Patents Assigned to Semantic Machines, Inc.
  • Patent number: 10824798
    Abstract: A data collection system is based on a general set of dialogue acts which are derived from a database schema. Crowd workers perform two types of tasks: (i) identification of sensical dialogue paths and (ii) performing context-dependent paraphrasing of these dialogue paths into real dialogues. The end output of the system is a set of training examples of real dialogues which have been annotated with their logical forms. This data can be used to train all three components of the dialogue system: (i) the semantic parser for understanding context-dependent utterances, (ii) the dialogue policy for generating new dialogue acts given the current state, and (iii) the generation system for both deciding what to say and how to render it in natural language.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: November 3, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Percy Shuo Liang, Daniel Klein, Laurence Steven Gillick, Jordan Rian Cohen, Linda Kathleen Arsenault, Joshua James Clausman, Adam David Pauls, David Leo Wright Hall
  • Patent number: 10762892
    Abstract: A method for a dialogue system includes establishing a dialogue session between an application executing on a server and a remote machine. The dialogue session includes one or more utterances received from a user at the remote machine. A natural language processing machine identifies a request associated with a computer-readable representation of an utterance. A dialogue expansion machine generates a plurality of alternative actions for responding to the request. A previously-trained machine learning confidence model assesses a confidence score for each alternative. If a highest confidence score for a top alternative does not satisfy a threshold, the plurality of alternatives including the top alternative are transmitted to a remote machine (which may be the same remote machine or a different remote machine) for review by a human reviewer. After the dialogue system and/or the human reviewer select an alternative, computer-readable instructions defining the selected alternative are executed.
    Type: Grant
    Filed: July 16, 2018
    Date of Patent: September 1, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Jesse Daniel Eskes Rusak, David Leo Wright Hall, Jason Andrew Wolfe, Daniel Lawrence Roth, Daniel Klein, Jordan Rian Cohen
  • Patent number: 10720148
    Abstract: A method for a dialogue system includes establishing a dialogue session between an application executing on a server and a remote machine. The dialogue session includes one or more utterances received from a user at the remote machine. A natural language processing machine identifies a request associated with a computer-readable representation of an utterance. A dialogue expansion machine generates a plurality of alternative actions for responding to the request. A previously-trained machine learning confidence model assesses a confidence score for each alternative. If a highest confidence score for a top alternative does not satisfy a threshold, the plurality of alternatives including the top alternative are transmitted to a remote machine (which may be the same remote machine or a different remote machine) for review by a human reviewer. After the dialogue system and/or the human reviewer select an alternative, computer-readable instructions defining the selected alternative are executed.
    Type: Grant
    Filed: July 16, 2018
    Date of Patent: July 21, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Jesse Daniel Eskes Rusak, David Leo Wright Hall, Jason Andrew Wolfe, Daniel Lawrence Roth, Daniel Klein, Jordan Rian Cohen
  • Patent number: 10713288
    Abstract: A system that generates natural language content. The system generates and maintains a dialogue state representation having a process view, query view, and data view. The three-view dialogue state representation is continuously updated during discourse between an agent and a user, and rules can be automatically generated based on the discourse. Upon a content generation event, an object description can be generated based on the dialogue state representation. A string is then determined from the object description, using a hybrid approach of the automatically generated rules and other rules learned from annotation and other user input. The string is translated to text or speech and output by the agent. The present system also incorporates learning techniques, for example when ranking output and processing annotation templates.
    Type: Grant
    Filed: February 8, 2018
    Date of Patent: July 14, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, David Leo Wright Hall, Daniel Klein, Adam David Pauls
  • Publication number: 20200193970
    Abstract: A system that allows non-engineers administrators, without programming, machine language, or artificial intelligence system knowledge, to expand the capabilities of a dialogue system. The dialogue system may have a knowledge system, user interface, and learning model. A user interface allows non-engineers to utilize the knowledge system, defined by a small set of primitives and a simple language, to annotate a user utterance. The annotation may include selecting actions to take based on the utterance and subsequent actions and configuring associations. A dialogue state is continuously updated and provided to the user as the actions and associations take place. Rules are generated based on the actions, associations and dialogue state that allows for computing a wide range of results.
