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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 09/08/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/08/2026 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims 32-38 and 40-53 under 35 U.S.C. § 103 in view of MacFarland and Waibel have been considered but are moot because of the new ground of rejection in view of MacFarland and Leydon for claims 32-35, 37 and 40-50 and 52-53; and MacFarland, Leydon and Waibel for claims 36, 38 and 51. In response to the arguments presented by the applicant, Leydon does explicitly teach the “high-risk word” as recited in the claim and as described in the specification, at least in cited p. 0077. Thus, the claims are rejected accordingly, as discussed in the rejections below.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “an automatic speech recognition module” “a language translation module” “a correction module” in claims 32-46.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claims 32-35, 37 and 40-50 and 52-53 are rejected under 35 U.S.C. 103 as being unpatentable over McFarland (US PG Pub 20090037171) in view of Leydon (US PG Pub 20110307241).
As per claims 32 and 47, McFarland discloses: A system and method (McFarland; p. 0033 & p. 0072) comprising: one or more processors (McFarland; p. 0058 – microphone array processor 520 & speaker identification processor 530; p. 0060 - features extraction processor 535; p. 0063 - text language processor 592) configured to execute processor-executable instructions stored in a non-transitory computer-readable medium (McFarland; p. 0048-0049 - Software implementing the procedures, systems and methods described herein can be stored in the memory of any computer system as a set of executable instructions…), the processor-executable instructions comprising: an automatic speech recognition module to receive audible output in a first human language from a speaker during an audio session (McFarland; p. 0034-0035 - Transcription software may execute in server 25 and takes audio input from at least one microphone 15 via noise filter 20… the software can determine who is speaking by the connection of the microphone and/or by the volume level of that microphone; see also p. 0045) and convert the audible output to transcribed text in the first human language (McFarland; p. 0034-0035 - Multiple voice recognition profiles can be simultaneously executed in the server 25 while immediately translating the spoken word to text); and a language translation module for translating the transcribed text in the first human language to translation text in a second human language (McFarland; p. 0063 - according to language decision module 585 if a language conversion is needed, the original output is saved at step 590 and text to text language processor 592 converts a copy of the original output to the target language upon which text to speech converter 594 outputs to a selected output device 596; see also p. 0072 - The system 10 can accept language translation commands and will translate from one language to another as required. The audio/video and transcript are synchronized files stored on a hard disk of the computer processing the voice translation and also on the remote computers if the option is selected); a correction module in communication with one or more client devices (McFarland; p. 0043 - The edit mode 315 provides a command interface, inclusion of presets, templates, text, and a spell checker. Additionally, in the edit mode 315, text can be highlighted and the audio/video can be played back, A dictionary can be edited wherein words can be added. Speech converted to text can be formatted and printed; see also p. 0037, 0040, 0054-0055 & 0071), wherein the correction module: receives corrective inputs, wherein the corrective inputs comprise corrections to at least one of the transcribed text in the first language or the translated text in the second human language (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 & p. 0070); and updates at least one of the automatic speech recognition module or the language translation module based on the received corrected inputs, such that the automatic speech recognition module or the language translation module uses the corrective inputs in generating the transcribed text in the first human language or translating the transcribed text to the second human language for a remainder of the audio session (McFarland; p. 0037 - A court reporter/computer operator is given the opportunity to edit the transcription, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0056 - The system allows the user to see the text, and edit the same in real time and the user is able to define unrecognized voice, which will be used for subsequent translation; see also p. 0066 - the system accepts operator input of corrections to the translation, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070 - While real time is taking place, a court reporter/computer operator, can make corrections and define incorrect voice translations and have those corrections apply to all future translations. The corrections only apply to the profile/dictionary that was opened at that particular point in the transcript. As corrections are made and parentheticals (unspoken text) are inserted by the court reporter/computer operator, the system 10 can refresh each connected computer accordingly. The system 10 has a list of all parentheticals, which can be selected for automatic insertion in the transcript).
McFarland, however, fails to disclose wherein the language translation module is configured to, during the audio session; identify a high-risk word in the translated text in the second human language flag the high-risk word in the display of the translated text; and update at least one of the automatic speech recognition module or the language translation module based on the received corrected inputs for the high-risk word.
