In a speech interface, a gap between a user’s mental model and actual structures of systems tends to be large because the amount of information conveyed by speech is limited. We address dynamic help generation adapted to users, to decrease the gap between them. We defined a domain concept tree as an expression of a system’s actual structure. We estimated and maintained user’s knowledge about the system on the tree. Every node in the tree has values representing the degree to which a user understands the concepts corresponding to the nodes. The values are updated based on the content of user’s utterances and help messages the system gives. Help messages provided for users are determined by referring to the domain concept tree and identifying concepts the user does not understand. We evaluated our method by testing twelve novice subjects. Both the average time to complete tasks and the number of utterances significantly decreased because of the help messages provided by our method.