计算机科学 ›› 2021, Vol. 48 ›› Issue (8): 234-239.doi: 10.11896/jsjkx.200700162
所属专题： 自然语言处理 虚拟专题
杨慧敏, 马廷淮
YANG Hui-min, MA Ting-huai
摘要： 对话模型是自然语言处理的重要方向之一。现如今的对话模型主要分为基于检索的方式和基于生成的方式。然而,检索方式无法回应语料库中未出现的问句,而生成方式容易出现安全回复的问题。鉴于此,提出融合检索与生成的复合对话模型,通过将检索方式与生成方式相结合来弥补各自的缺点。首先通过检索模块得到K个检索上下文以及所对应的K个检索候选回应。在多回应生成模块中进一步结合检索上下文得到若干生成候选回应。最后的候选回应排序模块分为预筛选与后排序两个步骤。预筛选部分通过计算输入问题与候选回应的相似度得到最优检索回应与最优生成回应,后排序部分进一步选出对于输入问题最合适的回答。实验结果显示,相对于传统模型,复合对话模型在BLUE指标上提升了6%,在多样性指标上提升了12%。
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