Leydon does teach wherein the language translation module is configured to, during the audio session: identify a high-risk word in the translated text in the second human language based on a predefined set of high-risk words; flag the high-risk word in a display of the translated text; and update at least one of the automatic speech recognition module or the language translation module based on the received corrected inputs for the high-risk word (Leydon; p. 0077 - The profanity module 316 may be configured to identify one or more profane words or phrases (hereafter, referred to as a “profanity” (high-risk word)) in a chat message, and may be further configured to suggest replacement words or phrases (e.g., suitable substitute) corresponding to the profanity (e.g., a toned down euphemism). In some embodiments, the profanity module 316 may flag identified profanity to be skipped or otherwise ignored during a subsequent machine translation (e.g., by the translation module 116). Additionally, in some embodiments, identified profanity may be flagged for later review and disposition by a human operator (e.g., an administrator of the CTT system 114). In order to identify profanity and/or its corresponding word or phrase, some embodiments may utilize a dataset (predefined set of high risk words) (e.g., stored on a data store) comprising profanity and/or mappings between abbreviations and their corresponding words and phrases. The dataset may be constructed by way of training or a learning system, may be proprietary (e.g., manually collected “in-house” by an administrator of the CTT system 114), may be commercially acquired, or may be derived from a publicly available Internet knowledgebase. The result from the profanity module 316 may comprise profanity flagged by the profanity module 316 to be ignored, a suggested replacement, or a word or phrase inserted into the message by the profanity module 316 (e.g., in place of the identified profanity). Depending on the embodiment, the message that results from the profanity module 316 may be provided to another transformation module (in the transformation module 208) for further processing or the suggested replacement may be provided to the CTT control module 202 to determine if the message transformed by the profanity module 316 is in the data store 210).
Therefore, it would have been obvious to one of ordinary skill in the art to modify the system and method of McFarland to include wherein the language translation module is configured to, during the audio session: identify a high-risk word in the translated text in the second human language based on a predefined set of high-risk words; flag the high-risk word in a display of the translated text; and update at least one of the automatic speech recognition module or the language translation module based on the received corrected inputs for the high-risk word, as taught by Leydon, in order to improve translation in a multi-lingual multi-user chat system associated with an online game (e.g., in-game chat system) (Leydon; p. 0007). As per claims 33 and 48, McFarland in view of Leydon discloses The system and method of claims 32 and 47, wherein: the audio session comprises a live audio session by the speaker (McFarland; p. 0007 - The real-time voice transcription system provides a speech recognition system and method that includes use of speech and spatial-temporal acoustic data to enhance speech recognition probabilities while simultaneously identifying the speaker), and generating the transcribed text in the first human language and to translate the transcribed text to the translation text in the second human language during the live audio session (McFarland; p. 0035 - The system 10 is capable of transcribing a single voice for captioning for deaf students and television news broadcasts as well as inputs from multiple voices. Real time translation and editing of the real time text for immediate delivery of transcription is provided by the system 10; see also p. 0054-0055 - The system 10 can transcribe multiple voices even when spoken concurrently at different microphones 15 and identify each speaker separately as the voices are buffered within the computer 25. Multiple channels may be used for this feature. Another option can be to select that all participants are translated and displayed on the screen with a space between each participant when more then one speak at the same time. When one participant stops speaking, the blank space between speakers automatically disappears. The text is in different colors for each speaker making it immediately apparent who is speaking… The system 10 translates in real time and displays the text in an interface that allows for a court reporter/computer operator to edit the translation as it is taking place). As per claims 34 and 49, McFarland in view of Leydon discloses: The system and method of claims 33 and 48, wherein: the one or more client devices are configured to, during the live audio session, display the translated text and accept the corrective inputs; and the speech recognition and translation computer system is configured to, during the live audio session, receive the corrective inputs and update the language translation module (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0055 - The system 10 translates in real time and displays the text in an interface that allows for a court reporter/computer operator to edit the translation as it is taking place; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070-0071 - While real time is taking place, a court reporter/computer operator, can make corrections and define incorrect voice translations and have those corrections apply to all future translations. The corrections only apply to the profile/dictionary that was opened at that particular point in the transcript. As corrections are made and parentheticals (unspoken text) are inserted by the court reporter/computer operator, the system 10 can refresh each connected computer accordingly… Each connected computer, such as computers 30 or computers 40 and 45 has the option of receiving a signal from the translating computer 25 or viewing the translated text on the