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 .
Application Status
Present office action is in response to the preliminary amendment filed 06/25/2025. Claims 1-21 are cancelled. Claims 22-42 are added and currently pending in the application.
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 22-42 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1: Statutory Category?
Independent claims 22, 30 and 40 respectively recites “a computing system” (i.e., a “machine”), “a computer-implemented method” (i.e. a process), and “a non-transitory computer-readable storage medium” (i.e., a “manufacture”). As such, independent claims 22, 30 and 40 are each directed to a statutory category of invention within § 101, i.e., machine, process, and manufacture. (Step 1: YES).
Step 2A – Prong 1: Judicial Exception Recited?
Independent claim 30, analyzed as representative of the claimed subject matter, is reproduced below. The limitations determined to be abstract ideas are shown in italics. The additional element(s) recited at a high level of generality are shown in bold. The limitation(s) determined to be extra-solution activity are underlined.
A computer-implemented method for interactive language learning, the method comprising:
[L1] causing a prompt to be presented to a user that is associated with a native language via a computing device, the prompt instructing the user to speak a word or a phrase in a non-native language;
[L2] receiving speech data from the user that is responsive to the prompt, the speech data representing the word or the phrase in the non-native language as spoken by the user;
[L3] converting the speech data into text data, the text data comprising a set of characters indicative of the word or the phrase in the non-native language as spoken by the user;
[L4] generating an evaluation of the speech data received from the user by generating a comparison of the set of characters to an anticipated set of characters; and
[L5] causing audible feedback to be presented to the user based on the evaluation of the speech data via the computing device.
It is common practice for a human, such as a language instructor, as part of a teaching activity to verbally and/or in writing interact with another human, such as a language learner, to prompt the learner, receive aural response to the prompt from the learner, convert/transcribe the learner’s speech response to text, evaluate the learner’s response based on comparison to expected responses and provide aural feedback to the learner based on the evaluation. Thus, other than reciting the “computing device” additional non-abstract element in representative independent claim 30 above, under the broadest reasonable interpretation, at least the italicized claim limitations may be performed in the human mind, including observations, evaluations, and judgments and may also be characterized as a certain method of organizing human activity, i.e., managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Accordingly, the claim recites an abstract idea under Step 2A: Prong 1. (Step 2A – Prong 1: YES).
Step 2A – Prong 2: Integrated into a Practical Application?
The computer component(s), namely the “computing device” is recited at a high level of generality (see originally filed Specification, at least ¶ 6: … a system for interactive language learning includes an audio input device, an audio to text converter coupled to the audio input device, a processor coupled to the audio to text converter, a predetermined set of instructions on a storage medium and readable by the processor, a speech generator coupled to the processor, and an audio output device coupled to the speech generator …; ¶ 13: one or more processors executing instructions stored on a computer-readable medium. The computer-readable medium may include permanent memory storage devices, such as computer hard drives or servers. Examples of machines and devices that utilize processors, memory, and instructions stored on computer-readable mediums include, but are not limited to, servers, computers, mobile devices, such as cellular telephones, and terminals …; ¶ 15: Audio input device 12 may be any suitable transducer configured to convert audio signals to a corresponding input electrical signal, such as one or more microphones. Audio input device 12 may optionally include audio enhancing features in hardware and/or software form such as audio processors, noise limiters, compressors, equalizers, amplifiers, and filters. The input electrical signal may be in any analog or digital form readable by audio to text converter 14, and may be stored as an audio file in a suitable storage medium; ¶ 17: Processor 16 may be any suitable type of computing device including, without limitation, one or more central or distributed microprocessors, microcontrollers, or computers. Processor 16 may be implemented in dedicated hardware, software operated on a generic platform, or a combination of hardware and software; ¶ 22: …one or more of: servers; computers; mobile devices such as cellular telephones; vehicle audio and entertainment systems; “smart” speakers; “smart” televisions and other “smart” appliances; augmented