DETAILED ACTION Claims 1-20 are presented for examination. 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. 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 non-statutory subject matter. Claim s 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claimed invention is directed to “ speech recognition-based task organization ” (Spec: ¶ 3) without significantly more. Step Analysis 1: Statutory Category? Yes – The claims fall within at least one of the four categories of patent eligible subject matter. Process (claims 1-7) , Apparatus (claims 8-14) , Article of Manufacture (claims 15-20) Independent claims: Step Analysis 2A – Prong 1: Judicial Exception Recited? Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite: [Claim s 1 , 8, 15 ] A method of speech recognition-based task organization comprising: receiving voice data from a user corresponding to a task for the user to perform; identifying the task from the received voice data; comparing the identified task to prior tasks stored within a historical task database; determining an amount of time needed to complete the identified task based on the compared prior tasks; and tracking user actions and determining a task progress completion value based on the identified amount of time. It is noted that a database may simply be a collection of data. Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. A human user may recognize speech, including voice data, identify associated tasks, compare a task to prior tasks, determine an amount of time to complete tasks, track user actions and determine task progress completion, etc. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to task management (which is described as incorporating tasks performed by humans, per Spec: ¶ 2) , which (under its broadest reasonable interpretation) is an example of managing personal behavior, relationships, and/or interactions between people (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity. 2A – Prong 2: Integrated into a Practical Application? No – Th e judicial exception (s) is /are not integrated into a practical application. Claim 1 recites that the method of speech recognition-based task organization is executable by a processor. Claim 8 recites a computer system for speech recognition-based task organization, the computer system comprising: one or more computer-readable storage media configured to store computer program code; and one or more computer processors configured to access said computer program code and operate as instructed by said computer program code, said computer program code including various pieces of code to perform the recited operations. Claim 15 recites a computer program product for speech recognition-based task organization, comprising: one or more computer-readable storage devices; and program instructions stored on at least one of the one or more computer-readable storage devices, the program instructions configured to cause one or more computer processors to perform the recited operations. Claims 1, 8, and 15 recite identifying the task from the received voice data through natural language processing. The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶ 51 – “ These computer readable program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. ” ). The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The use of a memory or machine-readable media with executable instructions facilitates generic processor operations. The additional elements are recited at a high-level of generality ( i.e. , as generic process ing elements performing generic computer function s) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception (s) using generic computer component s . There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). A ccordingly, th e additional element s do not integrate the abstract idea s into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim s are directed to an abstract idea (s) . The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process ( see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)) . Claims 1, 8, and 15 recite identifying the task from the received voice data through natural language processing. Considering that the implementation of the machine learning model and/or the training of the model is performed using generic processing elements (in the form of performing natural language processing to identify a task, for example) , such an implementation is presented as a generic recitation of machine learning in the claims and as a general link to technology. The machine learning-based processing elements are simply tools to generally automate the underlying process that could be performed by a human. It is further noted that, as described in Applicant’s Specification, the machine learning operations are generic machine learning operations (Spec: ¶¶ 3-5, 8, 36, 42 – Natural language processing is referenced. ). The Specification presents no assertion that there is any improvement in the automated machine learning process itself. Such a generic recitation of machine learning, as recited in the claims, is little more than automating an analogous process that can be performed by a human. There is no transformation or reduction of a particular article to a different state or thing recited in the claims. Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately. 