24 citations · 66 across the 16 of their papers we have counts for
7 papers · 1 filter
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration
Han Li, Sunghyun Park, Aswarth Dara +5
Current state-of-the-art large-scale conversational AI or intelligent digital assistant systems in industry comprises a set of components such as Automatic Speech Recognition (ASR)…
A scalable framework for learning from implicit user feedback to improve natural language understanding in large-scale conversational AI systems
Sunghyun Park, Han Li, Ameen Patel +5
Natural Language Understanding (NLU) is an established component within a conversational AI or digital assistant system, and it is responsible for producing semantic understanding…
Coupled Representation Learning for Domains, Intents and Slots in Spoken Language Understanding
JIhwan Lee, Dongchan Kim, Ruhi Sarikaya +1
Representation learning is an essential problem in a wide range of applications and it is important for performing downstream tasks successfully. In this paper, we propose a new mo…
Contextual Slot Carryover for Disparate Schemas
Chetan Naik, Arpit Gupta, Hancheng Ge +2
In the slot-filling paradigm, where a user can refer back to slots in the context during a conversation, the goal of the contextual understanding system is to resolve the referring…
Efficient Large-Scale Domain Classification with Personalized Attention
Young-Bum Kim, Dongchan Kim, Anjishnu Kumar +1
In this paper, we explore the task of mapping spoken language utterances to one of thousands of natural language understanding domains in intelligent personal digital assistants (I…
A Scalable Neural Shortlisting-Reranking Approach for Large-Scale Domain Classification in Natural Language Understanding
Young-Bum Kim, Dongchan Kim, Joo-Kyung Kim +1
Intelligent personal digital assistants (IPDAs), a popular real-life application with spoken language understanding capabilities, can cover potentially thousands of overlapping dom…
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…