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Self-Adaptation Algorithm Based on Maximum A Posteriori Eigenvoice for Korean Connected Digit Recognition  

Kim Dong Kook (전남대학교 전자컴퓨터정보통신공학부)
Jeon Hyung Bae (한국전자통신연구원)
Publication Information
The Journal of the Acoustical Society of Korea / v.23, no.8, 2004 , pp. 590-596 More about this Journal
Abstract
This paper Presents a new self-adaptation algorithm based on maximum a posteriori (MAP) eigenvoice for Korean connected digit recognition. The proposed MAP eigenvoice is developed by introducing a probability density model for the eigenvoice coefficients. The Proposed approach provides a unified framework that incorporates the Prior model into the conventional eigenvoice estimation. In self-adaptation system we use only one adaptation utterance that will be recognized, we use MAP eigenvoice that is most robust adaptation. In series of self-adaptation experiments on the Korean connected digit recognition task. we demonstrate that the performance of the proposed approach is better than that of the conventional eigenvoice algorithm for a small amount of adaptation data.
Keywords
Maximum a Posteriori; Speaker Adaptation; Self-adaptation; Speech Recognition;
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