Download Building Applied Natural Language Generation System Final Project

Building Applied Natural Language Generation System
Final Project Proposal Supervisors: Dr. Elena Ravve E-mail: [email protected]
Background:
Natural language generation (nlg) is the subfield of artificial intelligence and
computational linguistics that is concerned with the construction of computer systems
that can produce understandable texts in English or other human languages from some
underlying non-linguistic representation of information. Natural language generation
systems combine knowledge about language and the application domain to
automatically produce documents, reports, explanations, help messages, and other
kinds of texts.
Goals of the project:
In this project, we are going to look at nlg from an applied system-building
perspective. We will describe the tasks that must be performed by a language
generation system, and will discuss possible algorithms and supporting
representations for performing each task.
We also hope to suggest techniques, often based on corpus analysis, which can be
used to acquire the various kinds of knowledge needed in order to build such nlg
systems.
Unique features:
* We plan to discuss when nlg technology is likely to be appropriate, and when
alternative or simpler techniques may provide a more appropriate solution.
* Throughout, our focus is on the use of well-established techniques that can be used
to build simple but practical working systems today.
* We will also provide pointers to ideas in the research literature that are likely to be
relevant to the development of more sophisticated nlg systems in the future.
* Our intention is that the overview, which we find here, should be useful both for
software developers who are considering using nlg techniques in their systems, and
for researchers interested in developing applied nlg technology.