Overview of the NLPCC 2018 Shared Task:Spoken Language Understanding in Task-Oriented Dialog Systems
This paper presents the overview for the shared task at the 7th CCF Conference on Natural Language Processing & Chinese Computing(NLPCC 2018): Spoken Language Understanding(SLU)in Task-oriented Dialog Systems.SLU usually consists of two parts,namely intent identification and slot filling.The shared task made publicly available a Chinese dataset of over 5.8 K sessions,which is a sample of the real query log from a commercial taskoriented dialog system and includes 26 K utterances.The contexts within a session are taken into consideration when a query within the session was annotated.To help participating systems correct ASR errors of slot values,this task also provides a dictionary of values for each enumerable type of slot.16 teams entered the task and submitted a total of 40 SLU results.In this paper,we will review the task,the corpus,and the evaluation results.
SLU Intent identification Slot filling
Xuemin Zhao Yunbo Cao
Tencent Technology(Chengdu)Company Limited,Chengdu,China Tencent Technology(Beijing)Company Limited,Beijing,China
国际会议
2018自然语言处理与中文计算国际会议(NLPCC2018)
呼和浩特
英文
468-478
2018-08-26（万方平台首次上网日期，不代表论文的发表时间）