Detailed Action
This communication is in response to the Arguments and Amendments filed on 11/17/2025.
Claims 1-20 are pending and have been examined.
Claims 1-20 are rejected.
Claims 1, 8 and 15 are independent and are parallel method, storage medium, and apparatus claims.
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 .
Arguments and Amendments
Applicants have amended the independent claims to include “environment, wherein said capturing comprises a plurality of microphones capturing a respective plurality of audio channels of the noisy audio signal, wherein said capturing comprises converting captured data to a digital form”
As clearly evident, the currently amended claims recite many technical features that show a technical improvement to a technical problem. For example, the technical features of applying speech separation on a plurality of digital channels of a noisy audio signal, in order to obtain a separate audio signal of an unidentified entity, and estimating the identifier of the unidentified entity, enables the user to gain full control over voice amplifications of unidentified entities. For example, by separating the audio signal of the unidentified entity, and then estimating the entity's identifier, the unidentified entity can be represented in a user-friendly manner that enables the user to control (e.g., activate or mute) their voice in the environment.
Examiner notes the claims recite steps that can be performed in the human mind or using pen and paper.
Applicant asserts that the claims, in their currently amended form, are not directed to an abstract idea of a mental process that can be performed by a human mind (Step 2A prong 1). Specifically, Applicant asserts that a human mind, with or without a physical aid such as pen and paper, is not equipped to perform the features of the independent claims. For example, with respect to Claim 1, Applicant asserts that a human mind is not equipped to perform: capturing a noisy audio signal from the environment, wherein said capturing comprises a plurality of microphones capturing a respective plurality of audio channels of the noisy audio signal, wherein said capturing comprises converting captured data to a digital form.
Examiner notes the microphones are noted as additional elements and are not sufficient to amount to significantly more than the judicial exception
Applicant notes a human mind is not equipped to perform: applying speech separation on the noisy audio signal to obtain a separate audio signal that represents a voice of an unidentified entity.
Examiner notes a human can naturally separate speech in the human mind.
Applicant notes Example 48 describes a speech separation system that uses a trained network to separate mixed audio signals into distinct speech sources.
Claim 2 of Example 48 was found eligible because it integrates the abstract idea into a practical application under Step 2A, Prong Two. Specifically, step (g) of Claim 2, which relates to combining speech waveforms to generate a mixed speech signal while excluding audio from an undesired source, was found to integrate the abstract idea into a practical application, since the claim reflects the improvements discussed in the disclosure. Specifically, this step is directed to creating a new speech signal that no longer contains extraneous speech signals from unwanted sources. The claimed invention reflects this technical improvement by including these features.
In the present case, the claimed invention similarly improves speech processing by performing source-specific speech separation and estimating identifiers of unidentified speech sources. As in Example 48, the claim features cannot practically be performed in the human mind, and reflect the improvements discussed in the disclosure by including these features. For example, the features of Claim 1 reflect the improvements discussed in Paragraphs [0042] and [0045] of the disclosure, such as enabling an automatic identification of people that are conversing with the user without having direct access to identifiers of the people, which is useful for enabling the user to activate or mute desired people in the environment via a user interface of the mobile device.
Examiner notes the additional elements are not sufficient to transform the abstract idea into a practical application.
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on the primary reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Examiner notes the amendments to the independent claims resulted in a new interpretation of the claims. Hence, new grounds for rejection have been made in view of Donsbach (US Patent Number US 20220310109 A1), in view of Shum (US Patent Number US 20200380980 A1), and Further in view of Masnadi-Shirazi (US Patent Number US 20210390952 A1).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding independent Claim 1, the claim recites
“A method performed in an environment of a user, a plurality of people is located in the environment, the user having a mobile device used for obtaining user input, the user having at least one hearable device used for providing audio output to the user, the method comprising:
capturing a noisy audio signal from the environment, wherein said capturing comprises a plurality of microphones capturing a respective plurality of audio channels of the noisy audio signal, wherein said capturing comprises converting captured data to a digital form;
applying speech separation on the noisy audio signal to obtain a separate audio signal that represents a voice of an unidentified entity;
estimating an identifier of the unidentified entity, thereby obtaining an estimated identifier of the unidentified entity;
and prompting the user to confirm or decline the estimated identifier.”
