Abstract
Virtual Personal Assistants like Siri have great potential but such developments hit the fundamental problem of how to make computational devices that understand human speech. Natural language understanding is one of the more disappointing failures of AI research and it seems there is something we computer scientists don't get about the nature of language. Of course philosophers and linguists think quite differently about language and this paper describes how we have taken ideas from other disciplines and implemented them. The background to the work is to take seriously the notion of language as action and look at what people actually do with language using the techniques of Conversation Analysis. The observation has been that human communication is (behind the scenes) about the management of social relations as well as the (foregrounded) passing of information. To claim this is one thing but to implement it requires a mechanism. The mechanism described here is based on the notion of language being intentional - we think intentionally, talk about them and recognise them in others - and cooperative in that we are compelled to help out. The way we are compelled points to a solution to the ever present problem of keeping the human on topic. The approach has led to a recent success in which we significantly improve user satisfaction independent of task completion. Talk Markup Language (TalkML) is a draft alternative to VoiceXML that, we propose, greatly simplifies the scripting of interaction by providing default behaviours for no input and not recognised speech events.
Abstract (translated)
URL
https://arxiv.org/abs/2105.11294
