Below are some of the astounding faculty and graduate students of the SCS Language Technologies Institute!
Speech Recognition, Natural Language Processing
"I make machines understand human speech, and the world of sounds around them in general." - Professor Rita Singh
It remains unclear to scientists just how the speech signal carries information that is interpreted so effectively by the human brain. Current machine learning techniques for speech make up for this lack of understanding by analyzing large volumes of data and learning surface-level structure from them. Today's best automated speech recognition systems are trained on much more speech than most humans will hear in their lifetime. Yet their performance remains much worse than that of humans. For the most part, Professor's Singh research tries to reduce this gap by building on a better understanding of the speech signal itself.
Computer Supported Cooperative Learning, Education, Machine Learning
Carolyn Penstein Rose is an Assistant Professor with a joint appointment between the Language Technologies Institute and the Human-Computer Interaction Institute. In that role, she leads several research projects in the area of Computer Supported Collaborative Learning and teaches courses in machine learning, discourse analysis, automatic summarization, computer supported collaborative learning, and research communication.
Machine Learning, Data Fusion, Computer Vision, Artificial Intelligence
Carla Viegas is a dual-degree PhD student in the CMU | Portugal Program. Currently, she is working on stress detection from faces, analyzing videos. She is also part of the project called BioVisualSpeech which aims to research natural and multimodal interaction mechanisms for providing bio-feedback in speech therapy through the use of serious (computer) games.