  Traditional approaches to building natural language (NL) interfaces typically
use a semantic parser to parse the user command and convert it to a logical
form, which is then translated to an executable action in an application.
However, it is still challenging for a semantic parser to correctly parse
natural language. For a different domain, the parser may need to be retrained
or tuned, and a new translator also needs to be written to convert the logical
forms to executable actions. In this work, we propose a novel and application
independent approach to building NL interfaces that does not need a semantic
parser or a translator. It is based on natural language to natural language
matching and learning, where the representation of each action and each user
command are both in natural language. To perform a user intended action, the
system only needs to match the user command with the correct action
representation, and then execute the corresponding action. The system also
interactively learns new (paraphrased) commands for actions to expand the
action representations over time. Our experimental results show the
effectiveness of the proposed approach.
