Software inspections are an effective method for early detection of faults present in software development artifacts (e.g., requirements and design documents). However, many faults are left undetected due to the lack of focus on the underlying sources of faults (i.e., what caused the injection of the fault?). To address this problem, research work done by Psychologists on analyzing the failures of human cognition (i.e., human errors) is being used in this research to help inspectors detect errors and corresponding faults (manifestations of errors) in requirements documents. We hypothesize that the fault detection performance will demonstrate significant gains when using a formal taxonomy of human errors (the underlying source of faults). This paper describes a newly developed Human Error Taxonomy (HET) and a formal Error-Abstraction and Inspection (EAI) process to improve fault detection performance of inspectors during the requirements inspection. A controlled empirical study evaluated the usefulness of HET and EAI compared to fault based inspection. The results verify our hypothesis and provide useful insights into commonly occurring human errors that contributed to requirement faults along with areas to further refine both the HET and the EAI process.