对话系统-“任务型”多轮对话（二）：对话状态追踪（DST）【基于规则；基于模型】【输入：当前意图和槽值对+历史槽值对；输出：State（槽值对集合）或State Vector 】【为DP做数据准备】_基于规则的对话状态跟踪

在任务型的对话系统中，对话状态跟踪（DST）的目标是从对话历史中监控对话的状态。

DST的输入：Intent+Slot+History；输出：State或State Vector

DST中的State用一组Slot-Value键值对表示；

一、基于规则的DST

二、基于模型的DST

At a high level, given a dialog context and a candidate slot- value pair, our model outputs a score indicating the relevance of the candidate.

In other words, the approach is similar to a sentence pair classification task.

• The first input corresponds to the dialog context, and it consists of the system utterance from the previous turn and the user utterance from the cur- rent turn. The two utterances are separated by a [SEP] token.
• The second input is the candidate slot-value pair. We simply represent the candidate pair as a sequence of tokens (words or pieces of words).

At each turn, the proposed BERT-based model is used to estimate the probability score of every candidate slot-value pair.After that, only pairs with predicted probability equal to at least 0.5 are chosen as the final prediction for the turn.