2B: Claim(s) Provide(s) an Inventive Concept? No – The claim s do not include additional elements that are sufficient to amount to significantly more than the judicial exception (s) . As discussed above with respect to integration of the abstract idea (s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exception s using a generic computer component (s) . Mere instructions to apply an exception using a generic computer component (s) cannot provide an inventive concept. The claim s are not patent eligible . D ependent claims: Step Analysis 2A – Prong 1: Judicial Exception Recited? Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite: [Claim 2] wherein the amount of time needed to complete the identified task is determined based on categorizing the identified task as a new task or as a task that is subordinate to a prior task stored within the historical task database. [Claim 3] identifying related subordinate tasks from among the prior tasks stored within the historical task database based on the identified task being categorized as subordinate to the prior task. [Claim 4] determining an overall amount of time needed to complete a project associated with the identified task based on the identified related subordinate tasks. [Claim 5] updating the task progress completion value based on receiving additional voice data. [Claim 6] archiving or deleting the identified task based on the identified task being determined to be duplicate, completed, or outdated. [Claim 7] developing a timeline for completion of the task based on the determined amount of time. It is noted that a database may simply be a collection of data. The dependent claims further present details of the abstract ideas identified in regard to the independent claim s. Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. A human user may recognize speech, including voice data, identify associated tasks, compare a task to prior tasks, determine an amount of time to complete tasks, track user actions and determine task progress completion, etc. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to task management (which is described as incorporating tasks performed by humans, per Spec: ¶ 2), which (under its broadest reasonable interpretation) is an example of managing personal behavior, relationships, and/or interactions between people (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity. 2A – Prong 2: Integrated into a Practical Application? No – Th e judicial exception (s) is /are not integrated into a practical application. The dependent claims include the additional elements of their independent claims. Claim 1 recites that the method of speech recognition-based task organization is executable by a processor. Claim 8 recites a computer system for speech recognition-based task organization, the computer system comprising: one or more computer-readable storage media configured to store computer program code; and one or more computer processors configured to access said computer program code and operate as instructed by said computer program code, said computer program code including various pieces of code to perform the recited operations. Claim 15 recites a computer program product for speech recognition-based task organization, comprising: one or more computer-readable storage devices; and program instructions stored on at least one of the one or more computer-readable storage devices, the program instructions configured to cause one or more computer processors to perform the recited operations. Claims 1, 8, and 15 recite identifying the task from the received voice data through natural language processing. The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶ 51 – “ These computer readable program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. ”). The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The use of a memory or machine-readable media with executable instructions facilitates generic processor operations. The additional elements are recited at a high-level of generality ( i.e. , as generic process ing elements performing generic computer function s) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception (s) using generic computer component s . There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). A ccordingly, th e additional element s do not integrate the abstract idea s into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim s are directed to an abstract idea (s) . The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process ( see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)) . Claims 1, 8, and 15 recite identifying the task from the received voice data through natural language processing. Considering that the implementation of the machine learning model and/or the training of the model is performed using generic processing elements (in the form of performing natural language processing to identify a task, for example), such an implementation is presented as a generic recitation of machine learning in the claims and as a general link to technology. The machine learning-based processing elements are simply tools to generally automate the underlying process that could be performed by a human. It is further noted that, as described in Applicant’s Specification, the machine learning operations are generic machine learning operations (Spec: ¶¶ 3-5, 8, 36, 42 – Natural language processing is referenced.). The Specification presents no assertion that there is any improvement in the automated machine learning process itself. Such a generic recitation of machine learning, as recited in the claims, is little more than automating an analogous process that can be performed by a human. There is no transformation or reduction of a particular article to a different state or thing recited in the claims. Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately. 2B: Claim(s) Provide(s) an Inventive Concept? No – The claim s do not include additional elements that are sufficient to amount to significantly more than the judicial exception (s) . As discussed above with respect to integration of the abstract idea (s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exception s using a generic computer component (s) . Mere instructions to apply an exception using a generic computer component (s) cannot provide an inventive concept. The claim s are not patent eligible . 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 1- 4, 6-11, 13-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over McQueen et al. (US 2011/0288900) in view of Friend et al. (US 2012/0035925) FILLIN "Insert the prior art relied upon." \d "[ 2 ]" . [Claim 1] McQueen discloses a method of task organization, executable by a processor, (¶¶ 157-172, 315, 318) comprising: receiving data corresponding to a task for the user to perform (¶¶ 133-137, claim 2 – Task information is identified and/or input.) ; identifying the task from the received data (¶ 137 – “Task data for example can lists of tasks to be performed, including subtasks and descriptors of all tasks and subtasks. The descriptors can be industry-based or workplace/organization specific. There is a thesaurus to normalise task data into a common task name and goal, since a task and a goal can come under a variety of terms. For example, the name "go to the bank" can also be termed "get some money" "get petty cash reimbursed" et cetera. Here goals and task can be confused and therefore the thesaurus can check name and/or goals to normalize the task data. This normalisation of task data can occur automatically or via task naming pick lists, task selection wheels or via a variety of other means. This normalisation allows like or similar tasks can be associated by their task data including their metadata, task name(s) and/or task goal(s).”) ; comparing the identified task to prior tasks stored within a histor ical task database ( ¶ 233 – “ Automated task management 70 is performed objectively so the relevant allocation of tasks can be applied via the extraction of like task data (or like time periods) compared with historical data, scheduling algorithms and/or behavioural files. That is, if a task with an estimate of 40 minutes duration is assigned then the allocation of time may bring forward a dialogue box stating that previous estimates of this time period have not been completed in the scheduled time. The dialogue box may also suggest an adjustment of the time period to be in line with previous task completion. Alternatively, a re-allocation of the time (in a scheduling context) may take place due to the task management software noting that tasks are never completed on a Friday afternoon after 7 pm. ”; ¶ 140 – “ The population of absent requirements allows normalisation of task requirement to take place so like tasks in the form of task requirements, task objects and even task schedules is enabled in some embodiments. This normalisation of task requirements to be associated with other specified task requirements allows task information to me adapted to personnel, group or project needs. For example, if "shopping for food" specifies two hours of time then one person is allocated as the resource; however, the resource may require personnel adjustments such as when Joe does the shopping it take three hours but when Robyn does it then the shopping only takes ninety minutes. Normalisation of requirements takes the spread of known activity and applies it to the individual's performance such that a specific user may be within one standard deviation of the mean and closely associated with the mode time taken when "shopping for food".”; ¶ 249 – “The historical time estimates are enabled to be viewed and assessed to state whether estimates and completion of tasks are aligned. When there is a constant error in specific time intervals or with specific tasks then a software generated estimated work schedule is enabled to be generated and overlaid on the user's estimated schedule such that the a difference between the two schedules can be revealed. ”; ¶ 253 – “ Past tasks performed by a user and/or project basis are listed and available in the form of a popup and/or dialogue box, which on selecting brings forth the details of the historical task management. Here a user can select a historical task that may have been completed and has similar features to the current task that need to be performed. ”; ¶ 255 – “ If the historical task has data that has not been recorded correctly, then the user may amend this record. This allows the adjustment of historical records to be aligned with practice. This enables objective schedules are to be adjusted and re-run if historical data is incorrect. Therefore, amendment of completed tasks must be available to allow correction of the historical and/or behaviour files. ” The existence of historical task records exemplifies a historical task database. ) ; determining an amount of time needed to complete the identified task based on the compared prior tasks ( ¶ 233 – “ Automated task management 70 is performed objectively so the relevant allocation of tasks can be applied via the extraction of like task data (or like time periods) compared with historical