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http://dx.doi.org/10.7776/ASK.2013.32.5.438

An Enhancement of Japanese Acoustic Model using Korean Speech Database  

Lee, Minkyu (과학기술연합대학원대학교 컴퓨터소프트웨어 및 공학, 한국전자통신연구원 자동통역인공지능연구센터 자동통역연구실)
Kim, Sanghun (과학기술연합대학원대학교 컴퓨터소프트웨어 및 공학, 한국전자통신연구원 자동통역인공지능연구센터 자동통역연구실)
Publication Information
The Journal of the Acoustical Society of Korea / v.32, no.5, 2013 , pp. 438-445 More about this Journal
Abstract
In this paper, we propose an enhancement of Japanese acoustic model which is trained with Korean speech database by using several combination strategies. We describe the strategies for training more than two language combination, which are Cross-Language Transfer, Cross-Language Adaptation, and Data Pooling Approach. We simulated those strategies and found a proper method for our current Japanese database. Existing combination strategies are generally verified for under-resourced Language environments, but when the speech database is not fully under-resourced, those strategies have been confirmed inappropriate. We made tyied-list with only object-language on Data Pooling Approach training process. As the result, we found the ERR of the acoustic model to be 12.8 %.
Keywords
Speech recognition; Japanese speech recognition; Automatic speech translation; Language adaptation; Data pooling; Under-resourced language;
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