[Paper] Empirical Study of End-to-End Speech-to-Braille Translation of Japanese for Deafblind Persons

This study undertakes an end-to-end braille translation approach for Japanese speech to address the needs of deafblind individuals. The Japanese language consists of many characters, such as kanji and kana, and much effort is required for manual translation. Thus, in Japan, automated braille translation is anticipated to enhance information accessibility for deafblind individuals. Conventionally, braille translation relies on separate ASR and braille software, creating a two-step process. This two-step process is inefficient because the speech-to-braille translation is performed via kana-kanji characters. On the other hand, Japanese Braille exhibits strong compatibility with automatic speech recognition (ASR) owing to its predominant use of kana characters, which mirrors Japanese phonetic features. Therefore, one-step speech-to-braille translation is expected to perform better than the conventional two-step method. In this study, we propose an end-to-end (E2E) approach using neural networks to translate Japanese Braille directly from speech and compare it with the conventional two-step method.