exception using a generic computer do not amount to significantly more than the judicial exception. Accordingly, claim 19 is directed to an abstract idea.
Claim 19 does not contain any additional elements which integrate the judicial exception into a practical application. As discussed above, claim 19 does not contain any additional limitations. Therefore, claim 19 is not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
5. Claims 1-3, 5-6, 11-13, and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Bojja et al. (US 2017/0185581 A1, hereinafter Bojja) in view of Schmid (NPL Learnji — the language app based on emoji) and in further view of Edge et al. (US 2012/0322043 A1, hereinafter Edge).
Regarding claim 1, Bojja discloses A computer-implemented method in a system (Fig. 1) for translating an input text element into a sequence of characters comprising a set of graphical symbols (para. 0005), the system comprising a pre-processing module (Fig. 1, 116), a selection module (Fig. 1, 120), a translation module (Fig. 1, 118), and a display module (para. 0131 “To provide for interaction with a user, implementations of the subject matter described in this specification can be implemented on a computer having a display device…), the method comprising: the pre-processing module receiving input text comprising meta-information indicating a parameter of the input text (para. 0033 “The method 200 begins by obtaining (step 202) features associated with a communication (e.g., an electronic message) of a user. The features can include, for example, a cursor position in the content, one or more words from the communication, one or more words from a previous communication, a user preference (e.g., preferred instances when emoji are to be used, preferred specific emoji, preferred types of emoji, or preferred categories of emoji), and/or demographic information (e.g., an age, gender, ethnicity, income, or citizenship of the user and/or a recipient).”); the pre-processing module pre-processing the input text to identify a set of words in the input text element suitable for translation to thereby obtain a pre-processed text element (para. 0033 “The features are provided (step 204) to the emoji detection module 116, which preferably employs a plurality of emoji detection methods to identify candidate emoji that might be appropriate for the communication.”; para. 0051 “The part-of-speech (POS) tagging module 308 can be used to provide disambiguation. For example, a dictionary in the dictionary-based module 306 can be modified to include POS tags, such as Noun Phrases, Verb Phrases, Adjectives, etc., and/or additional information such as a total number of POS tags (e.g., per word) and a valid set of POS tags (i.e., a set of tags for which a word can be emojified).This allows the words in a sentence or phrase to be screened for possible emojification. Noun Phrases, if identified successfully by a Part of Speech Tagger, can be potentially bunched together at the phrase level and be replaced by relevant emoji. As an example, for the sentence “The Police Car sped along the road,” a POS tagger would identify “The Police Car” and “the road” as Noun Phrases and “sped along” as a Verb Phrase.”; see also components 302-316, which additionally suggest emojis); the selection module selecting one or more words out of the pre-processed text element to be translated to obtain a word selection, the selection being carried out based on one or more selection criteria (para. 0069 “Referring again to FIG. 1, for a given communication, the manager module 120 can select outputs from specific emoji detection methods, classifiers, and/or combinations of emoji detection methods to suggest emoji for insertion into the communication. The manager module 120 can make the selection according to, for example, the linguistic domain, a length of the communication, or a preference of a user.”; selecting particular outputs from emoji detection methods amounts to selecting particular words with which to subsequently translate); the selection module marking the word selection (carrying out the above selection to subsequently perform the translation reads on the BRI of ‘marking the word selection’; para. 0069); the translation module translating the word selection identified by the marking into at least a set of graphical symbols by using an artificial intelligence language model (para. 0033 “Output from the emoji detection module 116 is provided (step 206) to the emoji classifier module 118, where one or more classifiers process the output from the emoji detection module and provide (step 208) suggested emoji for the communication.”; Fig. 4; para. 0062 “Referring to FIG. 4, the emoji classifier module 118 can include an interpolation module 402, a support vector machines (SVM) module 404, and a linear SVM module 406.”; para. 0067 “Other possible classifiers used by the systems and methods described herein include, for example, decision tree learning, association rule learning, artificial neural networks, inductive logic programming, random forests, gradient boosting