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The communication between user and computer is more and more shifting towards voice interfaces. Voice interfaces are the most natural form of communication to most users. They can be used in a variety of situations (e.g., while driving), even from a distance. The Cornell Database Group is working on leveraging voice query interfaces for manipulating and analyzing structured data.

Our research focuses on three challenges. First, resolving ambiguities in voice input, due to noisy speech recognition. Second, extracting high-level trends from query results, suitable for concise output. Third, reducing computational overheads by exploiting particularities of voice interfaces (e.g., by overlapping computation with voice output). Our most recent paper (talk video below) uses pre-processing to summarize query results with minimal overheads.




We thankfully acknowledge funding by the following organizations: