CTNF 17/518,376 CTNF 98840 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 12-151 AIA 26-51 12-51 Status of Claims This action is in reply to the claims and arguments/remarks filed on 13 July 2026. Claims 11-45, 49-51, and 56-75 were canceled. Claims 76-78 have been newly added. Claims 1, 46 and 48 have been amended. Claims 1-10, 46-48, 52-55, and 76-78 are currently pending and have been examined. Continued Examination Under 37 CFR 1.114 07-42-04 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 13 July 2026 has been entered. Response to Arguments Applicant's arguments, see Page(s) 7-9, filed 13 July 2026, with respect to the 35 USC § 103 rejection(s) of claim(s) 1-10, 46-48, 52-55, and 76-78 have been fully considered but they are moot due to the Examiner relying on new references not previously used for the newly amended claim 1 and 46. Applicant’s arguments are directed towards Danieli-Bhamidipati-Feinauer, however, the Examiner is relying on prior art, Lee, to teach the amended features from the arguments. Specifically, the Examiner is now relying on new prior art Lee to teach determining based on the first portion of the keyword and before generation of the keyword is complete. The Examiner maintains the 35 USC § 103 claim rejection(s) of claim(s) 1 – 10, 46 – 48, and 52-55 under Danieli-Lee-Feinauer. Furthermore, the Examiner is rejecting new claims 76-78 under Danieli-Lee-Feinauer in view of Lawrence. Claim Rejections - 35 USC § 103 07-103 AIA The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. 07-21-aia AIA Claim s 1 – 10, 46 – 48, and 52-55 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2006/0095262 A1 to Damon V. Danieli (hereinafter Danieli) in view of U.S. Patent no. US 5509104 A (herein after Lee) and in further view of U.S. Patent No. 11,450,311 B2 to Christoph Johan Feinauer et al. (hereinafter Feinauer) . Regarding claim 1, Danieli teaches an apparatus to modify sound of speech in an audio signal, the apparatus comprising: (Danieli teaches a system for automatically censoring a real-time audio source (i.e., modifying speech of an audio signal.) Danieli at ¶¶ [0029] - [0030]. Further, Danieli’s teachings of automatic censoring during live broadcast are applicable to any sort of broadcast of voice. For example, voice may be broadcast in telephone calls, video calls, live chat sessions, livestreams, cross-platform communications, gaming lobbies, etc.)) memory; instructions in the apparatus; (Danieli teaches the system comprising memory instructions stored in the memory. Danieli at ¶ [0013].) and processor circuitry to execute the instructions to: (Danieli teaches the system comprising a processor that executes the instructions stored in the memory. Danieli at ¶ [0013]) determine a waveform to replace the keyword. (see at least Paragraph [0060] of Danieli “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) transforming the keyword into a different word by introducing the waveform into the audio signal. (see at least Paragraph [0060] of Danieli “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) Danieli, however, does not teach identifying a first portion of a keyword in the speech during generation of the speech; determining, based on the first portion of the keyword and before generation of the keyword is complete, a waveform to replace a second portion of the keyword. However, Lee the known technique of: identifying a first portion of a keyword in the speech during generation of the speech; (see at least Col. 5, ll. 3-22 “The FSLB algorithm in procedure 13 performs a maximum-likelihood string decoding on a frame-by frame basis, therefore making optimally decoded partial strings available at any time. The output of this process is a set of valid candidate strings.”; Col. 1, ll. 20-52 explains that the system was developed for live telephone audio.) and determining, based on the first portion of the keyword and before generation of the keyword is complete, predicted words; (see at least Col. 5, ll. 3-22 “The sequence of spectral vectors of an unknown speech utterance is matched against a set of stored word-based hidden Markov models 12 using a frame-synchronous level-building (FSLB) algorithm 13 […] The FSLB algorithm in procedure 13 performs a maximum-likelihood string decoding on a frame-by frame basis, therefore making optimally decoded partial strings available at any time. The output of this process is a set of valid candidate strings.”). This technique of Lee is applicable to the system of Danieli as they both share characteristics and capabilities, namely, they are directed to analyzing live audio broadcast waveforms to perform an action. