Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue
Jian Wang, Dongding Lin, Wenjie Li · 2023
Goal-directed dialogue systems aim to proactively reach a pre-determined target through multi-turn conversations.The key to achieving this task lies in planning dialogue paths that smoothly and coherently direct conversations towards the target.However, this is a challenging and under-explored task.In this work, we propose a coherent dialogue planning approach that uses a stochastic process to model the temporal dynamics of dialogue paths.We define a latent space that captures the coherence of goal-directed behavior using a Brownian bridge process, which allows us to incorporate user feedback flexibly in dialogue planning.Based on the derived latent trajectories, we generate dialogue paths explicitly using pre-trained language models.We finally employ these paths as natural language prompts to guide dialogue generation.Our experiments show that our approach generates more coherent utterances and achieves the goal with a higher success rate 1 .* Equal contribution. 1 Our code and data are available at https://github. com/iwangjian/Color4Dial.Hello, how are you going today?Not so good.I failed the exam today.