reality (AR), virtual reality (VR) and cross reality (XR) devices such as goggles, headsets, glasses and other wearable intelligence; and terminals. In some embodiments of the present invention some portions of system 10 may be located remotely from the others; ¶ 28: The user may interact with system 10 using either voice commands via audio input device 12 and/or any suitable user input device 26 (FIG. 1). User input device 26 may include, without limitation, one or more switches, keyboards, and programmed touch screens with programmed key inputs and one or more menus … The lack of details about the “computing device” indicates that the additional element(s) is/are generic, or part of generic computer elements performing or being used in performing the generic functions claimed. The claim does not change the way in which the recited “computing device” performs its tasks, it simply uses this component for its ordinary purpose to carry out the abstract idea of interactive language learning. The claim does not recite (i) an improvement to the functionality of a computer or other technology or technical field (see MPEP § 2106.05(a)); (ii) a “particular machine” to apply or use the judicial exception (see MPEP § 2106.05(b)); (iii) a particular transformation of an article to a different thing or state (see MPEP § 2106.05(c)); or (iv) any other meaningful limitation (see MPEP § 2106.05(e)). See 84 Fed. Reg. at 55. The claimed invention merely implements the abstract idea using instructions executed on generic computer components, as shown in bold above, and as supported in the above noted pertinent portions of the Specification. The instant claim merely uses a programmed computer as a tool to perform an abstract idea. See MPEP § 2106.05(f). The additional limitations [L1] (“causing a prompt to be presented”, i.e., data presentation), [L2] (“receiving speech data”, i.e., data gathering), [L3] (“converting the speech data into text data”, i.e., data gathering), and [L5] (“causing audible feedback to be presented to the user”, i.e., data presentation) reflect the type of extra-solution activity (i.e., in addition to the judicial exception) the courts have determined insufficient to transform judicially excepted subject matter into a patent-eligible application when they are claimed in a merely generic manner. See MPEP § 2106.05(g); see In re Bilski, 545 F.3d at 963 (characterizing data gathering steps as insignificant extra-solution activity); see also Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat’l Ass’n, 776 F.3d 1343, 1347 (Fed. Cir. 2014) (determining that claims drawn to collecting data, recognizing certain data within the collected set, and storing the recognized data were patent ineligible, noting that “humans have always performed these functions”); see also Mayo, 566 U.S. at 72–73; OIP Techs. v. Amazon.com, 788 F.3d 1359, 1363(Fed. Cir. 2015) (presenting offers to potential customers, gathering statistics generated based on the testing about how potential customers responded to the offers, and using statistics to calculate an optimized price are merely data gathering steps). The instant claim as a whole merely uses computer instructions to implement the abstract idea on a computer or, alternatively, merely uses a computer as a tool to perform the abstract idea. The claim limitations amount to merely indicating a field of use or technological environment (a computer) in which to apply a judicial exception and, as such, cannot integrate the judicial exception into a practical application. See MPEP § 2106.05(h). Hence, as per MPEP §§ 2106.05(a)–(c), (e)–(h), the additional element in claim 30, namely the “computing device” does not, either individually or in combination, integrate the abstract idea into a practical application. Because the abstract idea is not integrated into a practical application, the claim is directed to the judicial exception. (Step 2A, Prong 2: NO).
Step 2B: Claim provides an Inventive Concept?
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies here in Step 2B, i.e., mere instructions to apply an exception using generic computer components cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The fact that the Specification does not further describe the “computing device” indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional element to satisfy 35 U.S.C. § 112(a). See MPEP 2106.05(d), as modified by the USPTO Berkheimer Memorandum. Hence, the additional element(s) is/are generic, well-understood, routine, and conventional computing element(s). The use of the additional element either alone or in combination amounts to no more than mere instructions to apply the judicial exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept, and thus the claim is patent ineligible. (Step 2B: NO).
In regard to independent Claim 22:
Independent claim 22 recites a computing system for interactive language learning, the system comprising: memory comprising instructions; and a processor configured to execute the instructions to perform steps comparable to those of representative claim 30. Accordingly, independent claim 22 is rejected similarly to representative claim 30.
