The interaction-independent questioning proposed by customers in the communication industry has more defaults and strong contextual relevance,which lead the current response techniques of communication customer service robots are no longer able to satisfy the needs of customers.For this reason,artificial intelligence techniques for multi-scenario question and answer of communication robots are proposed.The design of the internal architecture of the communication customer service robot reply includes multiple functional modules such as speech recognition,text recognition,semantic understanding and dialog interaction,etc.The simple Bayesian classifier is used to recognize and classify the customer messages.By commecting the context to extract the question points in the customer messages,the long and short-term memory network is applied in the calculation process of reply message matching to obtain the better reply content.In the customer service robot performance test,different scenarios are set up for testing.The test results show that in different scenarios,the communication customer service robot's various indicators are all better than the traditional customer service robot,and it has a better question and answer reply effect.The results verify the scenario versatility and effectiveness of the designed customer service robot.
关键词
人工智能/信通客服/交互式问句/朴素贝叶斯分类器/长短期记忆网络/多场景问答/消息匹配
Key words
Artificial intelligence/Communication customer service/Interactive questioning/Simple Bayesian classifier/Long and short-term memory network/Multi-scenario question and answer/Message matching
维普
万方数据