Patents by Inventor David Nahamoo

David Nahamoo has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20190304445
    Abstract: A computer-implemented conversational system framework to perform tasks associated with a client request. A conversation application executing on a hardware processor provides application workflow orchestration, the conversation application receiving a client request and sending one or more application requests based on the application workflow orchestration. A conversation system executing on a hardware processor provides conversation workflow orchestration, the conversation system receiving the one or more application requests. The conversation application and the conversation system develop dialog context and store the dialog context in a memory device. The conversation application and the conversation system develop the dialog context by invoking at least one micro-service to perform tasks associated with the one or more application requests. The conversation application generates a response to the client request based on the developed dialog context.
    Type: Application
    Filed: September 11, 2018
    Publication date: October 3, 2019
    Inventors: David Nahamoo, Lazaros Polymenakos, Nathaniel Mills, Li Zhu
  • Patent number: 10395641
    Abstract: Provided herein is a system, method, and computer program product for modifying a language conversation model of the language learning system. Modifying the language conversation model includes receiving, using a conversational sub-system, voice inputs. The conversational sub-system converts the voice inputs to voice input data and processes the voice input data. The conversational sub-system detects an error in processing the voice input data and, based at least in part on the error, stores additional data comprising additional voice input data in a memory. The conversational sub-system applies machine learning to the additional data to derive a function that is not enabled within the language conversation model. The conversational sub-system develops an update that enables the language conversation model to implement the function. The update is applied to the language conversation model.
    Type: Grant
    Filed: February 8, 2017
    Date of Patent: August 27, 2019
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Pankaj Dhoolia, Sachindra Joshi, David Nahamoo, Dinesh Raghu
  • Publication number: 20190228327
    Abstract: Methods and systems for determining control inputs to a manufacturing apparatus to manufacture a product are described. A processor may receive model data including initial state data indicating an initial state of an input material, a set of model control inputs, and target measurement data associated with a target product. The processor may learn a causal predictive model based on the target data. Each state of the causal predictive model may be based on an application of the model control inputs on a previous state of the causal predictive model. The processor may compare a final state of the causal predictive model with the target measurement data to determine a difference. The processor may determine, based on the difference, a set of control inputs to be assigned to one or more controls. The one or more controls may define a design of the manufacturing process of an end product.
    Type: Application
    Filed: January 22, 2018
    Publication date: July 25, 2019
    Inventors: Lior Horesh, Chai W. Wu, Ramesh Natarajan, Raya Horesh, David Nahamoo, Christopher Wildsmith, Michael Widman
  • Publication number: 20190212879
    Abstract: A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A unified semantic representation of conversational content between a user and conversational system is created as a contextual graph of concepts and relations. A set of subgraph components of the semantic contextual graph dynamically identified based on a current dialog activity. The identified set of subgraph components in a user interface as a set of graphical elements representing respective concepts and relations.
    Type: Application
    Filed: January 11, 2018
    Publication date: July 11, 2019
    Inventors: Rangachari Anand, Ashima Arora, Raimo Bakis, Song Feng, Jatin Ganhotra, Chulaka Gunasekara, David Nahamoo, Lazaros Polymenakos, Sunil D Shashidhara, Li Zhu
  • Publication number: 20190213284
    Abstract: A method, apparatus and computer program product for presenting a user interface for a conversational system is described. For each of a set of user utterances produced in a dialog with the conversational system, a semantic meaning representation is determined. The semantic meaning representations are converted to respective sentential concept graphs. A first sentential concept graph is consolidated into a unified contextual graph. The unified contextual graph is updated based on new sentential concept graphs while the dialog with the conversational system progresses.
    Type: Application
    Filed: January 11, 2018
    Publication date: July 11, 2019
    Inventors: Rangachari Anand, Ashima Arora, Raimo Bakis, Song Feng, Jatin Ganhotra, Chulaka Gunasekara, David Nahamoo, Lazaros Polymenakos, Sunil D. Shashidhara, Li Zhu
  • Publication number: 20190205488
    Abstract: Methods and systems for generating output of a simulation model in a simulation system are described. In an example, a processor may retrieve observed output data from a memory. The observed output data may be generated based on a simulation operator of a simulation model. The processor may further optimize a generalization error of a distance measure between the observed output data and model output data. The model output data may be generated based on a high-fidelity operator. The processor may further determine a correction operator based on the optimized generalization error of the distance measure. The processor may further append the correction operator to the simulation operator to produce a supplemented operator. The processor may further generate supplemented output data by applying the simulation model with the supplemented operator on a set of inputs.
    Type: Application
    Filed: January 3, 2018
    Publication date: July 4, 2019
    Inventors: Lior Horesh, Ning Hao, Raya Horesh, David Nahamoo, Misha E. Kilmer
  • Publication number: 20190188067
    Abstract: A cognitive conversation system that generates effective diagnostic questions is provided. The cognitive conversation system receives a set of currently known symptoms (or currently available answers to diagnostic questions) of a reported problem or fault. The system identifies (i) a set of possible root causes of the reported problem based on the currently known symptoms and (ii) probabilities for the set of possible root causes by using a bipartite graph data structure that links possible symptoms with possible root causes. Upon determining that at least one possible root cause has a probability that is higher than a threshold, the system presents an explanation or solution associated with the at least one possible root cause. Upon determining that none of the possible root causes in the set of possible root causes has a probability higher than the threshold, the system presents a question based on information entropy that is computed based on probabilities of the identified possible root causes.
