One could argue that Human Machine Conversation (HMC) is now in a position like that of machine translation fifteen years ago: it is a real technology, coming into being in spite of scepticism, but with a huge gulf between busy practitioners getting on with the job, often within companies, and, on the other side, the researchers, in linguistics, artificial intelligence (AI) or whatever, whose papers fill the conferences. The rise of empirical linguistics has largely closed this gulf for machine translation and related arts, but not as yet, for HMC. First, let us set out historical trends in HMC, for if the HMC world is really as disparate as what follows it is hardly surprising there is so little consensus on how to progress.
The themes and approaches in this list are probably not wholly independent and may not be exhaustive. Notice that, thirty years after PARRY, no real form of (9) exists, and the corpora from which it might be done (for English at least) have only very recently come into existence. An interesting question right now, is whether (9) can be done in a principled way, as an alternative to PARRY-like systems built up over long periods by hand, or many of the other types of systems above with trivial vocabularies and virtually no functionality. This was exactly the opposition in machine translation for many years: with SYSTRAN's large hand-crafted functionality contrasted with a host of theoretical, published, acclaimed but non-functional systems. In Machine Translation, that opposition began to collapse with the arrival of IBM's statistical MT system about 1990. The possibility of a meaningful empirical pragmatics could do the same for HMC.
One additional point should be made here: we have said nothing of computer recognition (and production) of speech in dialogue systems. Speech research has pursued its own agenda, separate from written text, and all the above systems communicated via screen typing. The chief speech problem was always decoding the signals into words, rather than the content of dialogue as we have described it above-researchers tended to assume that speech could be solved separately and then a dialogue model of one of the following types just bolted on, as it were. This agenda for research has had obvious defects, especially in that speech phenomena like pauses, stress, pitch etc. convey meaning as well-but basically there has been agreement on all sides until now to separate out the speech and language issues so as to progress.