The limitations of “Capturing…”, “Applying…”, “Estimating …”, “Prompting …” as drafted covers a human mental activity or process.
More specifically,
A human is capable of capturing a noisy audio signal from the environment; using the auditory system.
A human is capable of applying speech separation on the noisy audio signal to obtain a separate audio signal that represents a voice of an unidentified entity; by listening for the desired signal or tuning out the unwanted signal in the human mind.
A human is capable of estimating an identifier of the unidentified entity, thereby obtaining an estimated identifier of the unidentified entity; in the human memory by identifying an entity.
A human is capable of and prompting the user to confirm or decline the estimated identifier. By voice or using pen and paper.
Regarding independent Claim 8, Claim 8 is a storage medium claim with limitations similar to that of claim 1 and is rejected under the same rationale.
Regarding independent Claim 15, Claim 15 is a apparatus claim with limitations similar to that of claim 1 and is rejected under the same rationale.
This judicial exception is not integrated into a practical application. In particular, claims 8 and 15 recites the additional element of “processor” “memory” and “computer” as per the independent claims. For example, in [00178] of the as filed specification, there is description of an Apparatus 700 may comprise a Processor 702.Processor 702 may be a Central Processing Unit (CPU), a microprocessor, an electronic circuit, an Integrated Circuit (IC) or the like. Processor 702 may be utilized to perform computations required by Apparatus 700 or any of its subcomponents. Processor 702 may be configured to execute computer-programs useful in performing the methods. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using a processor and computer is noted as a general computer as noted. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, the additional limitation in the claims noted above are directed towards insignificant solution activity. The claims are not patent eligible.
With respect to claims 2, 9 and 16, the claims relate to estimating is performed by matching an acoustic fingerprint of the voice of the unidentified entity with a stored acoustic fingerprint of a person, and extracting the identifier of the unidentified entity based on said matching. This relates to a human performing natural voice recognition within the human mind to match a voice fingerprint to an identity of an entity. No additional limitations are present.
With respect to claims 3, 10 and 17 the claims relate to estimating is performed based on a calendar event of the user, wherein a scheduled time duration of the calendar event overlaps at least partially to a time of said capturing, wherein the calendar event indicates the identifier of the unidentified entity. This relates to a human identifying an entity based on historical memory of a time or event captured. No additional limitations are present.
With respect to claims 4, 11 and 18 the claims relate to estimating is performed based on identities of people in past communications of the user. This relates to a human identifying an entity based on historical memory of a time or event captured. No additional limitations are present.
With respect to claims 5, 12 and 19 the claims relate to estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies within the transcription an indication of the identifier of the unidentified entity. This relates to a human performing transcription using pen and paper and performing natural language understanding to semantically analyze a transcription. No additional limitations present.
With respect to claims 6, 13 and 20 the claims relate to estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies a context of the at least one conversation based on the transcription, wherein said estimating is performed based on the context and based on previous conversations of the user with the context. This relates to a human identifying an entity based on historical memory of a time or event captured and identifying an entity based on historical memory of a time or event captured. No additional limitations present.
With respect to claim 7 and 14 the claims relate to outputting to the user via the at least one hearable device an enhanced audio signal, the enhanced audio signal comprising at least the separate audio signal. This relates to a human using the auditory system to listen for audio. No additional limitations present.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 2, 7-9, 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Donsbach (US Patent Number US 20220310109 A1), in view of Shum (US Patent Number US 20200380980 A1), and Further in view of Masnadi-Shirazi (US Patent Number US 20210390952 A1).