methods, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, and sparse dictionary learning. One or more of these classifiers, or other classifiers, can be incorporated into and/or form part of the emoji classifier module 118.”) considering the context of the word selection in the pre-processed text element (para. 0068 “In various implementations, the classifiers receive as input the probabilities or confidence scores generated by one or more of the emoji detection methods. The probability or confidence scores can correlate a word or a phrase in the user message to one or more possible emoji that the user may wish to insert. Depending on the classifier(s) in use, the classifiers can also receive as input the current cursor position, a word or phrase in the user message, a previous message or previous content sent or received by a user, user preferences, and/or user demographic information.”) to dynamically translate the word selection based on the context to obtain a translated word selection (para. 0061 “In general, the emoji classifier module 118 receives output from the emoji detection module(s) and process the output to obtain suggested emoji, using various techniques.”), wherein a given word in the word selection is translated into a sequence of at least two graphical symbols (para. 0060 “In a typical example, the word “luv” can be normalized to “love” by such a server, and the word “love” can then be correctly matched to one or more suitable emoji, such as a heart-shaped emoji (e.g., custom-character).”; para. 0068 “In various implementations, the classifiers receive as input the probabilities or confidence scores generated by one or more of the emoji detection methods. The probability or confidence scores can correlate a word or a phrase in the user message to one or more possible emoji that the user may wish to insert.”; para. 0013 “In certain implementations, the at least one classifier includes a supervised learning model, a partially supervised learning model, an unsupervised learning model, and/or an interpolation model. The at least one of the candidate emoji can be inserted at the current cursor position and can replace at least one word in the communication.”); the display module displaying the input text element as translated to a user…wherein the input text element as translated comprises the translated word selection (para. 0033 “Finally, at least one of the suggested emoji is inserted (step 210) into the communication. The emoji can be inserted into the communication automatically and/or be selected by the user for insertion. The inserted emoji can replace one or more words or phrases in the communication.”; para. 0031 “An application such as a web-based application can be provided as an end-user application to allow users to interact with the server system 112.”; para. 0131 “To provide for interaction with a user, implementations of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse, a trackball, a touchpad, or a stylus, by which the user can provide input to the computer. …In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user's client device in response to requests received from the web browser.”), wherein the input text element forms a content of an e-book or a website… (para. 0033 “The suggested emoji can be identified with the assistance of the manager module 120, which can select particular emoji detection methods and/or classifiers to use based on various factors, including, for example, a linguistic domain (e.g., gaming, news, parliamentary proceedings, politics, health, travel, web pages, newspaper articles, and microblog messages).”).
Bojja does not specifically disclose providing the user with an intuitive reading aid helping the user to understand complex or foreign-language input text elements…
Schmid teaches providing the user with an intuitive reading aid helping the user to understand complex or foreign-language input text elements… (see pg. 1, e.g., owl (‘die Eule’ in a foreign language (German)) has a corresponding owl emoji to aid the user in learning the foreign language).
Bojja and Schmid are considered to be analogous to the claimed invention as they are in the same field of natural language. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bojja to incorporate the teachings of Schmid in order to specifically have the word translated into an emoji provide the user with an intuitive visual reading aid thereby helping the user to understand complex or foreign-language input text elements. Doing so would be beneficial, as emojis are widely known graphical symbols which represent most basic communications and concepts (pg. 2, section 2), making them ideal representations to learn a foreign language.
Bojja in view of Schmid does not specifically disclose wherein the one or more selection criteria relate to one or more of the following aspects: difficulty of the respective word in the input text element to be read, understood, or remembered by the user, and a spaced repetition mechanism according to which a given word out of the pre-processed text element is selected at uneven intervals.
