Multitask Learning for Spoken Language Understanding

摘要

Systems for improving or generating a spoken language understanding system using a multitask learning method for intent or call-type classification. The multitask learning method aims at training tasks in parallel while using a shared representation. A computing device automatically re-uses the existing labeled data from various applications, which are similar but may have different call-types, intents or intent distributions to improve the performance. An automated intent mapping algorithm operates across applications. In one aspect, active learning is employed to selectively sample the data to be re-used.

主权项

1. A method comprising:
mapping call-types between a first spoken dialog system and a second spoken dialog system using individual training models for each spoken dialog system, to yield mapped call-types; and retraining a model of the individual models using information based on the mapped call-types.