In regard to independent Claim 40:
Independent claim 40 recites a non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processor, cause the processor to perform steps comparable to those of representative claim 30. Accordingly, independent claim 40 is rejected similarly to representative claim 30.
In regard to the dependent claims:
Dependents claims 23-29, 31-39 and 41-42 include all the limitations of corresponding independent claims 22, 30 and 40 from which they depend and, as such, recite the same abstract idea(s) noted above for corresponding independent claims 22, 30 and 40. The dependent claims do not appear to remedy the issues noted above.
Any additional claim element is recited as being used according to its conventional purpose in a conventional manner. The Examiner fails to see any claim activity used in some unconventional manner nor does any produce some unexpected result. An invocation to use known technology in the manner it is intended to be used for its ordinary purpose is both generic and conventional. As per MPEP §§ 2106.05(a)–(c), (e)–(h), none of the limitations of claims 23-29, 31-39 and 41-42 integrates the judicial exception into a practical application. While dependent claims 23-29, 31-39 and 41-42 may have a narrower scope than the representative claims, no claim contains an “inventive concept” that transforms the corresponding claim into a patent-eligible application of the otherwise ineligible abstract idea(s). Therefore, dependent claims 23-29, 31-39 and 41-42 are not drawn to patent eligible subject matter as they are directed to (an) abstract idea(s) without significantly more.
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) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
Claims 22, 28-30 and 36-40 are rejected under 35 U.S.C. 103 as obvious over ASH et al. (US 20180315420 A1) (ASH).
Re claims 22, 30 and 40:
[Claim 30] ASH discloses a computer-implemented method for interactive language learning (at least ¶ 1: … assessing the fluency and proficiency of a user's spoken dialogue in a given language), the method comprising: causing a prompt to be presented to a user that is associated with a native language via a computing device, the prompt instructing the user to speak a word or a phrase in a non-native language; receiving speech data from the user that is responsive to the prompt, the speech data representing the word or the phrase in the non-native language as spoken by the user (at least ¶ 4: an input for receiving an input utterance spoken by a user in response to a read prompt text); converting the speech data into text data, the text data comprising a set of characters indicative of the word or the phrase in the non-native language as spoken by the user (at least ¶ 7: … a speech recognition system that recognises the input utterance spoken by the user and that outputs a recognition result comprising a sequence of recognised words and sub-word units corresponding to the input utterance …); generating an evaluation of the speech data received from the user by generating a comparison of the set of characters to an anticipated set of characters; and causing feedback to be presented to the user based on the evaluation of the speech data via the computing device (at least ¶ 7: … a word alignment unit configured to receive the sequence of recognised words and sub-word units output by the speech recognition system and to align a sequence of said acoustic speech models corresponding to the received sequence of recognised words and sub-word units with the input utterance spoken by the user and to output an alignment result identifying a time alignment between the received sequence of recognised words and sub-word units and the input utterance spoken by the user …; ¶ 10: maintain a score representing the closeness of the match between the acoustic speech models for the different paths defined by the second network and the input utterance spoken by the use; ¶ 17: A scoring unit may also be provided that receives the plurality of speech scoring feature values for the input utterance determined by the speech scoring feature determining unit and that generates a score representing the language ability of the user. Typically, the score represents the fluency and/or proficiency of the user's spoken utterance; ¶ 17: speech features are then used to determine a score representing the user's fluency and/or proficiency in the language being assessed (in this case English). The score can be determined in substantially real time—so that the user can be marked and graded immediately; ¶ 192: scoring unit 35 will output a score defining the system's assessment of that user's input speech. This automatically determined assessment can then be fed-back instantly to the user just after they have input their spoken utterance).
The feedback presented being audible would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention because a person of ordinary skill has good reason to pursue the known options within his or her grasp. If this leads to the anticipated success, it is likely the product not of innovation but of ordinary skill and common sense.
[Claim 22] The claim is a computing system for interactive language learning, the system comprising: memory comprising instructions; and a processor configured to execute the instructions to perform steps comparable to those of representative claim 30. Accordingly, independent claim 22 is rejected for reasons similar to those previously explained when addressing representative claim 30.
