Uhura is an autonomous system that collaborates with humans in planning and executing complex tasks, especially under over-subscribed and risky situations.
Autonomous agents that use natural language to understand and adapt to a new environment.
Developing state-of-the-art tools that process 3D surfaces and volumes
Building models that learn spoken language by seeing and hearing
Adding domain knowledge to word embeddings.
Our goal is to develop new tools for modeling diverse multi-agent settings, and design estimation algorithms to unravel the strategic interactions among the agents.
We aim to create a virtual environment where agents learn to perform human tasks by executing programs. Furthermore, we aim to develop models that can generate such programs from video or text, enabling agents to understand and imitate such activities.
All humans process vast quantities of unannotated speech and manage to learn phonetic inventories, word boundaries, etc., and can use these abilities to acquire new word. Why can't ASR technology have similar capabilities? Our goal in this research project is to build speech technology using unannotated speech corpora.
This project aims to build models grounded in perception that tackle classical planning problems in AI in a new realm.
Our goal is to develop a socially intelligent team coacher agent that helps humans communicate, strategize, and work together efficiently.