Consumer speech recognition systems do not work as well for many people with speech
differences, such as stuttering, relative to the rest of the general population. However, what …

Operating a complex and dynamic system, such as an agile manufacturing line, is a
knowledge-intensive task. It imposes a steep learning curve on novice operators and …

Robustness of machine learning models on ever-changing real-world data is critical,
especially for applications affecting human well-being such as content moderation. New …

Dysfluencies and variations in speech pronunciation can severely degrade speech
recognition performance, and for many individuals with moderate-to-severe speech …

Collecting training data for semantic parsing is a time-consuming and expensive task. As a
result, there is growing interest in industry to reduce the number of annotations required to …

Natural language understanding (NLU) aims at identifying user intent and extracting
semantic slots. This requires sufficient annotating data to get considerable performance in …

Named Entity Recognition (NER) and Entity Linking (EL) play an essential role in voice
assistant interaction, but are challenging due to the special difficulties associated with …

Many industries are facing the challenge of how to capture workers' knowledge such that it
can be shared, in particular tacit knowledge. The operation of complex systems such as a …

Abstract Models developed for Machine Reading Comprehension (MRC) are asked to
predict an answer from a question and its related context. However, there exist cases that …

Improving the quality of Natural Language Understanding (NLU) models, and more
specifically, task-oriented semantic parsing models, in production is a cumbersome task. In …