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified the system of Danieli to incorporate the known technique of determining a predicted word based on the first portion of a keyword prior to generation of the keyword as taught by Lee. By using Lee’s technique of predicting the keyword with a frame by frame algorithm during a live broadcast on one of Danieli’s audio streams, Danieli could use the predicted word to determine if the keyword should be censored and censor it in real time. One of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to modify Danieli in order to get a best match keyword (see Col. 3, ll. 50-60 of Lee). Danieli in view of Lee (hereinafter Danieli-Lee), however, do not expressly teach wherein the identifying, determining and transforming are performed within less than 200 ms from generation of the first portion of the keyword. In a similar field of endeavor (e.g., real-time processing and modification of voice signals), Feinauer teaches wherein the identifying, determining and transforming are performed within less than 200 ms from generation of the first portion of the keyword. (Feinauer teaches introducing a lag delay of 100 ms to allow for the processing of the words while still allowing the audio to sound real-time to the user. Feinauer at 22:60 - 23:9. Further, Feinauer teaches identifying and replacing words as part of an accent and dialect modification process (i.e., identifying the word to be replaced, determining which word/waveform to replace it, and transforming the word by replacing it.). Feinauer at 16:66 - 17:14. Therefore, a person of ordinary skill in the art would have recognized that replacement of words or portions of words can be performed within 100 ms of the speech to prevent interruption of the flow of communication.) It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Danieli-Lee with the teachings of Feinauer (hereinafter Danieli-Lee-Feinauer) to provide the identifying, determining and transforming are performed within less than 200 ms from generation of the first portion of the keyword. Doing so would have allowed modification of a speech signal while preserving real-time transmission/communication for the users as recognized by Feinauer at 22:60 – 23:9. Further, Danieli teaches performing real-time audio processing and censorship in live chats such as video game voice sessions. Danieli at ¶ [0007]. Therefore, Feinauer’s 100 ms processing time would have been a predictable application of well-known audio processing techniques within similar fields of endeavor which allowed for the preservation of real-time communication while also providing the user a better experience by maintaining real-time information transmission. As such, a person of ordinary skill in the art would have found it obvious to apply Feinauer’s teachings to Danieli’s video game chat sessions in order to preserve real-time voice processing for a better user experience. Regarding claim 2, Danieli-Lee-Feinauer teaches all the limitations of claim 1 as laid out above. Further, Danieli teaches the apparatus of claim 1, wherein the processor circuitry is to: identify an attribute of the speech; and adjust the waveform based on the attribute. (see at least Paragraph [0059] “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) Regarding claim 3, Danieli-Lee-Feinauer teaches all the limitations of claim 2 as laid out above. Further, Danieli teaches the apparatus of claim 2, wherein the attribute is a volume. (See at least Paragraph [0056] of Danieli “a step 242b provides for attenuating the volume of the undesired word substantially below that of all of the acceptable speech in the input audio data stream, so that the undesired word will not be heard by an audience listening to the censored audio data.”) Regarding claim 4, Danieli-Lee-Feinauer teaches all the limitations of claim 2, as laid out above. Danieli in view of Lee does not teach: wherein the attribute is a vocal register. However, Feinauer teaches the apparatus of claim 2, wherein the attribute is a vocal register. (Col 14, ll. 3-31 “the accent and dialect modifier 318 modifies any voice characteristics such as pitch”) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Regarding claim 5, Danieli-Lee-Feinauer teaches all the limitations of claim 2, as laid out above. Danieli in view of Lee do not teach the apparatus of claim 2, wherein the attribute is a prosody. However, Feinauer teaches the attribute is a prosody. (Col. 26, ll. 28-48 “prosodic vocal features and characteristics of individual word dialects can be extracted from the individual word audio samples using preprocessing tools to convert the audio sample waveforms into a spectrogram of MFCC.”) