Abstract In this talk, we present issues in natural language modeling for text entry in languages that use noisy (i.e., non-standard) romanization strategies, with a particular focus on languages using Indic scripts. We discuss romanization[…]
Abstract The past few years have seen a dramatic increase in the performance of recognition systems thanks to the introduction of deep networks for representation learning. However, the mathematical reasons for this success remain elusive. A[…]
Abstract Automatic speech recognition has greatly progressed in recent years and is being used more and more in challenging conditions. However, the performance of current systems degrades when several people speak at the same time[…]
Abstract AI is moving both faster and slower than the general public realizes — it is being deployed extensively across many domains, but we are also still very, very far away from the sorts of (semi)autonomous[…]
All lectures will be held in Hackerman Hall, room B17. All labs will be held in Malone 122. The morning lectures are open to the public. We request that you inform us at least one[…]
This is the fifth in a series of six-week-long research workshops on Machine Learning for Speech Language and Computer Vision Technology. These workshops bring together diverse “dream teams” of leading professionals, graduate students, and undergraduates,[…]
Abstract Language use varies depending on context, which is reflected in a variety of factors, including topic, location, communication mode, social context or objective, and individual style. Differences are often so great that text from[…]
