Automatic speech recognition (ASR) technology allows people to interact with computers in advanced simulation systems or real life applications. ASR is the capability of a computer to convert spoken language to recognized words in textual form. Speech signals for commands and control messages must be processed in a reliable fashion especially under adverse conditions including noisy environments, different speaker accents, and stress. The conversion from spoken language to text can generate mistakes due to several environmental and human conditions that "confuse" stochastic conversion algorithms resulting in a wrong text output. The intelligent parser presented and simulated in this paper helps detect and correct these errors and output the processed speech as a text output and synthesized speech from the computer. The combined use of Java and logic programming in Prolog provides the necessary tools to implement and simulate a parser model that is able to recognize human speech in a reliable fashion, even if the recognition is done under noisy or adverse conditions. Humans are able to understand commands under special or adverse conditions due to their experience, common sense, and other cognitive abilities. Fuzzy logic rules are embedded in an intelligent parser implemented in Prolog to emulate the human's ability to understand language under adverse conditions. The parser could be an excellent tool to recognize spoken language in command communications and simulations. This paper presents an intelligent parser implemented using Java and an intelligent finite-state transition network (FSTN) syntactic parser model implemented in Prolog to overcome these difficulties. A working prototype model is presented in this simulation using commercial speech recognition software. The prototype uses air traffic controllers' commands to demonstrate its operation. A demonstration of the intelligent Prolog parser is being presented at I/ITSEC 2003 Conference.