data, scheduling algorithms and/or behavioural files. That is, if a task with an estimate of 40 minutes duration is assigned then the allocation of time may bring forward a dialogue box stating that previous estimates of this time period have not been completed in the scheduled time. The dialogue box may also suggest an adjustment of the time period to be in line with previous task completion. Alternatively, a re-allocation of the time (in a scheduling context) may take place due to the task management software noting that tasks are never completed on a Friday afternoon after 7 pm. ”; ¶ 140 – “ The population of absent requirements allows normalisation of task requirement to take place so like tasks in the form of task requirements, task objects and even task schedules is enabled in some embodiments. This normalisation of task requirements to be associated with other specified task requirements allows task information to me adapted to personnel, group or project needs. For example, if "shopping for food" specifies two hours of time then one person is allocated as the resource; however, the resource may require personnel adjustments such as when Joe does the shopping it take three hours but when Robyn does it then the shopping only takes ninety minutes. Normalisation of requirements takes the spread of known activity and applies it to the individual's performance such that a specific user may be within one standard deviation of the mean and closely associated with the mode time taken when "shopping for food".”; ¶ 249 – “The historical time estimates are enabled to be viewed and assessed to state whether estimates and completion of tasks are aligned. When there is a constant error in specific time intervals or with specific tasks then a software generated estimated work schedule is enabled to be generated and overlaid on the user's estimated schedule such that the a difference between the two schedules can be revealed. ”; ¶ 253 – “ Past tasks performed by a user and/or project basis are listed and available in the form of a popup and/or dialogue box, which on selecting brings forth the details of the historical task management. Here a user can select a historical task that may have been completed and has similar features to the current task that need to be performed. ”) ; and tracking user actions and determining a task progress completion value based on the id entified amount of time (¶ 344 – “Managers, for example, use the preferred embodiment through the schedule view to get feedback on the time utilisation of their staff members, as well as view visually the time utilisation of staff members historically. The visualisation of a single staff member's schedule or a group of staff member's schedules, on one page enables a means to quickly visualise and ascertain the progress of the project and its underlying tasks.”; ¶ 372 – “Managers can also view the Scheduled work that was not completed by a user on a given day. The test for work being not completed will be work which is scheduled--not estimated--which does not have a diary entry pointing back to it.”; ¶ 349 – “Workers are also able to use this preferred embodiment (through the activity view) to plan and report on their daily or weekly activities. They will be able to see list a list of all activities that they should and could be working on through the course of a day, and they will be able to enter logs of work done (like timesheets) against the time schedules on a given day or week. Entering these diary entries will allow them to re-estimate the time remaining for an activity. ” ) . McQueen does not explicitly disclose a method of speech recognition-based task organization comprising: receiving voice data from a user corresponding to a task for the user to perform; identifying the task from the received voice data through natural language processing. Friend discloses a method of speech recognition-based task organization, executable by a processor (¶ 88 – “In addition, for use of natural language processing and metadata application, as described below, keywords from a captured voice and/or audio input may be used for generating a task or list item for presentation via the device 410 or other device, as described above with reference to FIGS. 1 through 7. For example, if a keyword such as "next" or the like is used in the audio, the captured text may be split into separate sub-tasks, and the associated audio file may be clipped to have just the audio of the actual sub-task associated with the sub-task. In addition, use of such natural language processing and metadata application may be useful in catching and discarding or otherwise disposing of incorrect or erroneous audio recordings.”; ¶ 114 – “Moreover, embodiments of the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like.”), comprising: receiving voice data from a user corresponding to a task for the user to perform (¶ 88 – “In addition, for use of natural language processing and metadata application, as described below, keywords from a captured voice and/or audio input may be used for generating a task or list item for presentation via the device 410 or other device, as described above with reference to FIGS. 1 through 7. For example, if a keyword such as "next" or the like is used in the audio, the captured text may be split into separate sub-tasks, and the associated audio file may be clipped to have just the audio of the actual sub-task associated with the sub-task. In addition, use of such natural language processing