    Type: Application
    Filed: December 15, 2017
    Publication date: June 20, 2019
    Inventors: Hao Chen, Ya Bin Dang, Qi Cheng Li, Shao Chun Li, Li Jun Mei, David Nahamoo, Jian Wang, Yi Peng Yu
  • Publication number: 20190164208
    Abstract: A computer receives a conversational input. The computer detects, based on the conversational input, relevant entities and relevant entity values, wherein the relevant entities and relevant entity values correspond to entities and entity values extracted from a catalog. The computer identifies, based on the relevant entities and relevant entity values, one or more matching products or services. The computer displays the one or more matching products or services. The computer assesses one or more attributes of the matching products or services for refinement. The computer provides one or more attribute refinement options based on the assessed one or more attributes. The computer receives user refinement in response to providing the one or more attribute refinement options. The computer receives a product or service selection.
    Type: Application
    Filed: November 29, 2017
    Publication date: May 30, 2019
    Inventors: Pankaj Dhoolia, Harshit Kumar, Sachindra Joshi, David Nahamoo
  • Publication number: 20190147853
    Abstract: A method, program product and computer system to predict utterances in a dialog system includes receiving a set of utterances associated with a dialog between a client device and a dialog system, mapping the utterances to vector representations of the utterances, and identifying at least one cluster to which the utterances belong from among a plurality of possible clusters. A next cluster is predicted based upon a conditional probability of the next cluster following a set of a predetermined number of previous clusters using a language model. A next utterance is predicted from among a plurality of possible utterances within the predicted next cluster.
    Type: Application
    Filed: March 8, 2018
    Publication date: May 16, 2019
    Applicant: International Business Machines Corporation
    Inventors: Chulaka Gunasekara, David Nahamoo, Lazaros Polymenakos, Kshitij Fadnis, David Echeverria Ciaurri, Jatin Ganhotra
  • Patent number: 10176025
    Abstract: Generating recommendations for an individual based on a mood of the individual. Receiving information corresponding to one or more activities associated with an individual over a period of time. The received information corresponding to the one or more activities associated with the individual is processed to detect a mood of the individual. A recommendation is generated for the individual based on the detected mood of the individual and a future event associated with the individual. The future event has an occurrence at a later time instance.
    Type: Grant
    Filed: February 25, 2015
    Date of Patent: January 8, 2019
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORTION
    Inventors: Siddique M. Adoni, David Nahamoo, Pamela A. Nesbitt, Dhandapani Shanmugam
  • Publication number: 20180357216
    Abstract: A system and method performs automated domain concept discovery and clustering using word embeddings by receiving a set of documents for natural language processing for a domain, representing a plurality of entries in the set of documents as continuous vectors in a high dimensional continuous space, applying a clustering algorithm based on a mutual information optimization criterion to form a set of clusters, associating each entry of the plurality of entries with each cluster in the set of clusters through formalizing an evidence based model of each cluster given each entry, calculating a mutual information metric between each entry and each cluster using the evidence based model, and identifying a nominal center of each cluster by maximizing the mutual information.
    Type: Application
    Filed: December 14, 2017
    Publication date: December 13, 2018
    Inventors: Raimo BAKIS, David NAHAMOO, Lazaros C. POLYMENAKOS, Cheng WU, John ZAKOS
  • Publication number: 20180341870
    Abstract: An approach is provided in which a system provides a question and a set of options to a user. The question corresponds to a first node in a decision tree and at least a portion of the options correspond to nodes that are directly connected to the first node. The system determines that the user's response corresponds to a second node that is different than one of the directly connected nodes and, in turn, displays a second question to the user corresponding to the second node.
    Type: Application
    Filed: May 23, 2017
    Publication date: November 29, 2018
    Inventors: Sachindra Joshi, Harshit Kumar, David Nahamoo
  • Publication number: 20180226067
    Abstract: Provided herein is a system, method, and computer program product for modifying a language conversation model of the language learning system. Modifying the language conversation model includes receiving, using a conversational sub-system, voice inputs. The conversational sub-system converts the voice inputs to voice input data and processes the voice input data. The conversational sub-system detects an error in processing the voice input data and, based at least in part on the error, stores additional data comprising additional voice input data in a memory. The conversational sub-system applies machine learning to the additional data to derive a function that is not enabled within the language conversation model. The conversational sub-system develops an update that enables the language conversation model to implement the function. The update is applied to the language conversation model.