Edge teaches wherein the one or more selection criteria relate to one or more of the following aspects: difficulty of the respective word in the input text element to be read, understood, or remembered by the user, and a spaced repetition mechanism according to which a given word out of the pre-processed text element is selected at uneven intervals (para. 0047 “Embodiments of the learning module 125 include a core learning technique that is based on a learnedness value stored for every token. In general, a token is a stimulus-response pair where a student is presented with a stimulus (such as an English word), and the student provides a response (such as the Chinese translation of the English word).”; para. 0039 “The method determines when next to present the token to the student based on the student's response (box 230). In particular, a determination is made as to whether a correct response was provided by the student to the token (box 240). In some embodiments this is self-reported by the student, while in other embodiments it is determined through analysis of student-contributed speech or text responses. If the response is correct, then the method presents the token to the student at the next repetition interval (box 250). If the response is incorrect, then the learnedness value is reset and the progression through the repetition intervals is restarted (box 260). The repetition intervals, however, do take into account that the student has previously seen the material such that the progression through the repetition intervals is expanded as the student continues to provide correct responses to the token.”).
Bojja, Schmid, and Edge are considered to be analogous to the claimed invention as Bojja and Schmid are in the same field of natural language and Edge is in the same field of language learning. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bojja in view of Schmid to incorporate the teachings of Edge in order to specifically wherein the one or more selection criteria relate to one or more of the following aspects: difficulty of the respective word in the input text element to be read, understood, or remembered by the user, and a spaced repetition mechanism according to which a given word out of the pre-processed text element is selected at uneven intervals. Doing so would be beneficial, as this learning method allows for a user to quickly and effectively learn a particular concept (e.g. foreign language) with an adaptive learning curve tailored to the individual user/student (Edge, para. 0040).
Regarding claim 2, Bojja in view of Schmid and Edge discloses wherein the system further comprises a pre-processing module (Bojja, Fig. 1, 116), wherein the method further comprises the step of pre-processing by the pre-processing module the input text element to identify a set of words in the input text element suitable for translation to thereby obtain a pre-processed text element (para. 0033 “The features are provided (step 204) to the emoji detection module 116, which preferably employs a plurality of emoji detection methods to identify candidate emoji that might be appropriate for the communication.”; para. 0051 “The part-of-speech (POS) tagging module 308 can be used to provide disambiguation. For example, a dictionary in the dictionary-based module 306 can be modified to include POS tags, such as Noun Phrases, Verb Phrases, Adjectives, etc., and/or additional information such as a total number of POS tags (e.g., per word) and a valid set of POS tags (i.e., a set of tags for which a word can be emojified).This allows the words in a sentence or phrase to be screened for possible emojification. Noun Phrases, if identified successfully by a Part of Speech Tagger, can be potentially bunched together at the phrase level and be replaced by relevant emoji. As an example, for the sentence “The Police Car sped along the road,” a POS tagger would identify “The Police Car” and “the road” as Noun Phrases and “sped along” as a Verb Phrase.”; see also components 302-316, which additionally suggest emojis), and wherein the one or more words are selected from the pre-processed text element (para. 0069 “Referring again to FIG. 1, for a given communication, the manager module 120 can select outputs from specific emoji detection methods, classifiers, and/or combinations of emoji detection methods to suggest emoji for insertion into the communication. The manager module 120 can make the selection according to, for example, the linguistic domain, a length of the communication, or a preference of a user.”).
Regarding claim 3, Bojja in view of Schmid and Edge discloses wherein the word selection comprises one or more individual words and/or one or more sequences of consecutive individual words (Bojja, para. 0068 “In various implementations, the classifiers receive as input the probabilities or confidence scores generated by one or more of the emoji detection methods. The probability or confidence scores can correlate a word or a phrase in the user message to one or more possible emoji that the user may wish to insert. Depending on the classifier(s) in use, the classifiers can also receive as input the current cursor position, a word or phrase in the user message, a previous message or previous content sent or received by a user, user preferences, and/or user demographic information.”).