computer processing the voice translations). As per claims 35 and 50, McFarland in view of Leydon discloses: The system and method of claims 34 and 47, wherein the language translation module is configured to, after receiving the corrective inputs from the users of the one or more client devices, update the translated text displayed on the user interface session to include, in a presentation mode, the corrective inputs (McFarland; p. 0037 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator, Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0070). As per claim 37, McFarland in view of Leydon discloses: The system of claim 32, wherein the language translation module is configured to, after the audio session, transfer the corrective inputs to a long term memory for the language translation module (McFarland; p. 0037 - if edits are received, the system 410 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0055 - The system 10 translates in real time and displays the text in an interface that allows for a court reporter/computer operator to edit the translation as it is taking place. When a new text is defined for a mistranslated or un-translated voice, this data is stored in a default rules or user selected rules file and, going forward, the translation will use the new definition; see also p. 0070 - While real time is taking place, a court reporter/computer operator, can make corrections and define incorrect voice translations and have those corrections apply to ail future translations). As per claim 40, McFarland in view of Leydon discloses: The system of claim 32, wherein the audio session comprises an audible voice dialog between the speaker with a second speaker (McFarland; p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings). As per claim 41, McFarland in view of Leydon discloses: The system of claim 32, wherein the audio session comprises a recording of audible output by the speaker (McFarland; p. 0073 - The transcription to be executed in a computer, PDA or other processing device with voice recording capability and transferred via hard wired/wireless network to a back office computer where it will be validated by a transcriber). As per claim 42, McFarland in view of Leydon discloses: The system of claim 32, wherein the recording comprises a multimedia recording (McFarland; p. 0039 - The system 10 is capable of broadcasting over the Internet 35 or using the Internet 35 to send audio and video to a remote site 40 or alternative remote site 45 for remote translation and/or editing and for remote viewing and listening; see also p. 0043 - The edit mode 315 provides a command interface, inclusion of presets, templates, text, and a spell checker, in the edit mode 315, text can be highlighted and the audio/video can be played back). As per claim 43, McFarland in view of Leydon discloses: The system of claim 33, wherein: in the editor mode, the user interface of the one or more client devices is further configured to: display the transcribed text in the first human language during the audio session (McFarland; p. 0037 - the voice is converted to text by using at least one lexicon adapted to the professor's speech, punctuation and formatting logic is applied to the transcribed speech and broadcast to students. A court reporter/computer operator is given the opportunity to edit the transcription; see also p. 0040 - The basic functionality of the system 10 is a voice recognition transcription system that displays text in a user-friendly interface; see also p. 0054 - The system 10 can transcribe multiple voices even when spoken concurrently at different microphones 15 and identify each speaker separately as the voices are buffered within the computer 25. Multiple channels may be used for this feature. Another option can be to select that all participants are translated and displayed on the screen with a space between each participant when more then one speak at the same time. When one participant stops speaking, the blank space between speakers automatically disappears. The text is in different colors for each speaker making it immediately apparent who is speaking; see also p. 0055 - The system 10 translates in real time and displays the text in an interface that allows for a court reporter/computer operator to edit the translation as it is taking place; see also p. 0071); and accept transcribed-text corrective inputs to the displayed transcribed text from the user of each of the one or more client device during the audio session (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); and the speech recognition and translation computer system is further configured to: receive the transcribed-text corrective inputs from the users of the one or more client devices during the audio session (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules fila and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); and update the automatic speech recognition module based on the received transcribed-text corrected inputs during the audio session, such that the automatic speech recognition module uses the transcribed-text corrective inputs in recognizing the audible output by the speaker ‘during the audio session (McFarland; p. 0037 - A court reporter/computer operator is given the opportunity to edit the transcription, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0056 - The system allows the user to see the text, and edit the same in real time and the user is able to define unrecognized voice, which will be used for subsequent translation; see also p. 0066 - the system accepts operator input of corrections to the translation, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070). As per claim 44, McFarland in view of Leydon discloses: The system of claim 43, wherein the speech recognition and translation computer system is further configured to, upon receiving a transcribed-text corrective input that is applicable to a portion of the transcribed text, re-translate the portion of the transcribed text to the second human language such that the user interfaces of the one or more client devices display the re-translated portion in the second human language (McFarland; p. 0070 - While real