Measurement accuracy of material parameters is highly influenced by the difficulty in distinguishing terahertz (THz) signals from many unwanted signals. We introduce a novel method to effectively extract and separate THz signals from such effects. The proposed algorithm is assessed in terms of extraction efficiency, model validity and material parameter calculation accuracy, demonstrating significant enhancement in the THz spectrum accuracy and hence, material evaluation performance.