Regarding independent Claim 1, Donsbach teaches 1. A method performed in an environment of a user, a plurality of people is located in the environment, (see Donsbach [0002] “A diarization model may be trained to distinguish between two or more speakers.”) the user having a mobile device used for obtaining user input, the user having at least one hearable device used for providing audio output to the user, (see Donsbach [0045] By way of example and without limitation, computing device 200 may be a cellular mobile telephone (e.g., a smartphone),”) the method comprising: estimating an identifier of the unidentified entity, thereby obtaining an estimated identifier of the unidentified entity; (see Donsbach [0076] FIG. 4 illustrates an example diarization model 400 used to determine, predict, and/or estimate source speaker 402 of an utterance.”)
Donsbach does not specifically teach and prompting the user to confirm or decline the estimated identifier. However SHUM does teach this limitation (see SHUM [0312] “In some examples, if device 800 requests a user to confirm his/her identity (e.g., asks “you are Stephen, right?”), a user provides a speech input including an affirmative or negative response. In some examples, device 800 then determines that the speech input corresponds to a user by determining that the speech input includes an affirmative response (e.g., “yes,” “I am,” “mhmm,” and the like). In some examples, device 800 determines that the speech input does not correspond to a user by determining that the speech input includes a negative response, or otherwise non-affirmative response (e.g., “no,” “I am not,” and the like).”)
Donsbach and Shum are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach to incorporate the teachings of Shum to include and prompting the user to confirm or decline the estimated identifier. Doing so allows devices to provide personalized responses as recognized by Shum in [0013].
Donsbach in view of Shum does not specifically teach capturing a noisy audio signal from the environment, wherein said capturing comprises a plurality of microphones capturing a respective plurality of audio channels of the noisy audio signal, wherein said capturing comprises converting captured data to a digital form; However Masnadi-Shirazi does teach this limitation (see Masnadi-Shirazi [0016] “The present disclosure may be used in with beamforming techniques incorporating generalized eigenvector tracking to enhance the target audio in the received audio signals. In one or more embodiments, a multi-channel audio input signal is received through an array of audio sensors (e.g., microphones). Each audio channel is analyzed to determine whether target audio is present, for example, whether a target person is actively speaking. The system tracks target and noise signals to determine a location of a target audio source (e.g., a target person) relative to the microphone array. An improved generalized eigenvector process may be used to determine a direction of the target audio in real time. The determined direction may then be used by a spatial filtering process, such as a minimum variance distortionless response (MVDR) beamformer, to enhance the target audio. After the audio input signals are processed, an enhanced audio output signal may be used, for example, as audio output transmitted to one or more speakers, as voice communications in a telephone or voice over IP (VoIP) call, for speech recognition or voice command processing, or other voice application. A modified generalized eigenvector (GEV) system may be used to efficiently determine the direction of a target audio source in real-time, with or without the knowledge of the geometry of the array of microphones or the audio environment.”) (see Masnadi-Shirazi [0019] “The target audio source 110 may be any source that produces target audio detectable by the audio processing device 105. The target audio may be defined based on criteria specified by user or system requirements. For example, the target audio may be defined as human speech, a sound made by a particular animal or a machine. In the illustrated example, the target audio is defined as human speech, and the target audio source 110 is a person. In addition to target audio source 110, the operating environment 100 may include one or more noise sources 135-145. In various embodiments, sound that is not target audio is processed as noise”) applying speech separation on the noisy audio signal to obtain a separate audio signal that represents a voice of an unidentified entity; (see Masnadi-Shirazi [0035] The target activity detector 325 is operable to analyze the frames of one or more of the audio channels and generate a signal indicating whether target audio is present in the current frame. As discussed above, target audio may be any audio to be identified by the audio system. When the target audio is human speech, the target activity