and metadata application may be useful in catching and discarding or otherwise disposing of incorrect or erroneous audio recordings.”); identifying the task from the received voice data through natural language processing (¶ 88 – “In addition, for use of natural language processing and metadata application, as described below, keywords from a captured voice and/or audio input may be used for generating a task or list item for presentation via the device 410 or other device, as described above with reference to FIGS. 1 through 7. For example, if a keyword such as "next" or the like is used in the audio, the captured text may be split into separate sub-tasks, and the associated audio file may be clipped to have just the audio of the actual sub-task associated with the sub-task. In addition, use of such natural language processing and metadata application may be useful in catching and discarding or otherwise disposing of incorrect or erroneous audio recordings.”) . The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify McQueen to be adaptive to handle a method of speech recognition-based task organization comprising: receiving voice data from a user corresponding to a task for the user to perform; identifying the task from the received voice data through natural language processing in order to more effectively and conveniently capture task information (as suggested in ¶ 5 of Friend), thereby addressing prior art problems that “ entering task or list items may not be readily available or appropriate under certain circumstances, for example, while the user is driving, or while the user is on the go. ” (Friend: ¶ 3) [Claim 2] McQueen discloses wherein the amount of time needed to complete the identified task is determined based on categorizing the identified task as a new task or as a task th at is subordinate to a prior task stored within the historical task database (¶ 206 – “The preferred embodiment is enabled to integrate additional data in the form of task priority and dependency so as to display the priorities of the task. This display of task priority may also be derived from historical allocations with workflow information incorporated.”; ¶ 137 – “Task data for example can lists of tasks to be performed, including subtasks and descriptors of all tasks and subtasks. The descriptors can be industry-based or workplace/organization specific. There is a thesaurus to normalise task data into a common task name and goal, since a task and a goal can come under a variety of terms. For example, the name "go to the bank" can also be termed "get some money" "get petty cash reimbursed" et cetera. Here goals and task can be confused and therefore the thesaurus can check name and/or goals to normalize the task data. This normalisation of task data can occur automatically or via task naming pick lists, task selection wheels or via a variety of other means. This normalisation allows like or similar tasks can be associated by their task data including their metadata, task name(s) and/or task goal(s).”; ¶ 138 – “In one embodiment the adjustment time/resources, priority, policy/rules, workflow and/or dependency requirements are enabled so that the addition, subtraction and/or change in level of a requirement are enabled. For example, this adjustment can be performed by a user, where on reflection, the allocation of time is too low so that the user allocates further time to the task requirement; however, the resources available may be too high and therefore the subtraction of resources is enabled. Likewise the priority many be changed to a lower or higher level as circumstances change.” Subordinate tasks may include subtasks and/or tasks/subtasks of lower priority. ; ¶ 253 – “Past tasks performed by a user and/or project basis are listed and available in the form of a popup and/or dialogue box, which on selecting brings forth the details of the historical task management. Here a user can select a historical task that may have been completed and has similar features to the current task that need to be performed.” Similar past tasks may be identified to help assess requirements for a current task, which implies that the current task is a new task. ; ¶ 255 – “ If the historical task has data that has not been recorded correctly, then the user may amend this record. This allows the adjustment of historical records to be aligned with practice. This enables objective schedules are to be adjusted and re-run if historical data is incorrect. Therefore, amendment of completed tasks must be available to allow correction of the historical and/or behaviour files. ” The existence of historical task records exemplifies a historical task database. ) . [Claim 3] McQueen discloses identifying related subordinate tasks from among the prior tasks stored within the historical task database based on the identified task being categorized as subordinate to the prior task (¶ 206 – “The preferred embodiment is enabled to integrate additional data in the form of task priority and dependency so as to display the priorities of the task. This display of task priority may also be derived from historical allocations with workflow information incorporated.”; ¶ 137 – “Task data for example can lists of tasks to be performed, including subtasks and descriptors of all tasks and subtasks. The descriptors can be industry-based or workplace/organization specific. There is a thesaurus to normalise task data into a common task name and goal, since a task and a goal can come under