    Type: Application
    Filed: February 26, 2020
    Publication date: June 18, 2020
    Applicant: Semantic Machines, Inc.
    Inventors: Percy Shuo Liang, David Leo Wright Hall, Joshua James Clausman
  • Patent number: 10643601
    Abstract: A conversational system receives an utterance, and a parser performs a parsing operation on the utterance, resulting in some words being parsed and some words not being parsed. For the words that are not parsed, words or phrases determined to be unimportant are ignored. The resulting unparsed words are processed to determine the likelihood they are important and whether they should be addressed by the automated assistant. For example, if a score associated with an important unparsed word achieves a particular threshold, then a course of action to take for the utterance may include providing a message that the portion of the utterance associated with the important unparsed word cannot be handled.
    Type: Grant
    Filed: January 31, 2018
    Date of Patent: May 5, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: David Leo Wright Hall, Daniel Klein
  • Patent number: 10586530
    Abstract: A system that allows non-engineers administrators, without programming, machine language, or artificial intelligence system knowledge, to expand the capabilities of a dialogue system. The dialogue system may have a knowledge system, user interface, and learning model. A user interface allows non-engineers to utilize the knowledge system, defined by a small set of primitives and a simple language, to annotate a user utterance. The annotation may include selecting actions to take based on the utterance and subsequent actions and configuring associations. A dialogue state is continuously updated and provided to the user as the actions and associations take place. Rules are generated based on the actions, associations and dialogue state that allows for computing a wide range of results.
    Type: Grant
    Filed: February 23, 2018
    Date of Patent: March 10, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Percy Shuo Liang, David Leo Wright Hall, Joshua James Clausman
  • Publication number: 20190347321
    Abstract: A method for configuring an automated dialogue system uses traces of interactions via a graphical user interface (GUI) for an application. Each trace includes interactions in the context of a plurality of presentations of the GUI. Elements of one or more presentations of the GUI are identified, and templates are associated with portions of the trace. Each template has one or more defined inputs and a defined output. For each template of the plurality of templates, the portions of the traces are processed to automatically configure the template by specifying a procedure for providing values of inputs to the template via the GUI and obtaining a value of an output. The automated dialogue system is configured with the configured templates, thereby avoiding manual configuration of the dialogue system.
    Type: Application
    Filed: July 26, 2019
    Publication date: November 14, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Adam David Pauls, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak
  • Publication number: 20190295545
    Abstract: A method for generating a dialogue event in a natural language processing system comprises loading, into a computer memory, a computer-readable seed command describing an ordered sequence of two or more top-level dialogue events. A dialogue event includes a client utterance or a computerized assistant response. The seed command includes one or more sub-commands, each sub-command corresponding to a portion of the ordered sequence of two or more top-level dialogue events, and the focal sub-command of the one or more sub-commands being parametrized by a seed semantic parameter. The method further comprises re-parametrizing the focal sub-command by outputting a plurality of different re-parametrized focal sub-commands wherein, in each re-parametrized focal sub-command, the seed semantic parameter is replaced by one of a plurality of different synthetic semantic parameters.
    Type: Application
    Filed: December 21, 2018
    Publication date: September 26, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jacob Daniel ANDREAS, Daniel Louis KLEIN, David Leo Wright HALL, Laurence Steven GILLICK, Pengyu CHEN
  • Patent number: 10402488
    Abstract: A method for configuring an automated dialog system uses traces of interactions via a graphical user interface (GUI) for an application. Each trace includes interactions in the context of a plurality of presentations of the GUI. Elements of one or more presentations of the GUI are identified, and templates are associated with portions of the trace. Each template has one or more defined inputs and a defined output. For each template of the plurality of templates, the portions of the traces are processed to automatically configure the template by specifying a procedure for providing values of inputs to the template via the GUI and obtaining a value of an output. The automated dialog system is configured with the configured templates, thereby avoiding manual configuration of the dialog system.
    Type: Grant
    Filed: November 22, 2016
    Date of Patent: September 3, 2019
    Assignee: Semantic Machines, Inc.
