Machine Translation of Korean-to-English spoken language Based on Semantic Patterns

This paper analyzes Korean spoken language and describes the machine translation o[ Korean to-English spoken language based on semantic patterns, In Korean-to-English machine translation. ambiguity of Korean sentence analysis using syntactic information can be resolved by semantic patterns, Therefore, for machine translation of spoken language, we estabilish the system based on semantic patterns extracted from Korean scheduling domain, This system obtains the robustness by skip ability of syllables in analysis of Korean sentence and we add options to semantic patterns in order to reduce pattern numbers, The data used [or the experiment are scheduling domain and performance of Korean-to-English translation is 88%,