a variety of terms. For example, the name "go to the bank" can also be termed "get some money" "get petty cash reimbursed" et cetera. Here goals and task can be confused and therefore the thesaurus can check name and/or goals to normalize the task data. This normalisation of task data can occur automatically or via task naming pick lists, task selection wheels or via a variety of other means. This normalisation allows like or similar tasks can be associated by their task data including their metadata, task name(s) and/or task goal(s).”; ¶ 138 – “In one embodiment the adjustment time/resources, priority, policy/rules, workflow and/or dependency requirements are enabled so that the addition, subtraction and/or change in level of a requirement are enabled. For example, this adjustment can be performed by a user, where on reflection, the allocation of time is too low so that the user allocates further time to the task requirement; however, the resources available may be too high and therefore the subtraction of resources is enabled. Likewise the priority many be changed to a lower or higher level as circumstances change.” Subordinate tasks may include subtasks and/or tasks/subtasks of lower priority. ; ¶ 255 – “ If the historical task has data that has not been recorded correctly, then the user may amend this record. This allows the adjustment of historical records to be aligned with practice. This enables objective schedules are to be adjusted and re-run if historical data is incorrect. Therefore, amendment of completed tasks must be available to allow correction of the historical and/or behaviour files. ” The existence of historical task records exemplifies a historical task database. ). [Claim 4] McQueen discloses determining an overall amount of time needed to complete a project associated with the identified task based on the identified related subordinate tasks ( ¶¶ 217–220 – “ [0217] Providing the means for task allocation report(s) enables the user to visualise the task allocation(s) as SaaS or the like. This task allocation allows the user to monitor differences in the task allocation over time and with particular associations with other tasks and/or users. Thereby, ascertaining what associations enhanced task performance can be ascertained. [0218] Likewise, different projects can be compared under the same conditions such as time such that a determination of project completion can be ascertained. [0219] Tasks require a better alignment to increase the output of projects. Therefore, the means to educate and provide feedback to users regarding task allocation report(s) is enabled. Providing feedback via task allocation report(s) as to what types of task allocation(s) are successful and what times and/or resources were needed is a means to directly assess output. [0220] The feedback as to time and/or resources is available to inform the user as to whether to delay the task allocation on-project or to send it to near time scheduling. ”; ¶ 137 – “Task data for example can lists of tasks to be performed, including subtasks and descriptors of all tasks and subtasks. ”) . [Claim 6] McQueen does not explicitly disclose archiving or deleting the identified task based on the identified task being determined to be duplicate, completed, or outdated. However, in reference to displayed tasks (Friend: fig. 5), Friend states, “According to an embodiment, the list authoring surface may automatically hide some items or information so the lists do not get too long. For example, when a list item has been on the user's list for more than two weeks, or two weeks past the due date, it automatically gets hidden so the user does not feel overwhelmed or guilty for things he/she has not accomplished or things he/she does not intend to accomplish. Alternatively, an expiration date may be automatically set on every item when it is added such that items are hidden from display after the expiration date passes. ” (Friend: ¶ 65) Hiding an item that a user does not intend to accomplish is an example of deleting a task (from a display) when the item is outdated. Friend also describes how annotated information may be stored and how a user may check off completed tasks in the user interface (Friend: ¶ 29 – “ As illustrated in FIG. 1, one or more functionality buttons or controls 125, 130, 135, 140 may be provided in the list authoring surface UI 120 for editing or otherwise manipulating information contained in the UI 120. For example, a control 125 may be utilized for "checking off" completed tasks, a control 130 may be utilized for adding additional tasks, events or other information, a control 135 may be utilized for importing information or for annotating information to be stored or displayed in the user interface 120, and a variety of other controls 140 may be provided for other types of editing, sorting, filtering, searching, and the like information contained in the user interface 120. According to embodiments, selection of one or more functionality controls in association with a task or list item may cause a tagging of the task or list item with metadata associated with the selected functionality control that may be used subsequently for processing the task or list item, as described below. ”). This at least suggests the ability to archive completed tasks. