Meta-control of Dialogue Systems Using Large Language Models
CoRR(2023)
摘要
Utilizing Large Language Models (LLMs) facilitates the creation of flexible
and natural dialogues, a task that has been challenging with traditional
rule-based dialogue systems. However, LLMs also have the potential to produce
unexpected responses, which may not align with the intentions of dialogue
system designers. To address this issue, this paper introduces a meta-control
method that employs LLMs to develop more stable and adaptable dialogue systems.
The method includes dialogue flow control to ensure that utterances conform to
predefined scenarios and turn-taking control to foster natural dialogues.
Furthermore, we have implemented a dialogue system that utilizes this
meta-control strategy and verified that the dialogue system utilizing
meta-control operates as intended.
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