Clarification Question Generation for Speech Recognition Error Recovery Using Monolingual SMT
Clarification dialogue is an efficient and direct way of handling speech recognition errors in speech interface applications.In this paper we present a new approach to Clarification Question (CQ) generation.Monolinguai phrase-hased SMT (PB-SMT) framework is introduced to generate robust and flexible CQs.A parallel corpus from simulated error to manually anno-tated CQ is established and used for training the model.A new type of generalized phrase pair is expanded from conventional translation phrase table.Combining both generalized and conventionai phrase pairs,a two-step decoding process is carried out to generate CQs.Both manually and automatic metrics are used to evaluate the quality of generated CQs.Experimental results show that our method can effectively generate reasonable CQs form miss-recognized utteronees,and generated CQs can be used to prompt a clarification dialogue for error handling.
clarification dialogue question generatio speech recognition error recovery monolingual SMT
Dong Yu
International R&D Center for Chinese Education, Beijing Language and Culture University, Beijing, 10083, China
国际会议
太原
英文
942-946
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）