In this paper, we describe the strategy of semantic analysis for a speech user interface that is designed for a multimodal intelligent tutoring system. The semantic analysis involves three phases: semantic parsing, salient words/phrases spotting, and accented word detection. Semantic parsing attempts to represent the recognized sentence with a well-formed semantic frame. The recognized sentence consists of the a posterior most probably hypothesized words given the acoustic evidence, and is compliant with the grammatical knowledge that is represented by a semantic language model. The salient words/phrases are useful when semantic parsing fails. The accented words are useful when the user response is out of our expectations, and assist to make the computer agent smarter and smarter.