计算机工程2025，Vol.51Issue(10)：79-86,8.DOI:10.19678/j.issn.1000-3428.0069714
基于完形填空的小样本意图槽位联合识别方法
Few-Shot Joint Recognition Method of Intent and Slot Based on Cloze
摘要
Abstract
As the core module of a task-oriented dialogue system,Natural Language Understanding(NLU)aims to structurally represent user inputs in natural language;this is generally decomposed into two subtasks:intent recognition and slot filling.Recently,the joint modeling of these two tasks has become a universal solution.However,establishing the connection between the two tasks is difficult to collect using a small number of support set samples in few-shot scenarios.Owing to domain gaps,the general knowledge learned from resource-rich source domains cannot be directly transferred to target domains.Inspired by cloze,this paper considers the average vector of non-slot(labeled as"O")words as the sentence pattern representation and proposes a Sentence Pattern Adaptive Prototype Network(SPAPN).In resource-rich source domains,the model fully learns the cross-domain semantic knowledge of sentence patterns and uses this information as a hub to indirectly model the relationship between intents and slots.Resource-low target domains adopt a meta-learning training mode and an attention mechanism to learn the correlation among the prototypes of intents,slots,and sentence patterns to enhance the semantic representations of intent and slot prototypes,and combine Comparative Alignment Learning(CAL)is employed to judge the labels of intents and slots based on the vector similarity between the query samples and these prototypes.Experiments conducted on Chinese and English benchmark datasets show that,irrespective of fine-tuning,the proposed method consistently outperforms state-of-the-art baselines in terms of intent accuracy,slot filling F1 score,and joint accuracy.关键词
任务型对话系统/意图识别/槽位填充/小样本学习/注意力机制Key words
task-oriented dialogue system/intent recognition/slot filling/few-shot learning/attention mechanism分类
计算机与自动化引用本文复制引用
毕然,杨奉毅,周喜,杨雅婷,艾比布拉·阿塔伍拉..基于完形填空的小样本意图槽位联合识别方法[J].计算机工程,2025,51(10):79-86,8.基金项目
新疆维吾尔自治区杰出青年科学基金(2022D01E04) （2022D01E04）
新疆维吾尔自治区"天池英才"引进计划 （）
新疆维吾尔自治区"天山英才"科技创新领军人才项目(2022TSYCLJ0035) （2022TSYCLJ0035）
新疆维吾尔自治区重大科技专项(2020A02001-1). （2020A02001-1）
