156 citations
- Amazon (United States)US12 papers
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- National Yang Ming Chiao Tung UniversityTW3 papers
23 papers · 2 filters
CASE: Context-Aware Semantic Expansion
Jialong Han, Aixin Sun, Haisong Zhang +2
In this paper, we define and study a new task called Context-Aware Semantic Expansion (CASE). Given a seed term in a sentential context, we aim to suggest other terms that well fit…
Controlling Neural Machine Translation Formality with Synthetic Supervision
Xing Niu, Marine Carpuat
This work aims to produce translations that convey source language content at a formality level that is appropriate for a particular audience. Framing this problem as a neural sequ…
MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension
Di Jin, Shuyang Gao, Jiun-Yu Kao +2
Machine Reading Comprehension (MRC) for question answering (QA), which aims to answer a question given the relevant context passages, is an important way to test the ability of int…
Towards Personalized Dialog Policies for Conversational Skill Discovery
Maryam Fazel-Zarandi, Sampat Biswas, Ryan Summers +4
Many businesses and consumers are extending the capabilities of voice-based services such as Amazon Alexa, Google Home, Microsoft Cortana, and Apple Siri to create custom voice exp…
Bootstrapping NLU Models with Multi-task Learning
Shubham Kapoor, Caglar Tirkaz
Bootstrapping natural language understanding (NLU) systems with minimal training data is a fundamental challenge of extending digital assistants like Alexa and Siri to a new langua…
Investigation of Error Simulation Techniques for Learning Dialog Policies for Conversational Error Recovery
Maryam Fazel-Zarandi, Longshaokan Wang, Aditya Tiwari +1
Training dialog policies for speech-based virtual assistants requires a plethora of conversational data. The data collection phase is often expensive and time consuming due to huma…