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Regarding claim 6, Danieli-Lee-Feinauer teaches all the limitations of claim 2, as laid out above. Danieli in view of Lee do not teach the apparatus of claim 2, wherein the attribute is a speaking rate. However, Feinauer teaches the attribute is a speaking rate. (Col. 26, ll. 28-48 “prosodic vocal features and characteristics of individual word dialects can be extracted from the individual word audio samples using preprocessing tools to convert the audio sample waveforms into a spectrogram of MFCC.”; Examiner notes speaking rate is a core component of prosody.) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Regarding claim 7, Danieli-Lee-Feinauer teaches the apparatus of claim 1. Danieli further teaches: wherein the processor circuitry is to: identify text of the different word based on the keyword; (see at least Paragraph [0060] of Danieli “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) However, Danieli in view of Lee does not teach: convert the text to speech; and determine the waveform based on the converted text to speech. However, Feinauer teaches: convert the text to speech; and determine the waveform based on the converted text to speech. (Col. 8, ll. 41-67 “a dialect translation model and dialect dictionary could include a model to transcribe a spoken word from speech-to-text, determine the equivalent word by referencing an uploaded dialect dictionary and modulate a voice in real-time to replace the spoken word with an entirely new word using a text-to-speech model.”) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Regarding claim 8, Danieli-Lee-Feinauer teaches the apparatus of claim 1. Danieli further teaches: wherein the processor circuitry is to: determine a source phoneme sequence of the keyword; (see at least Paragraph [0038] “The censoring filter takes the input stream and passes it through a language-dependent speech recognizer 301. The recognizer produces a phoneme lattice 302 representing a continuous utterance stream. […] Based on the score of best candidate keyword 305, non-language specific censoring logic 306 can determine whether to take action or not, depending upon whether the score is above a dynamic threshold.”) identify a target phoneme sequence based on the source phoneme sequence; (see at least Paragraph [0060] of Danieli “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) and build the waveform based on the target phoneme sequence. (see at least Paragraph [0060] of Danieli “The sound track of a movie can be altered using the alternative of step 242d, to replace offensive and undesired words with corresponding acceptable words. Thus, for example, the words ‘God’ and ‘damn’ might be replaced with the words ‘gosh’ and ‘darn,’ using the phonemes from the previous speech by the speaker, producing the censored phrase ‘gosh darn it.’”; Fig. 9) Regarding claim 9, Danieli-Lee-Feinauer teaches the apparatus of claim 8. Danieli-Lee does not teach: wherein the processor circuitry is to implement a neural network to maintain characteristics of a voice speaking the keyword in the speech signal with the different word. However, Feinauer teaches: wherein the processor circuitry is to implement a neural network to maintain characteristics of a voice speaking the keyword in the speech signal with the different word. (see at least Col. 8, ll. 41-67 “The dialect translation model would determine attributes of a user before the target word was spoken so that their voice profile can be replicated in the real time modification and the replaced word flows with the vocal biometric profile of the user.”; Col. 26, ll. 8-48 “the features of the vocal characteristics in each category can be analyzed by a supervised neural network and the identified vocal characteristics correlated with their respective accent and dialect strength category labels.”) