Abstract While deep learning produces supervised models with unprecedented predictive performance on many tasks, under typical training procedures, advantages over classical methods emerge only with large datasets. The extreme data-dependence of reinforcement learners may be even more[…]

Read More

Abstract A recurring task at the intersection of humanities and computational research is pairing data collected by a traditional scholar with an appropriate machine learning technique, ideally in a form that creates minimal burden on[…]

Read More

Abstract Code-switching is a commonly occurring phenomenon in many multilingual communities, wherein a speaker switches between languages within a single utterance. Conventional Word Error Rate (WER) is not sufficient for measuring the performance of code-mixed[…]

Read More

Abstract Even conversational systems have attracted a lot of attention recently, the current systems sometimes fail due to the errors from different components. This talk presents our recent research: 1) we focus on analyzing the[…]

Read More

Abstract Language is not only about the words, it is also about the people. While much of the work in computational linguistics has focused almost exclusively on words (and their relations), recent research in the[…]

Read More

Abstract Traditional semantic representation frameworks generally define complex, often exclusive category systems that require highly trained annotators to build. And in spite of their high quality for the cases they are designed to handle, these[…]

Read More

Abstract: The increased availability of high resolution cameras and array microphones in live meetings, video production, and camera enabled assistant devices has created opportunities for exploiting multiple modalities in speech applications.  This presentation summarizes initial[…]

Read More