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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 21 July 2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to the rejection(s) of claim(s) 1, 7, and 14 under 35 U.S.C. 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Raz et al.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4-7, 9-12, 14, and 16-19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Raz et al. (U.S. Patent Application Pub. No. 2021/0183519, hereinafter “Raz”).
In regard to claim 1, Raz discloses a computer-implemented method for use in treating a health condition, comprising:
obtaining an audio file that captures one or more interactions between one or more providers and a patient of a service (a clinician elicits an audio language sample from a candidate, paragraphs [0076-0077]);
generating a transcript of at least a portion of the one or more interactions captured in the audio file (speech from the audio file is transcribed into text, paragraph [0088]);
inferring, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (various characteristics are determined from the language sample, paragraph [0089]);
determining one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (biomarkers such as hypomania or mania are determined, based on correlation with the language characteristics, paragraph [0090]);
generating a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a measure of risk is determined based on the biomarkers and language characteristics, paragraph [0097]), and at least one factor evaluated prior to the service and indicative of suitability for the service (the evaluation occurring prior to starting a regiment of psychedelic therapy to determine whether a candidate is fit for psychedelic therapy, paragraph [0072]); and
administering psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (administration of psilocybin, paragraph [0048]).
In regard to claim 2, Raz discloses a recording is transcribed using Natural Language Processing (NLP) (using natural language toolkit, paragraph [0088]).
In regard to claim 4, Raz discloses analyzing one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0088]);
generating one or more tags associated with the one or more utterances (partially processed natural language data providing representation, summarization, etc., paragraph [0135]); and
inferring the plurality of analytics based, at least in part, upon the generated tags (characteristics derived from the processed language sample, paragraphs [0089] and [0135]).
In regard to claim 5, Raz discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the audio file (words per phrase, sematic coherence, pitch, frequency, etc., paragraphs [0089] and [0093]).
In regard to claim 6, Raz discloses assigning one or more tags to the audio file based, at least in part, upon audio cues detected in the audio file (acoustic features, paragraph [0093]).
In regard to claim 7, Raz discloses a system for use in treating a health condition comprising:
at least one processor (paragraph [0055]); and
at least one memory, storing instructions (paragraph [0055]) that, when executed by the at least one processor, cause the at least one processor to:
obtain a media file that captures one or more interactions between one or more providers and a patient of a service (an audio recording of a clinician interacting with a candidate, paragraph [0076]);
generate a transcript of at least a portion of the one or more interactions captured in the media file (speech from the audio file is transcribed into text, paragraph [0088]);
infer, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (various characteristics are determined from the language sample, paragraph [0089]);
determine one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (biomarkers such as hypomania or mania are determined, based on correlation with the language characteristics, paragraph [0090]);
generate a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a measure of risk is determined based on the biomarkers and language characteristics, paragraph [0097]), and at least one factor evaluated prior to the service and indicative of suitability for the service (the evaluation occurring prior to starting a regiment of psychedelic therapy to determine whether a candidate is fit for psychedelic therapy, paragraph [0072]); and
administer psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (administration of psilocybin, paragraph [0048]).
In regard to claim 9, Raz discloses a recording is transcribed using Natural Language Processing (NLP) (using natural language toolkit, paragraph [0088]).
In regard to claim 10, Raz discloses instructions that, when executed by the at least one processor, cause the at least one processor to further:
analyze one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0088]);
generate one or more tags associated with the one or more utterances (partially processed natural language data providing representation, summarization, etc., paragraph [0135]); and
infer the plurality of analytics based, at least in part, upon the generated tags (characteristics derived from the processed language sample, paragraphs [0089] and [0135]).
In regard to claim 11, Raz discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the audio file (words per phrase, sematic coherence, pitch, frequency, etc., paragraphs [0089] and [0093]).
In regard to claim 12, Raz discloses In regard to claim 10, Raz discloses he instructions that, when executed by the at least one processor, cause the at least one processor to further:
assign one or more tags to the audio file based, at least in part, upon audio cues detected in the audio file (acoustic features, paragraph [0093]).
In regard to claim 14, Raz discloses a non-transitory computer-readable medium for use in treating a health condition, storing instructions (paragraph [0055]) that, when executed by at least one processor, cause the at least one processor to:
obtain a media file that captures one or more interactions between one or more providers and a patient of a service (an audio recording of a clinician interacting with a candidate, paragraph [0076]);
generate a transcript of at least a portion of the one or more interactions captured in the media file (speech from the audio file is transcribed into text, paragraph [0088]);
infer, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (various characteristics are determined from the language sample, paragraph [0089]);
determine one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (biomarkers such as hypomania or mania are determined, based on correlation with the language characteristics, paragraph [0090]);
generate a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a measure of risk is determined based on the biomarkers and language characteristics, paragraph [0097]), and at least one factor evaluated prior to the service and indicative of suitability for the service (the evaluation occurring prior to starting a regiment of psychedelic therapy to determine whether a candidate is fit for psychedelic therapy, paragraph [0072]); and
administer psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (administration of psilocybin, paragraph [0048]).
In regard to claim 16, Raz discloses a recording is transcribed using Natural Language Processing (NLP) (using natural language toolkit, paragraph [0088]).
In regard to claim 17, Raz discloses instructions that, when executed by the at least one processor, cause the at least one processor to further:
analyze one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0088]);
generate one or more tags associated with the one or more utterances (partially processed natural language data providing representation, summarization, etc., paragraph [0135]); and
infer the plurality of analytics based, at least in part, upon the generated tags (characteristics derived from the processed language sample, paragraphs [0089] and [0135]).
In regard to claim 18, Raz discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the audio file (words per phrase, sematic coherence, pitch, frequency, etc., paragraphs [0089] and [0093]).
In regard to claim 19, Raz discloses In regard to claim 10, Raz discloses he instructions that, when executed by the at least one processor, cause the at least one processor to further:
assign one or more tags to the audio file based, at least in part, upon audio cues detected in the audio file (acoustic features, paragraph [0093]).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 3, 8, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raz, in view of Peters et al. (U.S. Patent Application Pub. No. 2007/0299664, hereinafter “Peters”).
In regard to claims 3, 8, and 15, Raz does not disclose correcting errors.
Peters discloses a method of transcribing a recording comprising:
detecting that the transcript contains an error (erroneous text is detected, paragraph [0051]);
providing an indication of the error (the user is provided an indication of the error, paragraph [0040]); and
suggesting one or more corrections to the error (rules to correct the error are suggested to the user, paragraph [0043]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect errors in the transcript and suggest one or more corrections, because it would indicate to the user how to eliminate those errors in future applications, as taught by Peters (paragraph [0043]).
Claim(s) 13 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raz, in view of Lucas et al. (U.S. Patent Application Pub. No. 2002/0143533, hereinafter “Lucas”).
In regard to claims 13 and 20, Raz does not disclose the media file is pre-processed prior to transcription to filter out unwanted noise from the media file.
Lucas discloses a system for transcribing voice from a media file, wherein the media file is pre-processed prior to transcription to filter out unwanted noise from the media file (an audio file is processed to remove noise prior to transcription, paragraph [0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to pre-process the media file prior to transcription to filter out unwanted noise from the media file, because, as is widely recognized in the art, removing noise would increase the accuracy of the transcription.
Conclusion
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BLA 8/5/26
/BRIAN L ALBERTALLI/ Primary Examiner, Art Unit 2656
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