面向YSU-Ⅱ下肢康复机器人语音交互系统的指令文本校对模型  

Instruction text proofreading model oriented to speech interaction system for YSU-Ⅱlower limb rehabilitation robot

作　　者：仲美玉 吴培良[1,2] 窦燕 张晓丹[1] 孔令富 ZHONG Meiyu;WU Peiliang;DOU Yan;ZHANG Xiaodan;KONG Lingfu(School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,China;The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province,Qinhuangdao 066004,China;The Key Laboratory of Software Engineering of Hebei Province,Qinhuangdao 066004,China)

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004 [2]河北省计算机虚拟技术与系统集成重点实验室,河北秦皇岛066004 [3]河北省软件工程重点实验室,河北秦皇岛066004

出　　处：《计算机集成制造系统》2024年第10期3633-3642,共10页Computer Integrated Manufacturing Systems

基　　金：国家重点研发计划资助项目(2018YFB1308300);国家自然科学基金区域联合基金资助项目(U20A20167);北京市自然科学基金资助项目(4202026);河北省自然科学基金资助项目(F202103079);河北省创新能力提升计划资助项目(22567626H);河北省软件工程重点实验室资助项目(22567637H)。

摘　　要：针对YSU-Ⅱ下肢康复机器人语音交互系统存在指令误识的问题,构建了基于双向门控循环单元的Seq2Seq模型来检测并纠正指令文本中的错误字符,提出一种基于指令上下文和关键字的注意力机制(CK Attention),用于捕获指令文本的上下文语义和关键字信息,以提升模型的文本校对能力。面向康复机器人的训练任务自行建立了语料库,并采用5次5折交叉验证法在该语料库上开展了相关实验,以客观评估模型性能。实验结果表明,所建模型适用于指令文本校对任务,CK Attention机制能够有效提升模型的文本校对性能,其检错F_(1)值和纠错F_(1)值分别达到97.72%和93.89%,对常用指令文本的校对时长在0.156 s~0.391 s之间。To resolve the problem of voice command recognition errors existing in the speech interaction system for YSU-Ⅱlower limb rehabilitation robot,a Bidirectional Gated Recurrent Unit(Bi-GRU)based Seq2Seq model was proposed to detect and correct the errors in instruction text.In addition,a Contextual and Keywords-based Attention(CK Attention)mechanism was proposed to enhance the performance of instruction text proofreading model.To objectively evaluate the performance of the model,a corpus for rehabilitation robot training tasks was established,and five 5-fold cross-validation method was employed to conduct a series of experiments on the corpus.The experimental results demonstrated that the Bi-GRU based Seq2Seq model was applicable for the instruction text proofreading task,and the CK Attention mechanism contributed to improve the performance of the text proofreading model.The detection F_(1) and the correction F_(1) of the proposed model had reached 97.72%and 93.89%respectively.The processing time of the instruction text proofreading model for common instructions was 0.156 s~0.391 s.

关 键 词：文本校对 语音交互 Seq2Seq 双向门控循环单元 注意力机制 

分 类 号：TH789[机械工程—仪器科学与技术] TN912.3[机械工程—精密仪器及机械] TP242[电子电信—通信与信息系统]