jurafsky&martin_3rdEd_17 (1).pdf

287 design a simple dialogue system for checking your

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28.7 Design a simple dialogue system for checking your email over the telephone. Implement in VoiceXML. 28.8 Test your email-reading system on some potential users. Choose some of the metrics described in Section 28.4 and evaluate your system.
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CHAPTER 29 Advanced Dialog Systems A famous burlesque routine from the turn of the last century plays on the difficulty of conversational understanding by inventing a baseball team whose members have confusing names: C: I want you to tell me the names of the fellows on the St. Louis team. A: I’m telling you. Who’s on first, What’s on second, I Don’t Know is on third. C: You know the fellows’ names? A: Yes. C: Well, then, who’s playing first? A: Yes. C: I mean the fellow’s name on first. A: Who. C: The guy on first base. A: Who is on first. C: Well what are you askin’ me for? A: I’m not asking you – I’m telling you. Who is on first. Who’s on First Bud Abbott and Lou Costello’s version of an old burlesque standard. Of course outrageous names of baseball players are not a normal source of dif- ficulty in conversation. What this famous comic conversation is pointing out is that understanding and participating in dialog requires knowing whether the person you are talking to is making a statement or asking a question. Asking questions, giving orders, or making informational statements are things that people do in conversa- tion, yet dealing with these kind of actions in dialogue—what we will call dialog acts — is something that the GUS-style frame-based dialog systems of Chapter 29 are completely incapable of. In this chapter we describe the dialog-state architecture, also called the belief- state or information-state architecture. Like GUS systems, these agents fill slots, but they are also capable of understanding and generating such dialog acts , actions like asking a question, making a proposal, rejecting a suggestion, or acknowledging an utterance and they can incorporate this knowledge into a richer model of the state of the dialog at any point. Like the GUS systems, the dialog-state architecture is based on filling in the slots of frames, and so dialog-state systems have an NLU component to determine the specific slots and fillers expressed in a user’s sentence. Systems must additionally determine what dialog act the user was making, for example to track whether a user is asking a question. And the system must take into account the dialog context (what the system just said, and all the constraints the user has made in the past). Furthermore, the dialog-state architecture has a different way of deciding what to say next than the GUS systems. Simple frame-based systems often just continuously
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442 C HAPTER 29 A DVANCED D IALOG S YSTEMS ask questions corresponding to unfilled slots and then report back the results of some database query. But in natural dialogue users sometimes take the initiative, such as asking questions of the system; alternatively, the system may not understand what the user said, and may need to ask clarification questions. The system needs a
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