Real-Time Communication Aid System for Korean Dysarthric Speech
Kwanghyun Park, Jungpyo Hong · Applied Sciences · 2025
Dysarthria is a speech disorder characterized by difficulties in articulation and vocalization due to impaired control of the articulatory system. Around 30% of individuals with speech disorders have dysarthria, facing significant communication challenges. Existing assistive tools for dysarthria either require additional manipulation or only provide word-level speech support, limiting their ability to support effective communication in real-world situations. Thus, this paper proposes a real-time communication aid system that converts sentence-level Korean dysarthric speech to non-dysarthric normal speech. The proposed system consists of two main parts in cascading form. Specifically, a Korean Automatic Speech Recognition (ASR) model is trained with dysarthric utterances using a conformer-based architecture and the graph transducer network–connectionist temporal classification algorithm, significantly enhancing recognition performance over previous models. Subsequently, a Korean Text-To-Speech (TTS) model based on Jointly Training FastSpeech2 and HiFi-GAN for end-to-end Text-to-Speech (JETS) is pipelined to synthesize high-quality non-dysarthric normal speech. These models are integrated into a single system on an app server, which receives 5–10 s of dysarthric speech and converts it to normal speech after 2–3 s. This can provide a practical communication aid for people with dysarthria.