[Claim 40] The claim is a non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processor, cause the processor to perform steps comparable to those of representative claim 30. Accordingly, independent claim 40 is rejected for reasons similar to those previously explained when addressing representative claim 30.
Re claims 28-29 and 36-39:
[Claims 28 and 36] ASH may not explicitly disclose a representation of how the speech data representing the word or the phrase in the non-native language as spoken by the user would be perceived by a native speaker of the non-native language. However, ASH (¶¶ 15, 181-185) discloses “first language model is trained using text output from the speech recognition system in response to input speech spoken by users having a first ability of the language, the second language model is trained using text output from the speech recognition system in response to input speech spoken by users having a second ability of the language, the second ability being greater than the first ability and the third language model is trained using text output from the speech recognition system in response to input speech spoken by users having a third ability of the language, the first ability being greater than the third ability”; ““good level” LM that is trained on the output from the ASR system 37 obtained by processing the speech of students that are considered to have good fluency and proficiency of the language being assessed”; ““medium level” LM that is trained on the output from the ASR system 37 obtained by processing the speech of students that are considered to have a medium fluency and proficiency of the language being assessed”: ““bottom level” LM that is trained on the output from the ASR system 37 obtained by processing the speech of students that are considered to have poor fluency and proficiency of the language being assessed”. In view of the above, modifying ASH as claimed would have been an obvious matter of choice.
[Claims 29 and 37] ASH may not explicitly disclose wherein the prompt comprises a first audible presentation of the word or phrase in the native language followed by a second audible presentation of the word or phrase in the non-native language and a third audible presentation of the word or phrase in the non-native language. However, it is common knowledge that language instructors may question learners in any desired fashion deemed to facilitate the learner to respond to the question. Therefore, it would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date of the invention, to have modified ASH as claimed because this would amount to no more than applying known techniques to a known method (device, or product) ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007) (“The combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.”).
[Claim 38] ASH discloses wherein the audible feedback indicates that the evaluation of the speech data is that the speech data is correct, partially correct, or incorrect (at least ¶ 17: speech features are then used to determine a score representing the user's fluency and/or proficiency in the language being assessed (in this case English). The score can be determined in substantially real time—so that the user can be marked and graded immediately; ¶ 66: if the user's pronunciation of a word is incorrect, then the phoneme alignment unit 25 will detect this …; ¶ 192: scoring unit 35 will output a score defining the system's assessment of that user's input speech. This automatically determined assessment can then be fed-back instantly to the user just after they have input their spoken utterance).
Alternatively, in the event the above interpretation is viewed as not being reasonable, because scoring implies determining a degree of correctness, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified ASH as claimed, because a person of ordinary skill has good reason to pursue the known options within his or her grasp. If this leads to the anticipated success, it is likely the product not of innovation but of ordinary skill and common sense.
[Claim 39] ASH may not explicitly disclose wherein the computing device comprises a virtual reality headset. However, a virtual reality headset is one of many commercially available computing devices. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified ASH as claimed, because a person of ordinary skill has good reason to pursue the known options within his or her grasp. If this leads to the anticipated success, it is likely the product not of innovation but of ordinary skill and common sense.
Claims 23-25, 31-33 and 41-42 are rejected under 35 U.S.C. 103 as obvious over ASH, as applied to claims 22, 30 and 40 above, in view of Egnor (US 5180309 A).
