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.
翻译:类似Siri的虚拟个人助理具有巨大的潜力,但这样的发展却触及了如何使计算设备能够理解人类语言这一根本问题。自然语言理解是AI研究中更令人失望的失败之一,而且似乎我们计算机科学家对语言的性质并不理解某种东西。当然,哲学家和语言学家对语言的看法是完全不同的,本文描述了我们如何从其他学科中汲取思想并加以实施。工作的背景是认真对待语言的概念,将语言概念视为行动,并审视人们使用对话分析技术使用语言的实际做法。我们发现,人类交流是(在幕后)管理社会关系以及(地下)传递信息的一种更令人失望的失败。我们称这是一件事,但实施它需要一种机制。这里描述的机制是基于语言概念,我们有意地思考,谈论它们,在其它学科中承认它们--我们不得不提供帮助。我们不得不指出一个解决当前问题的方法,即保持人类议题的解决方案。这一方法导致最近的一个成功之处是,我们没有在语言MLA上大大改进了用户对它的一种理解,我们通过语言的版本,我们提出一个理解的版本,让我们能够大大改进MLL的版本。