time is taking place, a court reporter/computer operator, can make corrections and define incorrect voice translations and have those corrections apply to all future translations. The corrections only apply to the profile/dictionary that was opened at that particular point in the transcript. As corrections are made and parentheticals (unspoken text) are inserted by the court reporter/computer operator, the system 10 can refresh each connected computer accordingly. The system 10 has a list of all parentheticals, which can be selected for automatic insertion in the transcript). As per claim 45, McFarland in view of Leydon discloses: The system of claim 32, further comprising: a storage for storing a recording of the audio session (McFarland; p. 0072 - The audio/video and transcript are synchronized files stored on a hard disk of the computer processing the voice translation and also on the remote computers if the option is selected); and audio output for audibly playing the recording of the audio session (McFarland; p. 0072 - The audio/video and transcript are synchronized files stored on a hard disk of the computer processing the voice translation and also on the remote computers if the option is selected. This makes it possible to select any portion of the text for playback when a participant in the proceedings asks for the record to be read back); wherein the system is configured to generate the transcribed text in the first human language (McFarland; p. 0033-0037 - Multiple voice recognition profiles can be simultaneously executed in the server 25 while immediately translating the spoken word to text… the system 10 can accept speech input from a lecturing professor, the voice is converted to text by using at least one lexicon adapted to the professor's speech, punctuation and formatting logic is applied to the transcribed speech…; see also p. 0045 - Microphone voice input 55 can be accepted by a voice link function 65. The voice link function 65 is also capable of accepting PCM formatted voice input 57 and WAV file input 60, The voice link 65 provides an interface between the aforementioned speech input types and the speech recognition layer 70, as well as the general utilities and database components layer 75. A plurality of speech recognition engines such as first SR engine 50 a and second SR engine 50b can be in operable communication with the speech recognition layer 70) and to translate the transcribed text to the translation text in the second human language during a playing of the recorded audio session (McFarland; p. 0063 - according to language decision module 585 if a language conversion is needed, the original output is saved at step 590 and text to text language processor 592 converts a copy of the original output to the target language upon which text to speech converter 594 outputs to a selected output device 596; see also p. 0072 - The system 10 can accept language translation commands and will translate from one language to another as required. The audio/video and transcript are synchronized files stored on a hard disk of the computer processing the voice translation and also on the remote computers if the option is selected); during the playing of the recorded audio session, cause the translated text to be displayed (McFarland; p. 0037 - the voice is converted to text by using at least one lexicon adapted to the professor's speech, punctuation and formatting logic is applied to the transcribed speech and broadcast to students, A court reporter/computer operator is given the opportunity to edit the transcription; see also p. 0040 - The basic functionality of the system 10 is a voice recognition transcription system that displays text in a user-friendly interface; see also p. 0054 - The system 10 can transcribe multiple voices even when spoken concurrently at different microphones 15 and identify each speaker separately as the voices are buffered within the computer 25. Multiple channels may be used for this feature. Another option can be to select that all participants are translated and displayed on the screen with a space between each participant when more then one speak at the same time. When one participant stops speaking, the blank space between speakers automatically disappears. The text is in different colors for each speaker making it immediately apparent who is speaking; see also p. 0055 & 0071) and accept the corrective inputs (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); and during the playing of the recorded audio session, receive the corrective inputs and update the language translation module (McFarland; p. 0037 - A court reporter/computer operator is given the opportunity to edit the ‘transcription, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0056 - The system allows the user to see the text, and edit the same in real time and the user is able to define unrecognized voice, which will be used for subsequent translation; see also p. 0066 & 0070). As per claim 46, McFarland in view of Leydon discloses: The system of claim 45, wherein the system is further configured to: display the transcribed text in the first human language during the playing of the recorded audio session (McFarland; p. 0037 - the voice is converted to text by using at least one lexicon adapted to the professor's speech, punctuation and formatting logic is applied to the transcribed speech and broadcast to students. A court reporter/computer operator is given the opportunity to edit the transcription; see also p. 0040 - The basic functionality of the system 10 is a voice recognition transcription system that displays text in a user-friendly interface; see also p. 0054 - The system 10 can transcribe multiple voices even when spoken concurrently at different microphones 15 and identify each speaker separately as the voices are buffered within the computer 25, Multiple channels may be used for this feature. Another option can be to select that all participants are translated and displayed on the screen with a space between each participant when more then one speak at the same time. When one participant stops speaking, the blank space between speakers automatically disappears. The