36,610 research outputs found
Retrieval-based Goal-Oriented Dialogue Generation
Most research on dialogue has focused either on dialogue generation for
openended chit chat or on state tracking for goal-directed dialogue. In this
work, we explore a hybrid approach to goal-oriented dialogue generation that
combines retrieval from past history with a hierarchical, neural
encoder-decoder architecture. We evaluate this approach in the customer support
domain using the Multiwoz dataset (Budzianowski et al., 2018). We show that
adding this retrieval step to a hierarchical, neural encoder-decoder
architecture leads to significant improvements, including responses that are
rated more appropriate and fluent by human evaluators. Finally, we compare our
retrieval-based model to various semantically conditioned models explicitly
using past dialog act information, and find that our proposed model is
competitive with the current state of the art (Chen et al., 2019), while not
requiring explicit labels about past machine acts
Lilia, A Showcase for Fast Bootstrap of Conversation-Like Dialogues Based on a Goal-Oriented System
International audienceRecently many works have proposed to cast human-machine interaction in a sentence generation scheme. Neural networks models can learn how to generate a probable sentence based on the user's statement along with a partial view of the dialogue history. While appealing to some extent, these approaches require huge training sets of general-purpose data and lack a principled way to intertwine language generation with information retrieval from back-end resources to fuel the dialogue with actualised and precise knowledge. As a practical alternative, in this paper, we present Lilia, a showcase for fast bootstrap of conversation-like dialogues based on a goal-oriented system. First, a comparison of goal-oriented and conversational system features is led, then a conversion process is described for the fast bootstrap of a new system, finalised with an on-line training of the system's main components. Lilia is dedicated to a chitchat task, where speakers exchange viewpoints on a displayed image while trying collaboratively to derive its author's intention. Evaluations with user trials showed its efficiency in a realistic setup
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