A Review of Voice-Driven Accessible Vocational Training Platforms for Persons with Visual Impairment

Abstract: The increasing demand for inclusive education and skill development has brought significant attention to assistive technologies designed for persons with visual impairments. Voice-driven vocational training platforms represent a transformative approach to delivering accessible learning experiences without reliance on visual interfaces. This review examines existing literature, system architectures, and technological frameworks used in voice-based e-learning and vocational training tools tailored for visually impaired users. The paper presents a four-tier taxonomy of platform sophistication, analyses key methods including Text-to-Speech (TTS), Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and screen reader integration, and identifies critical research gaps. Comparative analysis of reviewed systems highlights strengths and limitations. The review concludes by recommending a unified, adaptive voice- driven platform with offline capabilities and multi-language support to bridge the vocational accessibility gap.

Keywords: Visual Impairment, Voice-Driven Learning, Vocational Training, Assistive Technology, Text-to-Speech, Speech Recognition, Accessible Education, NLP