detector 325 may be implemented as a voice activity detector. In various embodiments, a voice activity detector operable to receive a frame of audio data and make a determination regarding the presence or absence of the target audio may be used. In some embodiments, the target activity detector 325 may apply target audio classification rules to the sub-band frames to compute a value. The value is then compared to the threshold value for generating a target activity signal. In various embodiments, the signal generated by the target activity detector 325 is a binary signal, such as an output of ‘1’ to indicate a presence of target speech in the sub-band audio frame and the binary output of ‘0’ to indicate an absence of target speech in the sub-band audio frame. The generated binary output is provided to the target enhancement engine 330 for further processing of the multichannel audio signal. In other embodiments, the target activity signal may comprise a probability of target presence, an indication that a determination of target presence cannot be made, or other target presence information in accordance with system requirements.”) (see Masnadi-Shirazi [0038] FIG. 4 illustrates an example system architecture 400 providing robust speaker localization in the presence of strong noise interference, in accordance with one or more embodiments. The system architecture 400 according to various embodiments of the disclosure may be implemented as a combination of digital circuitry and logic performed by a digital signal processor. The system architecture 400 includes a subband analysis block 410, a covariance computation block 420, input voice activity detector (input VAD 450) that makes speech/non-speech determinations, a target speech relative transfer function estimation using Eigen analysis module (RTF estimation module 430), and a modified covariance-based localization module 440.”)
Donsbach in view of Shum and Masnadi-Shirazi are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach and Shum to incorporate the teachings of Masnadi-Shirazi to include capturing a noisy audio signal from the environment; and applying speech separation on the noisy audio signal to obtain a separate audio signal that represents a voice of an unidentified entity Doing so allows for speaker enhancement and noise reduction as recognized by Masnadi-Shirazi in [0013].
Regarding independent Claim 8, Claim 8 is a parallel storage medium claim with limitations similar to that of Claim 1 and is rejected under the same rationale. Additionally, Donsbach teaches 8. A computer program product comprising a non-transitory computer readable storage medium retaining program instructions, which program instructions when read by a processor, cause the processor to (see Donsbach [0006] A third example embodiment may include a non-transitory computer-readable storage medium having stored thereon instructions that, when executed by a computing device, cause the computing device to perform operations.”)
Regarding independent Claim 15, Claim 15 is a parallel apparatus claim with limitations similar to that of Claim 1 and is rejected under the same rationale. Additionally, Donsbach teaches 15. An apparatus comprising a processor and coupled memory, the processor being adapted to perform a method in an environment of a user, (see Donsbach 0005] In a second example embodiment, a system may include a microphone and a processor configured to perform operations”)
Regarding claim 2, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 2. The method of Claim 1
Furthermore, Masnadi-Shirazi teaches, wherein said estimating is performed by matching an acoustic fingerprint of the voice of the unidentified entity with a stored acoustic fingerprint of a person, and extracting the identifier of the unidentified entity based on said matching. (see Masnadi-Shirazi [0014] “In the present disclosure systems and methods are described that robustly estimate the TDOA/DOA of one or more concurrent speakers when a stronger dominant noise/interference source (e.g., loud TV noise) is consistently present. In some embodiments, the system works by employing some features of the Generalized Eigenvalue (GEV) beamformer, which allows for the estimate of the target speaker's unique spatial fingerprint or Relative Transfer Function (RTF). The target RTF is estimated by effectively nulling the dominant noise source. By applying a modified TDOA/DOA estimation method that uses the RTF as an input, the systems described herein can obtain a robust localization estimate of the target speaker. If multiple target speakers are active in the presence a stronger noise source (e.g., stronger than the target speakers), with proper tuning the RTF of each source can be estimated intermittently and fed to a multi-source tracker, leading to a robust VAD for each source separately that can drive the multi-stream voice enhancement system.
