1 citations · 1 across the 4 of their papers we have counts for
4 papers
Locale-agnostic Universal Domain Classification Model in Spoken Language Understanding
Jihwan Lee, Ruhi Sarikaya, Young-Bum Kim
In this paper, we introduce an approach for leveraging available data across multiple locales sharing the same language to 1) improve domain classification model accuracy in Spoken…
Continuous Learning for Large-scale Personalized Domain Classification
Han Li, Jihwan Lee, Sidharth Mudgal +2
Domain classification is the task of mapping spoken language utterances to one of the natural language understanding domains in intelligent personal digital assistants (IPDAs). Thi…
OneNet: Joint Domain, Intent, Slot Prediction for Spoken Language Understanding
Young-Bum Kim, Sungjin Lee, Karl Stratos
In practice, most spoken language understanding systems process user input in a pipelined manner; first domain is predicted, then intent and semantic slots are inferred according t…
Speaker-Sensitive Dual Memory Networks for Multi-Turn Slot Tagging
Young-Bum Kim, Sungjin Lee, Ruhi Sarikaya
In multi-turn dialogs, natural language understanding models can introduce obvious errors by being blind to contextual information. To incorporate dialog history, we present a neur…