SalesBot 2.0: A Human-Like Intent-Guided Chit-Chat Dataset
- URL: http://arxiv.org/abs/2308.14266v1
- Date: Mon, 28 Aug 2023 02:48:49 GMT
- Title: SalesBot 2.0: A Human-Like Intent-Guided Chit-Chat Dataset
- Authors: Wen-Yu Chang, Yun-Nung Chen
- Abstract summary: This paper aims to build SalesBot 2.0, a revised version of the published data, by leveraging the commonsense knowledge of large language models (LLMs) through proper prompting.
The newly released large-scale dataset with detailed annotations exhibits smoother transitions between topics and is more human-like in terms of naturalness and consistency.
- Score: 28.257630375747606
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: In recent research on dialogue systems and corpora, there has been a
significant focus on two distinct categories: task-oriented (TOD) and
open-domain (chit-chat) dialogues. TOD systems aim to satisfy specific user
goals, such as finding a movie to watch, whereas open-domain systems primarily
focus on generating engaging conversations. A recent study by Chiu et al.
(2022) introduced SalesBot, which provides simulators and a dataset with
one-turn transition from chit-chat to task-oriented dialogues. However, the
previously generated data solely relied on BlenderBot, which raised concerns
about its long-turn naturalness and consistency during a conversation. To
address this issue, this paper aims to build SalesBot 2.0, a revised version of
the published data, by leveraging the commonsense knowledge of large language
models (LLMs) through proper prompting. The objective is to gradually bridge
the gap between chit-chat and TOD towards better naturalness and consistency.
The newly released large-scale dataset with detailed annotations exhibits
smoother transitions between topics and is more human-like in terms of
naturalness and consistency. It can serve as a valuable resource for both
academic research and commercial applications. Furthermore, our proposed
framework can be applied to generate numerous dialogues with various target
intents.
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