Re claims 23-25, 31-33 and 41-42:
[Claims 23-25, 31-33 and 41-42] ASH discloses “a word alignment unit … to maintain matching scores for the alignments between the different sequences of acoustic speech models with the input utterance spoken by the user” and “a sub-word alignment unit … that receives the sequence of sub-word units corresponding to the dictionary pronunciation, that determines where the input utterance spoken by the user differs from the dictionary pronunciation and that outputs a sequence of sub-word units corresponding to an actual pronunciation of the input utterance spoken by the user” (at least ¶¶ 6-13). In view of the above, it is apparent that pronunciation comparison of “utterance spoken by the user” (non-native language) and “dictionary pronunciation” (native language) illustrates an evaluation that depends on the native language and the non-native language. ASH appears to be silent on but Egnor which relates to automated evaluation and scoring (abstract) teaches or at least suggests wherein generating the evaluation of the speech data received from the user comprises determining a number of incorrect characters in the set of characters based on the comparison, ([Claims 24, 32 and 42]) wherein generating the evaluation of the speech data received from the user is based on the number of incorrect characters in the set of characters and a total number of characters in the set of characters, ([Claims 25 and 33]) wherein generating the evaluation of the speech data received from the user is based on a tolerance value that depends on the native language and the non-native language (at least col 3, lines 2-10: For each question in Question.Dat there is a corresponding answer in Answer.Dat. Each answer in Answer.Dat contains within its 128 characters one or more characters that designate a tolerance which is used to evaluate a partially correct answer by the player. If the strings match exactly in the character by character comparison of the player's answer to the answer in Answer.Dat, full value is given for the answer. If only some of the characters match, partial credit will be awarded if the percentage of correct characters to total characters is within the tolerance for that answer. For example, if the designated tolerance is 0.6 then partial credit will be awarded for a partially correct answer if at least sixty percent of the characters in the player's answer match the characters in the answer found in Answer.Dat). Therefore, it would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date of the invention, to have used the character by character comparison and answer tolerance features of Egnor and to have modified ASH as claimed because this would amount to no more than applying known techniques to a known method (device, or product) ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007) (“The combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.”).
Claims 26-27 and 34-35 are rejected under 35 U.S.C. 103 as obvious over ASH in view of Egnor, as applied to claims 25 and 33 above, further in view of Thornton, II (US 20150019973 A1) (Thornton).
Re claims 26-27 and 34-35:
[Claims 26-27 and 34-35] ASH in view of Egnor appears to be silent on but Thornton teaches or at least suggests causing a second prompt to be presented to the user via the computing device responsive to determining that the number of incorrect characters in the set of characters satisfies a condition, the second prompt instructing the user to speak a second word or a second phrase in the non-native language that is different from the word or phrase in the non-native language (at least ¶ 10: to provide feedback, the system compares the selected discrete portion with content received from the user, and calculates a percentage accuracy. The percentage accuracy is compared with the threshold accuracy chosen by the user; ¶ 14: permit the user to set an accuracy threshold for when the user repeats the content; ¶¶ 23-25: Step 11) If the accuracy threshold is: a) satisfied, then the method presents a second discrete portion of the content and repeats steps 5-10 with the additional content, or the method ends if no more content is available), ([Claims 27 and 35]) causing the prompt to be presented to the user a second time via the computing device responsive to determining that the number of incorrect characters in the set of characters does not satisfy the condition; (at least ¶¶ 23-25: Step 11) If the accuracy threshold is: … b) not satisfied, then steps 4-10 are repeated until the accuracy threshold is satisfied).
It is apparent that similarly to the claimed invention, ASH in view of Egnor and Thornton discloses presenting a different prompt if the condition is satisfied and repeating a same prompt if the condition is not satisfied. The claimed “set of characters divided by the tolerance value” represents calculating a percent tolerance. Thus, the claimed prompt conditions are associated with the percent tolerance. Because “[Th]e percentage accuracy is compared with the threshold accuracy”, the prior art prompt conditions are associated with the percentage accuracy. Subsequently, the only difference between the prior art and the instant claims is the use of percent tolerance instead of percentage accuracy. Since ASH in view of Egnor and Thornton’s discloses determining answer tolerance, it would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date of the invention, to have modified ASH in view of Egnor and Thornton as claimed because this would amount to no more than substituting one known element (percent tolerance) for another (percentage accuracy) to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007) (“a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable result.”).
Conclusion
The prior art made of record and not relied upon is listed in the attached PTO
Form 892 and is considered pertinent to applicant's disclosure.
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/EDDY SAINT-VIL/Primary Examiner, Art Unit 3715