    Type: Application
    Filed: February 8, 2017
    Publication date: August 9, 2018
    Inventors: Pankaj Dhoolia, Sachindra Joshi, David Nahamoo, Dinesh Raghu
  • Publication number: 20180091457
    Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to train an enhanced chatflow system, the method comprising: ingesting a corpus of information comprising at least one user input node corresponding to a user question and at least one variation for each user input node; for each user input node: designating the node as a class; storing the node in a dialog node repository; designating each of the at least one variations as training examples for the designated class; converting the classes and the training examples into feature vector representations; training one or more training classifiers using the one or more feature vector representations of the classes; and training classification objectives using the one or more feature vector representations of the training examples.
    Type: Application
    Filed: September 28, 2016
    Publication date: March 29, 2018
    Inventors: Raimo Bakis, Ladislav Kunc, David Nahamoo, Lazaros Polymenakos, John Zakos
  • Publication number: 20180089584
    Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to train an enhanced chatflow system, the method comprising: ingesting, using a rule-based module, a corpus of information comprising at least one user input node corresponding to a user question and at least one expert-designed variation for each user input node; matching, using the rule-based module, one or more user inputs to one or more corresponding dialog nodes using regular expressions and delimiters; ingesting, using a statistical matching module, one or more usage logs from a deployed dialog system, each usage log comprising at least one user input node; for each user input node: designating the node as a class; storing the node in a dialog node repository; designating each of the at least one variations as training examples for the designated class; converting the classes and the training examples into fe
    Type: Application
    Filed: September 28, 2016
    Publication date: March 29, 2018
    Inventors: Raimo Bakis, Ladislav Kunc, David Nahamoo, Lazaros Polymenakos, John Zakos
  • Publication number: 20180062931
    Abstract: A method for simplifying user interactions with decision tree dialog managers is provided. The method may include receiving from a client computer, by a server computer, a user input. The server computer may identify one or more candidate nodes of a decision tree corresponding to the received user input. An entropy value may be calculated by the server computer for each of the identified candidate nodes. The server computer may then select a current node from among the candidate nodes, whereby the selected current node has a lowest calculated entropy value. A prompt associated with the selected current node may be transmitted to the user by the server computer.
    Type: Application
    Filed: August 24, 2016
    Publication date: March 1, 2018
    Inventors: Sachindra Joshi, Harshit Kumar, David Nahamoo
  • Patent number: 9837080
    Abstract: Systems and methods for maintaining speaker recognition performance are provided. A method for maintaining speaker recognition performance, comprises training a plurality of models respectively corresponding to speaker recognition scores from a plurality of speakers over a plurality of sessions, and using the plurality of models to conclude whether a speaker seeking access to an environment is a non-ideal target speaker or a non-ideal non-target speaker. Using the plurality of models to conclude comprises calculating a first probability that the speaker seeking access is the non-ideal target speaker, calculating a second probability that the speaker seeking access is the non-ideal non-target speaker, and determining whether the first probability, the second probability or a sum of the first probability and the second probability is above a probability threshold.
    Type: Grant
    Filed: August 21, 2014
    Date of Patent: December 5, 2017
    Assignee: International Business Machines Corporation
    Inventors: Hagai Aronowitz, Shay Ben-David, David Nahamoo, Jason W. Pelecanos, Orith Toledo-Ronen
  • Patent number: 9646001
    Abstract: Operation of an automated dialog system is described using a source language to conduct a real time human machine dialog process with a human user using a target language. A user query in the target language is received and automatically machine translated into the source language. An automated reply of the dialog process is then delivered to the user in the target language. If the dialog process reaches an initial assistance state, a first human agent using the source language is provided to interact in real time with the user in the target language by machine translation to continue the dialog process. Then if the dialog process reaches a further assistance state, a second human agent using the target language is provided to interact in real time with the user in the target language to continue the dialog process.
    Type: Grant
    Filed: September 19, 2011
    Date of Patent: May 9, 2017
    Assignee: Nuance Communications, Inc.
    Inventors: Ruhi Sarikaya, Vaibhava Goel, David Nahamoo, Rèal Tremblay, Bhuvana Ramabhadran, Osamuyimen Stewart
  • Patent number: 9640186
    Abstract: Deep scattering spectral features are extracted from an acoustic input signal to generate a deep scattering spectral feature representation of the acoustic input signal. The deep scattering spectral feature representation is input to a speech recognition engine. The acoustic input signal is decoded based on at least a portion of the deep scattering spectral feature representation input to a speech recognition engine.
    Type: Grant
    Filed: May 2, 2014
    Date of Patent: May 2, 2017
    Assignee: International Business Machines Corporation
    Inventors: Petr Fousek, Vaibhava Goel, Brian E. D. Kingsbury, Etienne Marcheret, Shay Maymon, David Nahamoo, Vijayaditya Peddinti, Bhuvana Ramabhadran, Tara N. Sainath
  • Publication number: 20170004231
    Abstract: Methods and systems for model discovery include forming a mathematical program based on a set of observational data to generate an objective function and one or more constraints. The mathematical program represents a model space as an expression tree comprising operators and operands. The mathematical program is solved by optimizing the objective function subject to the one or more constraints to determine a model in the model space that best fits the set of observational data.
    Type: Application
    Filed: June 30, 2015
    Publication date: January 5, 2017
    Inventors: Haim Avron, Lior Horesh, Leo S. Liberti, David Nahamoo