text is in different colors for each speaker making it immediately apparent who is speaking; see also p. 0055 & 0071); and accept transcribed-text corrective inputs to the displayed transcribed text from the user of each of the one or more client device during the playing of the recorded audio session (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); and receive the transcribed-text corrective inputs from one or more client devices during the playing of the audio session (McFarland; p. 0034 - A court reporter/computer operator is given the opportunity to edit the transcription at step 811, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0066 - the system accepts operator input of corrections to the translation. At step 627, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); update the automatic speech recognition module based on the received transcribed-text corrected inputs during the playing of the recorded audio session, such that the automatic speech recognition module uses the transcribed-text corrective inputs in recognizing the audible output by the speaker during the playing of the recorded audio session (McFarland; p. 0037 - A court reporter/computer operator is given the opportunity to edit the transcription, if edits are received, the system 10 saves the corrections to a rules file and the voice engine will use the corrections for future translations; see also p. 0053 - The system 10 can transcribe dialogue in hearings, depositions, trials, and a plurality of other dialogue settings. During transcription, the system 10 accepts corrections of any unrecognized voice patterns in real time transmitted to it by a court reporter/computer operator. Once a particular pattern has been corrected in this manner, the software will automatically correctly transcribe the pattern for all subsequent occurrences; see also p. 0056 - The system allows the user to see the text, and edit the same in real time and the user is able to define unrecognized voice, which will be used for subsequent translation; see also p. 0066 - the system accepts operator input of corrections to the translation, responsive to the operator inputted corrections, the system updates the selected lexicon with the new definition; see also p. 0070); and upon receiving a transcribed-text corrective input that is applicable to a portion of the transcribed text, re-translate the portion of the transcribed text to the second human language such that the user interfaces of the one or more client devices display the re-translated portion in the second human language (McFarland; p. 0070 - While real time is taking place, a court reporter/computer operator, can make corrections and define incorrect voice translations and have those corrections apply to all future translations. The corrections only apply to the profile/dictionary that was opened at that particular point in the transcript. As corrections are made and parentheticals (unspoken text) are inserted by the court reporter/computer operator, the system 10 can refresh each connected computer accordingly. The system 10 has a list of all parentheticals, which can be selected for automatic insertion in the transcript).
As per claims 52 and 53, McFarland in view of Leydon disclose: The system and method of claims 32 and 47, upon which claims 52 and 53 depend. McFarland, however, fail to teach wherein the high-risk word comprises one of vulgar language, insults, sexist language, racist language, hate speech, politically or socially charged concepts and words.
Leydon does teach wherein the high-risk word comprises one of vulgar language, insults, sexist language, racist language, hate speech, politically or socially charged concepts and words (Leydon; p. 0077 - The profanity module 316 may be configured to identify one or more profane words or phrases (hereafter, referred to as a “profanity” (high-risk word)) in a chat message, and may be further configured to suggest replacement words or phrases (e.g., suitable substitute) corresponding to the profanity (e.g., a toned down euphemism). In some embodiments, the profanity module 316 may flag identified profanity to be skipped or otherwise ignored during a subsequent machine translation (e.g., by the translation module 116). Additionally, in some embodiments, identified profanity may be flagged for later review and disposition by a human operator (e.g., an administrator of the CTT system 114). In order to identify profanity and/or its corresponding word or phrase, some embodiments may utilize a dataset (e.g., stored on a data store) comprising profanity and/or mappings between abbreviations and their corresponding words and phrases. The dataset may be constructed by way of training or a learning system, may be proprietary (e.g., manually collected “in-house” by an administrator of the CTT system 114), may be commercially acquired, or may be derived from a publicly available Internet knowledgebase. The result from the profanity module 316 may comprise profanity flagged by the profanity module 316 to be ignored, a suggested replacement, or a word or phrase inserted into the message by the profanity module 316 (e.g., in place of the identified profanity). Depending on the embodiment, the message that results from the profanity module 316 may be provided to another transformation module (in the transformation module 208) for further processing or the suggested replacement may be provided to the CTT control module 202 to determine if the message transformed by the profanity module 316 is in the data store 210).
Therefore, it would have been obvious to one of ordinary skill in the art to modify the system and method of McFarland to include wherein the high-risk word comprises one of vulgar language, insults, sexist language, racist language, hate speech, politically or socially charged concepts and words, as taught by Leydon, in order to improve translation in a multi-lingual multi-user chat system associated with an online game (e.g., in-game chat system) (Leydon; p. 0007).
Claims 36, 38 and 51 are rejected under 35 U.S.C. 103 as being unpatentable over McFarland in view of Leydon and further in view of Waibel (US PG Pub 20110307241).