Regarding claim 5, Bojja in view of Schmid and Edge discloses wherein the translation of the word selection comprises the translation module stochastically translating the word selection into a plurality of translation candidates each comprising a set of candidate graphical symbols (Bojja, classifiers such as random forest are stochastically trained (uses randomness); Bojja teaches this classifier for translation, which reads on stochastically translating the word selection: para. 0067 “Other possible classifiers used by the systems and methods described herein include, for example, decision tree learning, association rule learning, artificial neural networks, inductive logic programming, random forests, gradient boosting methods, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, and sparse dictionary learning.”), the translation module assessing the translation quality of the translation candidates by using a utility function to assign a translation score to each one of the translation candidates (Bojja, para. 0019 “receiving from the at least one classifier a proposed set of candidate emoji and second confidence scores, each second confidence score being associated with a different candidate emoji in the proposed set and representing a likelihood that the user may wish to insert the associated candidate emoji into the communication;”), and the translation module including only the translation candidate with the best utility score in the translated word selection (para. 0022 “In some instances, inserting the at least one of the candidate emoji includes identifying a best emoji having a highest second confidence score in the proposed set of candidate emoji.”).
Regarding claim 6, Bojja in view of Schmid and Edge discloses wherein the utility function considers one or more of the following aspects: guessability of the meaning of a given translation candidate to the user, length of the given translation candidate, user’s familiarity with a given translation candidate, and user’s previous exposure to a given translation candidate (Bojja, para. 0012 “In some examples, the first confidence scores and/or the second confidence scores can be based on a user preference, a linguistic domain, demographic information, prior usage of emoji by at least one of the user and a community of users, and/or prior usage of emoji in prior communications having at least one of a word, a phrase, a context, and a sentiment in common with the communication.”).
Regarding claim 11, Bojja in view of Schmid and Edge discloses wherein the displayed input text element as translated comprises the word selection that is used to obtain the respective set of graphical symbols included in the translated word selection (Bojja, para. 0029 “In general, systems and methods described herein can be used to suggest emoji to users for insertion into content or to replace one or more portions of the content.”).
Regarding claim 12, Bojja in view of Schmid and Edge discloses wherein the translated word selection replaces in the displayed input text element as translated the word selection that is used to obtain the respective set of graphical symbols (Bojja, para. 0029 “In general, systems and methods described herein can be used to suggest emoji to users for insertion into content or to replace one or more portions of the content.”).
Regarding claim 13, Bojja in view of Schmid and Edge discloses wherein the translated word selection is only displayed by the display module to the user if a given action is triggered (Bojja, para. 0033 “The emoji can be inserted into the communication automatically and/or be selected by the user for insertion. The inserted emoji can replace one or more words or phrases in the communication.”).
Regarding claim 15, Bojja in view of Schmid and Edge discloses wherein graphical symbols are emojis (Bojja, para. 0029 “In general, systems and methods described herein can be used to suggest emoji to users for insertion into content or to replace one or more portions of the content.”).
Regarding claim 16, Bojja in view of Schmid and Edge discloses wherein in addition to the context, the dynamic translation of the word selection by the translation module considers one or more of the following aspects: user's age, user's nationality, user's geographical location, time of the day, user's cultural background, and user's language skills (Bojja, para. 0068 “Depending on the classifier(s) in use, the classifiers can also receive as input the current cursor position, a word or phrase in the user message, a previous message or previous content sent or received by a user, user preferences, and/or user demographic information.”; para. 0032 “The user information 128 database may include demographic information (e.g., age, race, ethnicity, gender, income, residential location, etc.)…”).
Regarding claim 17, claim 17 is a non-transitory computer program product which recites “the steps of the method according to claim 1”, and is thus rejected under similar rationale as method claim 1.
Additionally, Bojja discloses A non-transitory computer program product comprising instructions for implementing (para. 0019 “In another aspect, the subject matter described in this specification can be embodied in an article. The article includes a non-transitory computer-readable medium having executable instructions”) the steps of the method according to claim 1 (see above claim mapping for claim 1) when loaded and run on computing means of a data processing device (para. 0019 “The executable instructions are executable by one or more processors to perform operations including…”).
Regarding claim 18, claim 18 is an apparatus claim with limitations similar to those recited in method claim 1, and is thus rejected under similar rationale.
Additionally, Bojja discloses An apparatus for translating an input text element into a sequence of characters comprising a set of graphical symbols, the apparatus comprising…(Fig. 1, 112).
