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US 9,754,585 B2Granted
Crowdsourced, grounded language for intent modeling in conversational interfaces
AssigneeMicrosoft Technology Licensing, LLC
InventorsChristopher John Brockett, Piali Choudhury, William Brennan Dolan, Yun-Cheng Ju, Patrick Pantel, Noelle Mallory Sophy, Svitlana Volkova
Life of this patent
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Abstract
Different advantageous embodiments provide a crowdsourcing method for modeling user intent in conversational interfaces. One or more stimuli are presented to a plurality of describers. One or more sets of describer data are captured from the plurality of describers using a data collection mechanism. The one or more sets of describer data are processed to generate one or more models. Each of the one or more models is associated with a specific stimulus from the one or more stimuli.
Claims20
A system comprising:
- one or more processors;
- a model generation mechanism configured to:
- identify a first set of data;
- based on the identified first set of data, select a plurality of users;
- present the first set of data to the selected plurality of users;
- and
- process a second set of data captured from the selected plurality of users in response to the first set of data presented to the selected plurality of users to generate metadata documents that correspond to respective users of the selected plurality of users;
- a clarification mechanism configured to:
- process the metadata documents;
- based on the processing, identify ambiguities in the metadata documents, the ambiguities comprising relative terms or descriptive words having more than one meaning;
- generate a set of clarifying questions based on the identified ambiguities;
- and
- present the set of clarifying questions to the selected plurality of users;
- a data collection mechanism configured to capture clarifying data from the selected plurality of users in response to the presentation of the set of clarifying questions;
- the model generation mechanism further configured to:
- refine the metadata documents based on the clarifying data;
- and
- generate a model that provides natural language descriptions of the first set of data based on the refined metadata documents and the clarifying data;
- and
- a conversational interface configured to be trained using the model generated by the model generation mechanism to determine a meaning behind a verbal communication from a user.
17 more elements
An apparatus, comprising:
- a processor programmed to:
- identify a first set of data;
- based on the identified first set of data, select a plurality of users;
- and
- present the first set of data to the selected plurality of users;
- a data collection mechanism configured to capture a second set of data from the selected plurality of users in response to the first set of data presented to the selected plurality of users;
- a model generation mechanism configured to:
- process the second set of data;
- and
- generate a model that provides natural language descriptions of the first set of data, the generated model including a set of metadata documents associated with the first set of data;
- and
- a clarification mechanism configured to:
- process the metadata documents;
- and
- based on the processing, identify ambiguities in the set of metadata documents, the ambiguities comprising relative terms or descriptive words having more than one meaning;
- and
- generate a set of clarifying questions based on the identified ambiguities, wherein the set of clarifying questions are presented to the selected plurality of users, and wherein the data collection mechanism captures clarifying data from the selected plurality of users in response to the presentation of the set of clarifying questions;
- the model generation mechanism further configured to:
- refine the metadata documents based on the clarifying data;
- and
- refine the generated model based on the refined metadata documents and the clarifying data.
18 more elements
A method comprising:
- identify a first set of data;
- based on the identified first set of data, select a plurality of users;
- presenting the first set of data to the selected plurality of users for determining a meaning behind a verbal communication from a user in conversational interfaces, the first set of data comprising a stimuli and questions regarding the stimuli;
- capturing a second set of user data in response to the second set of data from the selected plurality of users using a data collection mechanism;
- processing, by a processor, the second set of data;
- based on processing the second set of data, generate metadata documents that correspond to respective users of the selected plurality of users;
- process the metadata documents;
- based on processing the metadata documents, identify ambiguities in the second set of data, the ambiguities comprising relative terms or descriptive words having more than one meaning;
- generate, by the processor, a set of clarifying questions based on the identified ambiguities;
- present the set of clarifying questions to the selected plurality of users;
- capture clarifying data from the selected plurality of users in response to the presentation of the set of clarifying questions;
- refine the metadata documents based on the clarifying data;
- and
- generate, by the processor, one or more models that provide natural language descriptions of the first set of data based on the refined metadata documents and the clarifying data.
11 more elements
Dependencies are inferred from the claim text.