Optimize the obvious: Automatic call flow generation

In commercial spoken dialog systems, call flows are built by call flow designers implementing a predefined business logic. While it may appear obvious from this logic how the call flow has to look like, i.e., which pieces of information have to be gathered from the caller or back-end systems and in which sequence, there are, in fact, strong arguments for automating call flow generation: 1) manual generation is time-consuming 2) manual generation is suboptimal and error-prone 3) automatic generation can react on dynamically changing business logic or external factors such as the distribution of callers and call reasons This paper presents a method for automatically deriving a call flow minimizing the average number of user turns given a business logic and a frequency distribution of call reasons. As an example, we applied the method to a call routing application whose manually built call flow is processing about 4 million calls per month and whose call reason distribution served to measure the impact of the automatic call flow generation.