Voice-Driven Support System for Speech Practice in Older Adults: An Accessible Web–Mobile Approach

Population aging poses significant challenges to oral communication due to age-related changes in articulation, verbal fluency, and speech pacing, even among older adults without neurodegenerative conditions. Despite advances in voice-based assistive technologies, there remains a lack of integrated engineering solutions that support structured, autonomous speech practice in non-clinical environments. This study proposes a deterministic, rule-based speech evaluation workflow implemented within a hybrid web–mobile assistive system. The workflow integrates audio capture, cloud-based automatic speech recognition (ASR), rule-based pronunciation evaluation, immediate multimodal feedback, and progress monitoring within a unified system architecture. The proposed architecture includes a mobile application for older adults and a web platform for configuration and monitoring by caregivers. A prototyping-oriented methodology was applied, including requirements elicitation, system design, implementation, and usability evaluation using the Thinking Aloud method and the System Usability Scale (SUS). Results showed stable system behavior under controlled evaluation conditions, an average recognition accuracy of 90% during preliminary evaluation sessions, and a response latency of 1.82 s, supporting stable real-time interaction during guided speech exercises. These findings demonstrate the feasibility of the proposed assistive architecture as an accessible and reproducible solution for guided speech support in older adults.