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Regarding claim 10, Danieli-Lee-Feinauer teaches the apparatus of claim 9. Danieli in view of Lee does not teach: wherein the processor circuitry is to: disentangle characteristics of the voice; learn representations of the speech in the audio signal independent of the source phoneme sequence; and build the waveform based on the learned representations. However, Feinauer teaches:wherein the processor circuitry is to: disentangle characteristics of the voice; (see at least Col. 8, ll. 41-67 “The dialect translation model would determine attributes of a user before the target word was spoken so that their voice profile can be replicated”) learn representations of the speech in the audio signal independent of the source phoneme sequence; (see at least Col. 8, ll. 41-67 “modulate a voice in real-time to replace the spoken word with an entirely new word using a text-to-speech model.”; Examiner notes the system of Feinauer learns patterns of words/phonemes that are not spoken by the speaker to replace the word with a word that isn’t spoken by a speaker. For example, learning “darn” to replace “damn”) and build the waveform based on the learned representations. (see at least Col. 8, ll. 41-67 “modulate a voice in real-time to replace the spoken word with an entirely new word using a text-to-speech model.”) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 1. Claim(s) 46 is/are directed to a non-transitory machine readable medium. Claim(s) 46 recite limitations parallel in nature as those addressed above for claim(s) 1, which are directed towards system. Claim(s) 46 is/are therefore rejected for the same reasons as set above for claim(s) 1. Claim 46 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli). Claim(s) 47 is/are directed to a non-transitory machine readable medium. Claim(s) 47 recite limitations parallel in nature as those addressed above for claim(s) 2, which are directed towards system. Claim(s) 47 is/are therefore rejected for the same reasons as set above for claim(s) 2. Claim 47 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli). Regarding claim 48, Danieli-Lee-Feinauer teaches all the limitations of claim 47 as laid out above. Further, Danieli teaches the machine-readable medium of claim 47, wherein the attribute is a volume. (See at least Paragraph [0056] of Danieli “a step 242b provides for attenuating the volume of the undesired word substantially below that of all of the acceptable speech in the input audio data stream, so that the undesired word will not be heard by an audience listening to the censored audio data.”) Claim(s) 52 is/are directed to a non-transitory machine readable medium. Claim(s) 52 recite limitations parallel in nature as those addressed above for claim(s) 7, which are directed towards system. Claim(s) 52 is/are therefore rejected for the same reasons as set above for claim(s) 7. Claim 52 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli). Claim(s) 53 is/are directed to a non-transitory machine readable medium. Claim(s) 53 recite limitations parallel in nature as those addressed above for claim(s) 8, which are directed towards system. Claim(s) 53 is/are therefore rejected for the same reasons as set above for claim(s) 8. Claim 53 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli). Claim(s) 54 is/are directed to a non-transitory machine readable medium. Claim(s) 54 recite limitations parallel in nature as those addressed above for claim(s) 9, which are directed towards system. Claim(s) 54 is/are therefore rejected for the same reasons as set above for claim(s) 9. Claim 54 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli). Claim(s) 55 is/are directed to a non-transitory machine readable medium. Claim(s) 55 recite limitations parallel in nature as those addressed above for claim(s) 10, which are directed towards system. Claim(s) 55 is/are therefore rejected for the same reasons as set above for claim(s) 10. Claim 55 further recites a non-transitory machine readable medium comprising instructions that, when executed cause one or more processors to perform the method (see at least the memory medium in Paragraph [0013] of Danieli) . 07-21-aia AIA Claim s 76-78 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2006/0095262 A1 to Damon V. Danieli (hereinafter Danieli) in view of U.S. Patent no. US 5509104 A (herein after Lee) and in further view of U.S. Patent No. 11,450,311 B2 to Christoph Johan Feinauer et al. (hereinafter Feinauer) in further view of Lawrence et al. (US 20190103098 A1) (herein after Lawrence) . Regarding claim 76, Danieli-Lee-Feinauer teaches the apparatus of claim 1. Danieli-Lee-Feinauer does not teach: a buffer to temporarily store the audio signal, the buffer sized to store a selected duration of the audio signal that is less than a keyword duration of the keyword. However, Lawrence teaches: a buffer to temporarily store the audio signal, the buffer sized to store a selected duration of the audio signal that is less than