Donsbach in view of Shum and further and Masnadi-Shirazi are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach Shum and Masnadi-Shirazi to incorporate the teachings of Masnadi-Shirazi to include estimating is performed by matching an acoustic fingerprint of the voice of the unidentified entity with a stored acoustic fingerprint of a person, and extracting the identifier of the unidentified entity based on said matching. Doing so allows for speaker enhancement and noise reduction as recognized by Masnadi-Shirazi in [0013].
Regarding Claim 7, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 7. The method of Claim 1
Furthermore, Masnadi-Shirazi teaches, further comprising outputting to the user via the at least one hearable device an enhanced audio signal, the enhanced audio signal comprising at least the separate audio signal. (See Masnadi-Shirazi [0016] The present disclosure may be used in with beamforming techniques incorporating generalized eigenvector tracking to enhance the target audio in the received audio signals. In one or more embodiments, a multi-channel audio input signal is received through an array of audio sensors (e.g., microphones). Each audio channel is analyzed to determine whether target audio is present, for example, whether a target person is actively speaking. The system tracks target and noise signals to determine a location of a target audio source (e.g., a target person) relative to the microphone array. An improved generalized eigenvector process may be used to determine a direction of the target audio in real time. The determined direction may then be used by a spatial filtering process, such as a minimum variance distortionless response (MVDR) beamformer, to enhance the target audio. After the audio input signals are processed, an enhanced audio output signal may be used, for example, as audio output transmitted to one or more speakers, as voice communications in a telephone or voice over IP (VoIP) call, for speech recognition or voice command processing, or other voice application. A modified generalized eigenvector (GEV) system may be used to efficiently determine the direction of a target audio source in real-time, with or without the knowledge of the geometry of the array of microphones or the audio environment.”)
Donsbach in view of Shum and further in view of Masnadi-Shirazi are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach and Shum and Masnadi-Shirazi to incorporate the teachings of Masnadi-Shirazi to include outputting to the user via the at least one hearable device an enhanced audio signal, the enhanced audio signal comprising at least the separate audio signal. Doing so allows for speaker enhancement and noise reduction as recognized by Masnadi-Shirazi in [0013].
As to Claim 9, claim 9 is a parallel storage medium claim with limitations similar to that of Claim 2 and is rejected under the same rationale.
As to Claim 14, claim 14 is a parallel storage medium claim with limitations similar to that of Claim 7 and is rejected under the same rationale.
As to Claim 16, claim 16 is a parallel apparatus claim with limitations similar to that of Claim 2 and is rejected under the same rationale.
.
Claims 3, 4, 6 10, 11, 13, 17, 18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Donsbach (US Patent Number US 20220310109 A1), in view of Shum (US Patent Number US 20200380980 A1), and Further in view of Masnadi-Shirazi (US Patent Number US 20210390952 A1), and further in view of Kulkarni (US Patent Number US 11568038 B1).
Regarding claim 3, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 3. The method of Claim 1
Donsbach in view of Shum and further in view of Masnadi-Shirazi do not specifically teach, wherein said estimating is performed based on a calendar event of the user, wherein a scheduled time duration of the calendar event overlaps at least partially to a time of said capturing, wherein the calendar event indicates the identifier of the unidentified entity. However, KULKARNI does teach this limitation (See KULKARNI (4:59-5:17) “(20) In an embodiment, selection of the set of peers 112 is performed based at least in part on prior performance of each of the peers 112 in evaluating authentication information from users. The authentication system 110 evaluates past peer availability for evaluating authentication information and providing an authentication response based at least in part on this evaluation. In one embodiment, the authentication system 110 provides, to each peer identified in the peer database, sample authentication information that is used to evaluate the performance of the peers 112. In an embodiment, the authentication system 110 prepares the sample authentication information and maintains the expected authentication response that should be provided by the peers being evaluated. Based at least in part on the authentication responses from these peers 112, the authentication system 110 determines which peers 112 are more accurate in evaluating authentication information from users. This evaluation of peers 112 is used to update the peer database and to select the peers 112 that are to evaluate the authentication information from the user 102. These evaluations are performed by the authentication system 110 periodically or in response to a triggering event (e.g., suspicious activity detected, peers are removed from the pool of available peers, etc.) to improve the accuracy of the peer database and to identify reliable peers 112 for evaluation of authentication information.”)
