SYSTEM AND METHOD FOR AUGMENTING TRAINING DATA FOR NATURAL LANGUAGE TO MEANING REPRESENTATION LANGUAGE SYSTEMS

Abstract: techniques for augmenting training data include accessing training data comprising a plurality of training examples comprising a first training example comprising a first natural language utterance and a first logical form for the first natural language utterance. a second natural language utterance is generated by adding or replacing one or more values in the first natural language utterance. a logical form for the second natural language utterance is generated. a second training example is generated, comprising the second natural language utterance and the logical form for the second natural language utterance. the training data is augmented by adding the second training example to the plurality of training examples to generate an augmented training data set. a machine learning model is trained to generate logical forms for utterances using the augmented training data set.

Inventor(s): Philip Arthur, Gioacchino Tangari, Nitika Mathur, Aashna Devang Kanuga, Cong Duy Vu Hoang, Poorya Zaremoodi, Thanh Long Duong, Mark Edward Johnson

CPC Classification: G06F40/40 (ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models ))

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