Robust information extraction from utterances

摘要

The performance of traditional speech recognition systems (as applied to information extraction or translation) decreases significantly with, larger domain size, scarce training data as well as under noisy environmental conditions. This invention mitigates these problems through the introduction of a novel predictive feature extraction method which combines linguistic and statistical information for representation of information embedded in a noisy source language. The predictive features are combined with text classifiers to map the noisy text to one of the semantically or functionally similar groups. The features used by the classifier can be syntactic, semantic, and statistical.

主权项

1. A classification system comprising:
a non-transitory storage medium; a classification engine comprising a set of executable instructions stored on the non-transitory storage medium and configured to:
receive an input associated with semantic information;generate an action-based concept tagged document of the input;classify the input into one or more semantic classes based at least in part on the action-based concept tagged document;predict paraphrased representations of the input with respect to a source language based on the one or more semantic classes; and generate a system response based on the paraphrased representations.