As per claims 36 and 51, McFarland in view of Waibel discloses: The system and method of claims 35 and 50, upon which claims 36 and 51 depend. MacFarland in view of Leydon, however fail to teach wherein the one or more client devices are further configured to, during the live audio session, display the transcribed text in the first human language and the translated text in the second human language. Waibel teaches wherein the one or more client devices are further configured to, during the live audio session, display the transcribed text in the first human language and the translated text in the second human language (Waibel; Fig. 18 illustrates the display of the text in the first and second language simultaneously; p. 0056 - a simultaneous translation mode will be present. In this mode no button push is required but the system continuously recognizes and translates all speech present on both microphone inputs. Continuously recognition and simultaneous translation is shown). Therefore, it would have been obvious to one of ordinary skill in the art to modify the system and method of McFarland to include wherein the one or more client devices are further configured to, during the live audio session, display the transcribed text in the first human language and the translated text in the second human language, as taught by Waibel, in order to enabling users to add new vocabulary items and improving and modifying the content and usage of their system in the field, without requiring linguistic or technical knowledge or expertise for field maintenance (Waibel; p. 0003). As per claim 38, McFarland in view of Leydon discloses: The system of claim 32, upon which claim 38 depend. McFarland in view of Leydon, however, fail to teach wherein the language translation module is configured to, during the audio session: identify a low-confidence word in the translated text in the second human language where the language translation module has a confidence level for the low-confidence word below a threshold confidence level; flag the low-confidence word in the display of the translated text. Waibel does teach wherein the language translation module is configured to, during the audio session: identify a low-confidence word in the translated text in the second human language where the language translation module has a confidence level for the low-confidence word below a threshold confidence level; flag the low-confidence word in the display of the translated text (Waibel; p. 0053 - To help the user determine if the translation output is adequate, the automatically generated translation is translated back into the input language via MT module 3 or 8 and displayed with parentheses under the original input. If the confidence of both speech recognition and translation are high as determined by the ASR model, 2 or 9, and the MT module, 3 or 8, spoken output is generated via loud speakers 5 or 6, via TTS modules 4 or 7. Otherwise, the system indicates that the translation may be wrong via the GUI, audio and/or tactical feedback. The specific TTS module used in step 33 is selected based on the output language); receive a corrective input from a user of one of the one or more client devices for the low-confidence word: and update a model of the language translation module to use the corrective input for the low-confidence word for the audio session (Waibel; p. 0055 - Thereafter, if the user is dissatisfied with the generated translation, the user may intervene during the speech-to-speech translation process in any of steps from 27 to 33 or after process has completed. This invokes the Correction and Repair Module 14 at. The Correction and Repair Module records and logs any corrections the user may make, which can be later used to update ASR modules 2 and 9 and MT modules 3 and 8 as described in detail further below in this document. If the correction contains a new vocabulary item, or if the user enters the field customization mode to explicitly add a new word to the system, or if a new word is automatically detected in the input audio using confidence measures or new word models, the User Field Customization Module (Module 12) is invoked). Therefore, it would have been obvious to one of ordinary skill in the art to modify the system and method of McFarland to include wherein the language translation module is configured to, during the audio session: identify a low-confidence word in the translated text in the second human language where the language translation module has a confidence level for the low-confidence word below a threshold confidence level; flag the low-confidence word in the display of the translated text; receive a corrective input from a user of one of the one or more client devices for the low- confidence word; and update a model of the language translation module to use the corrective input for the low-confidence word for the audio session, as taught by Waibel, in order to enabling users to add new vocabulary items and improving and modifying the content and usage of their system in the field, without requiring linguistic or technical knowledge or expertise for field maintenance (Waibel; p. 0003).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record and not relied upon includes: Nelson (US PG Pub 20190273767) an approach is provided for integrating mobile devices into electronic meetings conducted over computer networks using IWB appliances. The approach includes a user-friendly way for users to join electronic meetings using mobile devices. The approach also allows participants to command and control an electronic meeting using their mobile device, and to receive individualized output, such as meeting transcripts, real-time language translation, messages, prompts, meeting information, and personalized audio streams (Nelson; Abstract). Lee (US PG Pub 20200258504) an electronic apparatus configured to acquire information on a plurality of candidate texts corresponding to input speech of a user through a general speech recognition module, determine text corresponding to the input speech from among the plurality of candidate texts using a trained personal language model, and output the text as a result of speech recognition of the input speech (Lee; Abstract).
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/RODRIGO A CHAVEZ/Examiner, Art Unit 2658
/RICHEMOND DORVIL/Supervisory Patent Examiner, Art Unit 2658
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