a keyword duration of the keyword. (see at least Paragraph [0039] “a command processor (e.g., the command processor 118) buffers an analyzable duration of the acoustic data in an audio buffer (e.g., the audio buffer 120). In some embodiments, this analyzable duration is the maximum duration of a phoneme in slow but continuous speech (e.g., 500 ms).”; Paragraph [0042] “the audio buffer is dependent upon the size and number of basic constructs (e.g., phonemes) needed to validate a command sequence implied by the particular command indicator detected in the act 208”; Examiner notes the buffer is big enough to store a phoneme.) This operation of Lawrence is applicable to the system of Danieli-Lee-Feinauer as they both share characteristics and capabilities, namely, they are directed to processing real time audio. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified the system of Danieli-Lee-Feinauer to incorporate the buffer sizing as taught by Lawrence. One of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to modify Danieli-Lee-Feinauer in order to minimize latency between a user's utterance and subsequent processing (see paragraph [0041] of Lawrence). Regarding claim 77, Danieli-Lee-Feinauer teaches the apparatus of claim 76. Danieli-Lee-Feinauer does not teach: wherein the selected duration is based on a phoneme duration of the one or two initial phonemes of the keyword. However, Lawrence teaches: wherein the selected duration is based on a phoneme duration of the one or two initial phonemes of the keyword. (see at least Paragraph [0039] “a command processor (e.g., the command processor 118) buffers an analyzable duration of the acoustic data in an audio buffer (e.g., the audio buffer 120). In some embodiments, this analyzable duration is the maximum duration of a phoneme in slow but continuous speech (e.g., 500 ms).”; Paragraph [0042] “the audio buffer is dependent upon the size and number of basic constructs (e.g., phonemes) needed to validate a command sequence implied by the particular command indicator detected in the act 208”; Examiner notes the buffer is big enough to store a phoneme.) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 76. Regarding claim 78, Danieli-Lee-Feinauer teaches the apparatus of claim 77. Danieli-Lee-Feinauer does not teach: wherein the selected duration is shorter than the keyword duration by a length of the first portion. However, Lawrence teaches: wherein the selected duration is shorter than the keyword duration by a length of the first portion. (see at least Paragraph [0039] “a command processor (e.g., the command processor 118) buffers an analyzable duration of the acoustic data in an audio buffer (e.g., the audio buffer 120). In some embodiments, this analyzable duration is the maximum duration of a phoneme in slow but continuous speech (e.g., 500 ms).”; Paragraph [0042] “the audio buffer is dependent upon the size and number of basic constructs (e.g., phonemes) needed to validate a command sequence implied by the particular command indicator detected in the act 208”; Examiner notes the buffer is big enough to store a phoneme.) The motivation for making this modification to the teachings of Danieli-Lee is the same as that set forth above, in the rejection of claim 76. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIELLE ELIZABETH ZEVITZ whose telephone number is (703)756-1070. The examiner can normally be reached Mo-Th 10am-6pm. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /DANIELLE ELIZABETH ZEVITZ/Examiner, Art Unit 2655 /ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655 Application/Control Number: 17/518,376 Page 2 Art Unit: 2655 Application/Control Number: 17/518,376 Page 3 Art Unit: 2655 Application/Control Number: 17/518,376 Page 4 Art Unit: 2655 Application/Control Number: 17/518,376 Page 5 Art Unit: 2655 Application/Control Number: 17/518,376 Page 6 Art Unit: 2655 Application/Control Number: 17/518,376 Page 7 Art Unit: 2655 Application/Control Number: 17/518,376 Page 8 Art Unit: 2655 Application/Control Number: 17/518,376 Page 9 Art Unit: 2655 Application/Control Number: 17/518,376 Page 10 Art Unit: 2655 Application/Control Number: 17/518,376 Page 11 Art Unit: 2655 Application/Control Number: 17/518,376 Page 12 Art Unit: 2655 Application/Control Number: 17/518,376 Page 13 Art Unit: 2655 Application/Control Number: 17/518,376 Page 14 Art Unit: 2655 Application/Control Number: 17/518,376 Page 15 Art Unit: 2655 Application/Control Number: 17/518,376 Page 16 Art Unit: 2655
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