    Inventors: Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Adam David Pauls, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak
  • Publication number: 20190244601
    Abstract: A computing device includes a display configured to present a graphical user interface. The graphical user interface includes a transcript portion configured to display an unannotated transcript representing an ordered sequence of one or more dialogue events involving a client and a computerized assistant, at least one of the dialogue events taking the form of an example client utterance, and an annotation portion configured to display a hierarchical menu including a plurality of candidate utterance annotations. An utterance annotation machine is configured to receive one or more computer inputs selecting, for each of one or more response parameters in the example client utterance, utterance annotations from the hierarchical menu that collectively define a machine-readable interpretation of the example client utterance.
    Type: Application
    Filed: December 21, 2018
    Publication date: August 8, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jesse Daniel Eskes RUSAK, Percy Shuo LIANG
  • Publication number: 20190237061
    Abstract: A method for generating training data for training a natural language processing system comprises loading, into a computer memory, a computer-readable transcript representing an ordered sequence of one or more dialogue events. The method further comprises acquiring a computer-readable command describing an exemplary ordered subsequence of one or more dialogue events from the computer-readable transcript. The method further comprises re-parametrizing the computer-readable command with an alternative semantic parameter. The method further comprises generating an alternative ordered subsequence of one or more dialogue events based on the re-parametrized computer-readable command. The method further comprises outputting, to a data store, an alternative computer-readable transcript including the alternative ordered subsequence of one or more dialogue events, the alternative computer-readable transcript having a predetermined format usable to train the computerized assistant.
    Type: Application
    Filed: December 21, 2018
    Publication date: August 1, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jesse Daniel Eskes RUSAK, David Leo Wright HALL, Daniel Louis KLEIN, Percy Shuo LIANG
  • Patent number: 10319381
    Abstract: An interaction assistant conducts multiple turn interaction dialogs with a user in which context is maintained between turns, and the system manages the dialog to achieve an inferred goal for the user. The system includes a linguistic interface to a user and a parser for processing linguistic events from the user. A dialog manager of the system is configured to receive alternative outputs from the parser, and selecting an action and causing the action to be performed based on the received alternative outputs. The system further includes a dialog state for an interaction with the user, and the alternative outputs represent alternative transitions from a current dialog state to a next dialog state. The system further includes a storage for a plurality of templates, and wherein each dialog state is defined in terms of an interrelationship of one or more instances of the templates.
    Type: Grant
    Filed: February 14, 2018
    Date of Patent: June 11, 2019
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak, Andrew Robert Volpe, Steven Andrew Wegmann, Taylor Darwin Berg-Kirkpatrick, Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Michael Newman, Adam David Pauls
  • Patent number: 10276160
    Abstract: An interaction assistant conducts multiple turn interaction dialogs with a user in which context is maintained between turns, and the system manages the dialog to achieve an inferred goal for the user. The system includes a linguistic interface to a user and a parser for processing linguistic events from the user. A dialog manager of the system is configured to receive alternative outputs from the parser, and selecting an action and causing the action to be performed based on the received alternative outputs. The system further includes a dialog state for an interaction with the user, and the alternative outputs represent alternative transitions from a current dialog state to a next dialog state. The system further includes a storage for a plurality of templates, and wherein each dialog state is defined in terms of an interrelationship of one or more instances of the templates.
    Type: Grant
    Filed: November 10, 2016
    Date of Patent: April 30, 2019
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, Taylor Darwin Berg-Kirkpatrick, Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Michael Newman, Adam David Pauls, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak, Andrew Robert Volpe, Steven Andrew Wegmann
  • Publication number: 20190103107
    Abstract: A method includes receiving an utterance at a computerized automated assistant system, and detecting, via a date/time constraint module of the computerized automated assistant system, one or more constraints in the utterance associated with a date or time. The utterance is associated with a domain. The method further comprises generating, via the date/time constraint module, a periodic set for each of the one or more constraints associated with the date or time, and combining, via the date/time constraint module, the one or more periodic sets. The method further comprises processing, via a dialogue manager module of the computerized automated assistant system, the combined periodic sets to determine an action, and executing the action at the computerized automated assistant system.
