Speech-to-Sign Language systems are a boon for the hearing disabled. However, according to existing literature, these systems face limitations, particularly in handling homophones and inconsistencies in sign resolution. These challenges can be addressed by designing a system to convert spoken language into sign language, which accounts for homophones and incorporates translation based on Sign Language syntax. Thus, this paper has fourfold objectives. Firstly, the paper provides literature review the existing Speech-to-Sign Language converters. Secondly, the research paper proposes a framework (EqualWe) for Speech-to-Sign Language translation with major resolutions for handling homophones and addressing various dimensions of sign videos. Thirdly, the paper describes the implementation of the EqualWe system, enhancing it with a novel text translation feature for signs with different resolutions. Fourthly, it evaluates EqualWe’s performance using live speech inputs, measuring parameters such as response time and accuracy. Finally, the paper concludes with an analysis and discussion of the findings. EqualWe introduces a Speech-to-Sign Language translation system equipped with the innovative TxtSLProcess toolkit which is lighter than NLTK. The framework designed to handle homophone translation effectively, demonstrates encouraging outcomes, achieving accuracies of 22.31% for letters, 97.5% for words, 80% for homophones, and 82.22% for sentences. EqualWe produced smooth videos after resolving resolution issues.