This paper describes the acoustic processing in a syntactically guided natural language speech understanding system. A major characteristic of this system is that through the interaction of pragmatic, semantic, and syntactic information, candidate words are proposed to exist at specific points in the acoustic stream. The purpose of the acoustic processor is to verify or reject these hypotheses. This verification is done in two stages. First, digital filtering is done to classify each 10-ms segment as one of ten primitive classes. If the proposed word is consistent with the pattern of primitive classes at the corresponding point in the acoustic stream, further analysis is done using linear predictive coding and other digital filters. The results of this analysis are used to segment the acoustic signal and to further classify the voiced segments. Because this segmentation and classification can be tailored for each word, difficult analysis problems caused by coarticulation between adjacent sounds can be successfully solved. When combined with a sophisticated linguistic processor, these acoustical processing methods yield correct understanding of natural language utterances.