Imagine a picture puzzle that is inside-out. The edges of the puzzle start in a small square with an empty space in the middle. The smooth edges face in to the center. As pieces are added to the puzzle, the area gets larger, but there is no finish to it. Each row that is added around the outside has larger total area than the previous row.
This is how I see computational lingusitics. We are learning some of the basics of language and how computers can interact with humans using it. But we are still at the middle of the picture.
There is lots of research occuring in areas that are developing the pieces:
- Voice recognition and generation.
- Word semantics – finding relationships between words.
- Document extraction and summarization.
- Question Answering.
- Information retrieval.
- Analysis of syntax, discourse.
Much of this research is providing some amount of useful result. There are real world applications that are being created based on these results that are helping users get their job done.
But we have not yet arrived at the part of the puzzle solving process where large sections fall together and a whirlwind of activity suddenly explodes out of the pieces. We have not yet achieved the level of mastery where suddenly ‘aha’ occurs and we see how syntax, semantics and a theory of meaning form the basis for a system that learns meaning from the words it encounters without being supervised.
Eventually we will get computers to the point of the Enterprise mainframe.
- We will be able to interact with the computer by voice with ambiguity of context, sentence structure, and word sense.
- The computer will acknowledge our individuality and adjust its responses to match.
- The computer will have access to a large body of knowledge to use for responses to questions.
- Answers to questions will be generated in context from the deep structure of the underlying knowledge. Answers will be generated in the language of the questioner even though the knowledge may have been extracted from a source in a different language.
- When you ask a question, the computer will answer with a single result. You won’t need to sift through 198,235 pages to find what you are looking for.
We are not there yet. 
In the mean time, the small advances being made toward that vision with today’s real world applications are the places where we are learning. Each researcher that attempts to solve the puzzle in a different way adds to our total understanding. It is the incremental steps that eventually get us to the larger results.