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify McQueen to perform the step of archiving or deleting the identified task based on the identified task being determined to be duplicate, completed, or outdated in order to present users with cleaner user interfaces that present the most relevant task-related information that each user needs in the moment and that allow for task-related information to be delete d and/ or archive d appropriately when it is no longer needed at the moment , but may (or may not) be needed for future reference . [Claim 7] McQueen discloses developing a timeline for completion of the task based on the determined amount of time ( ¶ 344 – “ Managers, for example, use the preferred embodiment through the schedule view to get feedback on the time utilisation of their staff members, as well as view visually the time utilisation of staff members historically. The visualisation of a single staff member's schedule or a group of staff member's schedules, on one page enables a means to quickly visualise and ascertain the progress of the project and its underlying tasks. ”; ¶¶ 409-414 – “ [0409] Historically recorded time--this shows the time that was actually logged as diary entries, and is a solid block of colour on time in the past. This will of course include previous days, along with time logged during the current day. Something like blue would make sense here. [0410] Scheduled time--this shows time into the future which has been "scheduled". `Scheduled` time will be created in one of two ways: [0411] The user can specifically create a diary with a start and an end date/time. This will create an automatic Time Schedule linked to that diary entry for easy display in the chart, or [0412] The user will have previously converted Estimated Work into Scheduled Work on a Date. Because this time is blocked in, it appears at the bottom of the bar chart. [0413] Estimated time--this shows time into the future which has been "estimated". Estimated time is the time that the system thinks it will need to be allocated on a day by day basis to get an Activity completed by its deadline; because it is averaged and a guess, we want to show it on `top` of the scheduled time. [0414] Overdue time--this will apply only to the section of the chart representing today (so, if the selected date range doesn't include today, then it won't be shown at all), and will include a bar on top of both the scheduled and the estimated time of a different colour . This bar will be a sum of all of the remaining estimated hours for an activity which has a due date in the past. Visually, it could be tricky to show this (if there is a lot of overdue stuff, the bar could be quite high) without changing the scale for the whole chart so much that the rest of the bars become indistinguishable. It could be desirable to either toggle this off by default, or place the bar in a different part of the screen (so it doesn't screw with the Y axis scale for the schedule), or alternatively, instead of lumping overdue work onto "today", displaying the "work" for each overdue Time Estimate on the day that the Time Estimate was due, with a height equal to the number of hours that the Time Estimate still has remaining. ”) . [Claims 8- 11, 13- 14] Claims 8- 11 and 13- 14 recite limitations already addressed by the rejections of claims 1- 4 and 6- 7 above; therefore, the same rejections a pply. Furthermore, McQueen and Friend each disclose a computer system for task organization, the computer system comprising: one or more computer-readable storage media configured to store computer program code; and one or more computer processors configured to access said computer program code and operate as instructed by said computer program code, said computer program code including various pieces of code to perform the respectively disclosed operations (McQueen: ¶¶ 132, 157-172 ; Friend: ¶¶ 117-121 ) . [Claims 15 - 18, 20] Claims 15 - 18 and 20 recite limitations already addressed by the rejections of claims 1- 4 and 6 above; therefore, the same rejections apply. Furthermore, McQueen and Friend each disclose a computer program product for task organization, comprising: one or more computer-readable storage devices; and program instructions stored on at least one of the one or more computer-readable storage devices, the program instructions configured to cause one or more computer processors to pe rform the respectively disclosed operations (McQueen: ¶¶ 132, 157-172; Friend: ¶¶ 117-121). Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over McQueen et al. (US 2011/0288900) in view of Friend et al. (US 2012/0035925), as applied to claims 1, 8, and 15 above, in view of Nashif (US 2021/0158241) FILLIN "Insert the prior art relied upon." \d "[ 2 ]" . [Clai ms 5, 12, 19] McQueen and Friend do not explicitly disclose updating the task progress completion value based on receiving additional voice data. Nashif allows for workers to update a status of a task, including upon completion of the task, via voice input ( Nashif : ¶¶ 40, 89-92). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify the McQueen-Friend combination to perform the step of updating the task progress completion value based on receiving additional voice data in order to facilitate more convenien t communications between workers and the task tracking system, including the ability to communicate in a handsfree manner. Conclusion T he prior art made of record and not relied upon is considered pertinent to applicant's dis closure. Hufnagel et al. (US 2010/ 0 004921) – Presents a to-do list of a user’s tasks to be performed in a chronological order. Mitra et al. (US 2022/0343155) – Predicts a performance efficie