Research Groups An Exploration of How to Learn from Visually Descriptive Text Confusion-based Statistical Language Modeling for Machine Translation and Speech Recognition New Parameterization for Emotional Speech Synthesis
Abstract There is growing interest in the automatic extraction of opinions, emotions, and sentiments in text (subjectivity), to provide tools and support for various natural language processing applications. Most of the research to date has[…]
Abstract Computer systems that can directly and accurately answer peoples’ questions over a broad domain of human knowledge have been envisioned by scientists and writers since the advent of computers themselves. Open domain question answering[…]
Abstract Building on earlier work that integrates different factors in language modeling, we view (i) backing off to a shorter history and (ii) class-based generalization as two complementary mechanisms of using a larger equivalence class[…]
Abstract In this talk, I will present an interactive interface that helps users to explore and understand imperfect outputs from automatic machine translation (MT) systems. The target users of our system are people who do[…]
View Seminar Video Abstract To build computer systems that can ‘understand’ natural language, we need to go beyond bag-of-words models and take the grammatical structure of language into account. Part-of-speech tag sequences and dependency parse[…]
View Seminar Video Abstract What is in common between translating from English into Chinese and compiling C++ into machine code? And yet what are the differences that make the former so much harder for computers?[…]