    Type: Application
    Filed: July 13, 2018
    Publication date: April 4, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jordan Rian Cohen, David Leo Wright Hall, Jason Andrew Wolfe, Daniel Lawrence Roth, Daniel Klein
  • Publication number: 20190103092
    Abstract: A method for a dialogue system includes establishing a dialogue session between an application executing on a server and a remote machine. The dialogue session includes one or more utterances received from a user at the remote machine. A natural language processing machine identifies a request associated with a computer-readable representation of an utterance. A dialogue expansion machine generates a plurality of alternative actions for responding to the request. A previously-trained machine learning confidence model assesses a confidence score for each alternative. If a highest confidence score for a top alternative does not satisfy a threshold, the plurality of alternatives including the top alternative are transmitted to a remote machine (which may be the same remote machine or a different remote machine) for review by a human reviewer. After the dialogue system and/or the human reviewer select an alternative, computer-readable instructions defining the selected alternative are executed.
    Type: Application
    Filed: July 16, 2018
    Publication date: April 4, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jesse Daniel Eskes Rusak, David Leo Wright Hall, Jason Andrew Wolfe, Daniel Lawrence Roth, Daniel Klein, Jordan Rian Cohen
  • Publication number: 20190066660
    Abstract: An automated natural dialogue system provides a combination of structure and flexibility to allow for ease of annotation of dialogues as well as learning and expanding the capabilities of the dialogue system based on natural language interactions.
    Type: Application
    Filed: August 28, 2018
    Publication date: February 28, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Percy Shuo Liang, David Leo Wright Hall, Jesse Daniel Eskes Rusak, Daniel Klein
  • Publication number: 20180374479
    Abstract: A system that provides a sharable language interface for implementing automated assistants in new domains and applications. A dialogue assistant that is trained in a first domain can receive a specification in a second domain. The specification can include language structure data such as schemas, recognizers, resolvers, constraints and invariants, actions, language hints, generation template, and other data. The specification data is applied to the automated assistant to enable the automated assistant to provide interactive dialogue with a user in a second domain associated with the received specification. In some instances, portions of the specification may be automatically mapped to portions of the first domain. By having the ability to learn new domains and applications through receipt of objects and properties rather than retooling the interface entirely, the present system is much more efficient at learning how to provide interactive dialogue in new domains than previous systems.
    Type: Application
    Filed: March 2, 2018
    Publication date: December 27, 2018
    Applicant: Semantic Machines, Inc.
    Inventors: David Leo Wright Hall, Daniel Klein, David Ernesto Heekin Burkett, Jordan Rian Cohen, Daniel Lawrence Roth
  • Publication number: 20180350349
    Abstract: A system that allows non-engineers administrators, without programming, machine language, or artificial intelligence system knowledge, to expand the capabilities of a dialogue system. The dialogue system may have a knowledge system, user interface, and learning model. A user interface allows non-engineers to utilize the knowledge system, defined by a small set of primitives and a simple language, to annotate a user utterance. The annotation may include selecting actions to take based on the utterance and subsequent actions and configuring associations. A dialogue state is continuously updated and provided to the user as the actions and associations take place. Rules are generated based on the actions, associations and dialogue state that allows for computing a wide range of results.
    Type: Application
    Filed: February 23, 2018
    Publication date: December 6, 2018
    Applicant: Semantic Machines, Inc.
    Inventors: Percy Shuo Liang, David Leo Wright Hall, Joshua James Clausman
  • Publication number: 20180308481
    Abstract: A system that transforms queries for each dialogue domain into constraint graphs, including both constraints explicitly provided by the user as well as implicit constraints that are inherent to the domain. Once all the domain-specific constraints have been collected into a graph, general-purpose domain-independent algorithms can be used to draw inferences for both intent disambiguation and constraint propagation. Given a candidate interpretation of a user utterance as the posting, modification, or retraction of a constraint, constraint inference techniques such as arc consistency and satisfiability checking can be used to answer questions. The underlying engine can also handle soft constraints, in cases where the constraint may be violated for some cost or in cases where there are different degrees of violations.
    Type: Application
    Filed: April 20, 2018
    Publication date: October 25, 2018
    Applicant: Semantic Machines, Inc.
    Inventors: Jordan Cohen, Daniel Klein, David Leo Wright Hall, Jason Wolfe, Daniel Roth