AI RESEARCH
Automatic Speech Recognition for Documenting Endangered Languages: Case Study of Ikema Miyakoan
arXiv CS.AI
•
ArXi:2603.26248v1 Announce Type: cross Language endangerment poses a major challenge to linguistic diversity worldwide, and technological advances have opened new avenues for documentation and revitalization. Among these, automatic speech recognition (ASR) has shown increasing potential to assist in the transcription of endangered language data. This study focuses on Ikema, a severely endangered Ryukyuan language spoken in Okinawa, Japan, with approximately 1,300 remaining speakers, most of whom are over 60 years old.