Donsbach in view of Shum and further in view of Masnadi-Shirazi and KULKARNI are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach and Shum and Masnadi-Shirazi to incorporate the teachings of KULKARNI to include wherein said estimating is performed based on a calendar event of the user, wherein a scheduled time duration of the calendar event overlaps at least partially to a time of said capturing, wherein the calendar event indicates the identifier of the unidentified entity. Doing so allows for to view the authentication information that is provided to the authentication system in response to the authentication system's request as recognized by KULKARNI in (11:40-43).
Regarding Claim 4, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 4. The method of Claim 1
Donsbach in view of Shum and further in view of Masnadi-Shirazi do not specifically teach, wherein said estimating is performed based on identities of people in past communications of the user. However, KULKARNI does teach this limitation (See KULKARNI (4:59-5:17) “(20) In an embodiment, selection of the set of peers 112 is performed based at least in part on prior performance of each of the peers 112 in evaluating authentication information from users. The authentication system 110 evaluates past peer availability for evaluating authentication information and providing an authentication response based at least in part on this evaluation. In one embodiment, the authentication system 110 provides, to each peer identified in the peer database, sample authentication information that is used to evaluate the performance of the peers 112. In an embodiment, the authentication system 110 prepares the sample authentication information and maintains the expected authentication response that should be provided by the peers being evaluated. Based at least in part on the authentication responses from these peers 112, the authentication system 110 determines which peers 112 are more accurate in evaluating authentication information from users. This evaluation of peers 112 is used to update the peer database and to select the peers 112 that are to evaluate the authentication information from the user 102. These evaluations are performed by the authentication system 110 periodically or in response to a triggering event (e.g., suspicious activity detected, peers are removed from the pool of available peers, etc.) to improve the accuracy of the peer database and to identify reliable peers 112 for evaluation of authentication information.”)
Donsbach in view of Shum and further in view of Masnadi-Shirazi and KULKARNI are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach and Shum and Masnadi-Shirazi to incorporate the teachings of KULKARNI to include wherein said estimating is performed based on identities of people in past communications of the user. Doing so allows for to view the authentication information that is provided to the authentication system in response to the authentication system's request as recognized by KULKARNI in (11:40-43).
Regarding Claim 6, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 6. The method of Claim 1
Donsbach in view of Shum and further in view of Masnadi-Shirazi do not specifically teach, wherein said estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies a context of the at least one conversation based on the transcription, wherein said estimating is performed based on the context and based on previous conversations of the user with the context. However, KULKARNI does teach this limitation (see KULKARNI (4:59-5:17) “(20) In an embodiment, selection of the set of peers 112 is performed based at least in part on prior performance of each of the peers 112 in evaluating authentication information from users. The authentication system 110 evaluates past peer availability for evaluating authentication information and providing an authentication response based at least in part on this evaluation. In one embodiment, the authentication system 110 provides, to each peer identified in the peer database, sample authentication information that is used to evaluate the performance of the peers 112. In an embodiment, the authentication system 110 prepares the sample authentication information and maintains the expected authentication response that should be provided by the peers being evaluated. Based at least in part on the authentication responses from these peers 112, the authentication system 110 determines which peers 112 are more accurate in evaluating authentication information from users. This evaluation of peers 112 is used to update the peer database and to select the peers 112 that are to evaluate the authentication information from the user 102. These evaluations are performed by the authentication system 110 periodically or in response to a triggering event (e.g., suspicious activity detected, peers are removed from the pool of available peers, etc.) to improve the accuracy of the peer database and to identify reliable peers 112 for evaluation of authentication information.”)