Regarding claim 19, claim 19 is rejected for analogous reasons to claim 2.
6. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Bojja in view of Schmid and Edge, and further in view of Bellegarda & Barman (US PGPUB No. 2018/0336184, hereinafter Bellegarda).
Regarding claim 4, Bojja in view of Schmid and Edge does not specifically disclose wherein the context of the respective selected word in the word selection comprises at least one word or sentence preceding the respective selected word and at least one word or sentence following the respective selected word
Bellegarda teaches wherein the context of the respective selected word in the word selection comprises at least one word or sentence preceding the respective selected word and at least one word or sentence following the respective selected word (para. 0220 “At block 906, a left word context s.sub.t is determined for each respective word w.sub.t of the word sequence…”; para. 0222 “At block 908, a right word context r.sub.t is determined for each respective word w.sub.t of the word sequence…”; para. 0224 “At block 910, a word-level feature representation h.sub.t is determined for each respective word w.sub.t of the word sequence. In particular, the word-level feature representation h.sub.t of a respective word w.sub.t is determined based on the left word context s.sub.t for the respective word w.sub.t and the right word context r.sub.t for the respective word w.sub.t.”; para. 0238 “At block 918, an emoji likelihood y.sub.t for the respective word w.sub.t is determined. In some examples, the emoji likelihood y.sub.t is determined based on the adjusted feature representation h.sub.t′ of the respective word (e.g., according to equation (14), described above).”).
Bojja, Schmid, Edge, and Bellegarda are considered to be analogous to the claimed invention as Bojja, Schmid, and Bellegarda are in the same field of translating words into graphical symbols, and Edge is in the same field of language learning. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bojja in view of Schmid and Edge to incorporate the teachings of Bellegarda in order to have the context contain at least one word or sentence preceding the respective selected word and at least one word or sentence following the respective selected word. Doing so would be beneficial, as capturing context of surrounding words can lead to suggesting emojis which are more likely to be congruent with the intended semantic meaning of the selected word (para. 0023-0031, Examples A-D).
7. Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Bojja in view of Schmid and Edge, and further in view of Gokhale et al. (US PGPUB No. 2024/0078374, hereinafter Gokhale).
Regarding claim 9, Bojja in view of Schmid and Edge does not specifically disclose wherein the method further comprises the translation module assessing the translation quality of the set of graphical symbols and if the translation quality is insufficient, then the system forming a feedback loop to select one or more other words out of the pre-processed text element to obtain one or more other word selections, the translation module translating the one or more other word selections into at least one or more other sets of graphical symbols, and once the translation quality of the respective set of graphical symbols is determined to be sufficient, only then including by the translation module the respective set of graphical symbols in the translated word selection.
Gokhale teaches wherein the method further comprises the translation module assessing the translation quality of the set of graphical symbols and if the translation quality is insufficient (para. 0067 “the system determines whether one or more conditions for causing the one or more emojis to be visually rendered for presentation to the user are satisfied. The one or more conditions may include, for example, whether confidence values associated one or more emotion classes that are predicted to correspond to the spoken utterance satisfy one or more confidence value thresholds”; para. 0068 “If, at iteration of block 362, the system determines that the one or more conditions are not satisfied, the system may proceed to block 366.”), then the system forming a feedback loop to select one or more other words out of the pre-processed text element to obtain one or more other word selections (para. 0070 “If, at an iteration of block 366, the system determines that additional spoken utterance is received, then the system may return to block 356, and may perform an additional iteration of the method 300 with respect to additional audio data that captures the additional spoken utterance.”; Fig. 3, step 356), the translation module translating the one or more other word selections into at least one or more other sets of graphical symbols (para. 0070 “Notably, in identifying one or more additional emojis at an additional iteration of the method 300, the system may make this identification independent of any emojis identified at the prior iteration of the method 300.”; Fig. 3, step 360), and once the translation quality of the respective set of graphical symbols is determined to be sufficient, only then including by the translation module the respective set of graphical symbols in the translated word selection (para. 0067 “If, at iteration of block 362, the system determines that the one or more conditions are satisfied, the system may proceed to block 364. At block 364, the system causes the one or more emojis to be visually rendered for presentation to the user via the display of the client device (e.g., as described with respect to, for instance, the examples of FIGS. 4A-4E and 5A-5B). The system may proceed to block 366. Block 366 is described in more detail below.”).
