The complexity of software development has increased significantly, necessitating precise and efficient analysis of software requirements. One of the primary challenges in software engineering is ensuring that requirements are clear, consistent, and aligned with stakeholder intentions. This paper introduces an approach to enhance software requirements analysis using semantic similarity techniques. By leveraging natural language processing (NLP) methods, this approach can automatically identify and analyze the semantic relationships between words and sentences within requirement documents. This not only helps in detecting ambiguities and inconsistencies but also facilitates better communication among stakeholders. The results from applying this method to various case studies demonstrate its potential to improve the quality and clarity of software requirements.