Donsbach in view of Shum and further in view of Masnadi-Shirazi and KULKARNI are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Donsbach and Shumand Masnadi-Shirazi to incorporate the teachings of KULKARNI to include wherein said estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies a context of the at least one conversation based on the transcription, wherein said estimating is performed based on the context and based on previous conversations of the user with the context. Doing so allows for to view the authentication information that is provided to the authentication system in response to the authentication system's request as recognized by KULKARNI in (11:40-43).
As to Claim 10, claim 10 is a parallel storage medium claim with limitations similar to that of Claim 3 and is rejected under the same rationale.
As to Claim 11, claim 11 is a parallel storage medium claim with limitations similar to that of Claim 4 and is rejected under the same rationale.
As to Claim 13, claim 13 is a parallel storage medium claim with limitations similar to that of Claim 6 and is rejected under the same rationale.
As to Claim 17, claim 17 is a parallel apparatus claim limitations similar to that of Claim 3 and is rejected under the same rationale.
As to Claim 18, claim 18 is a parallel apparatus claim with limitations similar to that of Claim 4 and is rejected under the same rationale.
As to Claim 20, claim 20 is a parallel apparatus claim with limitations similar to that of Claim 6 and is rejected under the same rationale
Claims 5, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Donsbach (US Patent Number US 20220310109 A1), in view of Shum (US Patent Number US 20200380980 A1), and Further in view of Masnadi-Shirazi (US Patent Number US 20210390952 A1), and further in view of Steelberg (US Patent Number US 20220269761 A1).
As to Claim 5, Donsbach in view of Shum and further in view of Masnadi-Shirazi teaches 5. The method of Claim 1,
Donsbach in view of Shum and further in view of Masnadi-Shirazi do not specifically teach wherein said estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies within the transcription an indication of the identifier of the unidentified entity. However, Steelberg does teach this limitation, (see Steelberg [0006] Requesting the user to perform an action can also comprise: requesting the user to read out loud a text displayed on a displaying device; receiving an input audio data in response to requesting the user to read out loud the text; analyzing the input audio data to verify the user identity, using a voice verification engine; and transcribing the input audio data to verify that the text displayed is read correctly.”) (see Steelberg [0034] “At subprocess 120, the CMFA system can analyze, using an image or object classification neural network, the video data portion of the live multi-media stream (or video only data stream) to determine whether the user has performed the requested action such as to smile, look to the left, pick up an object, etc. The CMFA system can also analyze, using an audio classification neural network) the audio data portion of the live multi-media stream (or audio only data stream) to determine whether the user has read the requested words or sentence. For example, subprocess 120 can display one or more words on the user's display and instruct the user to read the one or more words. Subprocess 120 can also instructs the user by playing an audio through the user's device. Alternatively, subprocess 120 can instruct the user using both aural and visual presentation methods. For instance, subprocess 120 can instruct the user aurally to repeat the sentence “hello word, my name is Joe Smith” and/or display the sentence on the user's screen and instruct the user to read it out loud into the microphone.”)
Donsbach in view of Shum and further in view of Masnadi-Shirazi and Steelberg are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of Donsbach, Shum Masnadi-Shirazi to incorporate the teachings of Steelberg to include estimating is performed based on a transcription of at least one conversation in the environment, wherein a semantic analyzer identifies within the transcription an indication of the identifier of the unidentified entity. Doing so allows for a user to be correctly authenticated as recognized by Steelberg in [0030-0034].
As to Claim 12, claim 12 is a parallel storage medium claim with limitations similar to that of Claim 5 and is rejected under the same rationale.
As to Claim 19, claim 19 is a parallel apparatus claim with limitations similar to that of Claim 5 and is rejected under the same rationale.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTEN MICHELLE MASTERS whose telephone number is (703)756-1274. The examiner can normally be reached M-F 8:30 AM - 5:00 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Louis Desir can be reached at 571-272-7799. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KRISTEN MICHELLE MASTERS/Examiner, Art Unit 2659
/PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659