Speech based learning/training system using semantic decoding
DCFirst Claim
1. A method of populating a natural language speech lattice with semantically variant questions, the method comprising the steps of:
- (a) providing a target set of questions associated with a content of a task domain that is to be supported by the natural language speech lattice;
(a)′
receiving a first user question from said target set of questions;
(b) dividing the user question into a plurality of words corresponding to the user question;
(c) determining synonyms for selected words in said plurality of words;
(d) formulating a synonym set of questions related to said user question based on said synonyms;
(e) performing semantic decoding on said synonym set of questions, to identify a disambiguated set of questions;
(f) storing said set of disambiguated questions in a speech recognition lattice;
wherein said set of disambiguated questions correspond to semantic variants of said target set of questions that can be recognized by a natural language speech engine used for the task domain.
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Abstract
An intelligent query system for processing voiced-based queries is disclosed, which uses a combination of both statistical and semantic based processing to identify the question posed by the user by understanding the meaning of the user'"'"'s utterance. Based on identifying the meaning of the utterance, the system selects a single answer that best matches the user'"'"'s query. The answer that is paired to this single question is then retrieved and presented to the user. The system, as implemented, accepts environmental variables selected by the user and is scalable to provide answers to a variety and quantity of user-initiated queries.
662 Citations
12 Claims
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1. A method of populating a natural language speech lattice with semantically variant questions, the method comprising the steps of:
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(a) providing a target set of questions associated with a content of a task domain that is to be supported by the natural language speech lattice; (a)′
receiving a first user question from said target set of questions;(b) dividing the user question into a plurality of words corresponding to the user question; (c) determining synonyms for selected words in said plurality of words; (d) formulating a synonym set of questions related to said user question based on said synonyms; (e) performing semantic decoding on said synonym set of questions, to identify a disambiguated set of questions; (f) storing said set of disambiguated questions in a speech recognition lattice; wherein said set of disambiguated questions correspond to semantic variants of said target set of questions that can be recognized by a natural language speech engine used for the task domain. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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Specification