Bojja, Schmid, Edge, and Gokhale are considered to be analogous to the claimed invention as Bojja, Schmid, and Gokhale all in the same field of translating text into graphical symbols, and Edge is in the same field of language learning. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bojja in view of Schmid and Edge to incorporate the teachings of Gokhale in order to a feedback loop which assesses the a translation quality of the set of graphical symbols predicted, and only include the set of graphical symbols in the translated word selection when the translation quality is sufficient. Doing so would be beneficial, as this would ensure that only quality and meaningful translations are presented to the user, improving user experience.
8. Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Bojja in view of Schmid, Edge and Gokhale, and further in view of Zheng et al. (NPL Judging LLM-as-a-judge with MT-Bench and Chatbot Arena, hereinafter Zheng).
Regarding claim 10, Bojja in view of Schmid, Edge, and Gokhale does not specifically disclose wherein the translation quality is assessed by an artificial intelligence engine configured to simulate a human reader.
Zheng discloses wherein the translation quality is assessed by an artificial intelligence engine configured to simulate a human reader (pg. 4, section 3.1 “Single answer grading. Alternatively, an LLM judge is asked to directly assign a score to a single answer…”; pg. 13, Fig. 6 in Appendix, prompt given for model to evaluate quality of a response, judging on factors such as “helpfulness” simulates human reader).
Bojja, Schmid, Edge, and Gokhale, and Zheng are considered to be analogous to the claimed invention as Bojja, Schmid, and Gokhale are all in the same field of translating text into graphical symbols, Edge is in the same field of language learning, and Zheng is in the same field of evaluating quality of AI output using artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have to incorporate the teachings of Zheng in order to a have the translation quality be measured by an artificial intelligence engine configured to simulate a human reader. Doing so would be beneficial, as utilizing artificial intelligence models as a judge for quality provides benefits of scalability and explainability (pg. 4, section 3.2).
9. Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Bojja in view of Schmid and Edge and further in view of NPL Document 1 (MouseTooltipTranslator, hereinafter NPL1).
Regarding claim 14, Bojja in view of Schmid and Edge discloses a user performing the given action to obtain the respective set of graphical symbols included in the translated word selection (Bojja, para. 0033 “The emoji can be inserted into the communication automatically and/or be selected by the user for insertion. The inserted emoji can replace one or more words or phrases in the communication.”). However, Bojja in view of Schmid and Edge does not specifically disclose:
[wherein the given action comprises] detection by the system that the user hovers a cursor above the word selection that is used [to obtain the respective set of graphical symbols included in the translated word selection].
NPL1 discloses wherein the given action comprises detection by the system that the user hovers a cursor above the word selection that is used (pg. 1 “Mouse over to translate using google translate. When mouse hover on text, it shows translated tooltip in any desired language.”; pg. 1, first image translates hovered words in Japanese into a translated language (English), second image translates hovered words in English into a translated language (Korean)).
Bojja, Schmid, Edge, and NPL1 are considered to be analogous to the claimed invention as Bojja, Schmid, and NPL1 are all in the same field of translating text, and Edge is in the same field of language learning. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modified Bojja in view of Schmid and Edge to incorporate the teachings of NPL1 in order to specifically have the given action comprise hovering a cursor over the word selection to show the graphical symbol translation. Doing so would be beneficial, as the given action would allow the user to choose which translations they wish to see at a given moment while preserving the original language for the rest of the text, which avoids providing unwanted translations to the user, further improving user experience.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Patel (US 2017/0308290 A1): generating candidate emojis suggests for chat messaging (Fig. 1A-D)
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/CODY DOUGLAS HUTCHESON/Examiner, Art Unit 2659
/PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659
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