Abstract
A transformation matrix linear interpolation (TMLI) approach for speaker adaptation is proposed. TMLI uses the transformation matrixes produced by MLLR from selected training speakers and the testing speaker. With only 3 adaptation sentences, the performance shows a 12.12% word error rate reduction. As the number of adaptation sentences increases, the performance saturates quickly. To improve the behavior of TMLI for large amounts of adaptation data, the TMLI+MAP method which combines TMLI with MAP technique is proposed. Experimental results show TMLI+MAP achieved better recognition accuracy than MAP and MLLR+MAP for both small and large amounts of adaptation data.
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Foundation item: Supported by the Science and Technology Committee of Shanghai (01JC14033)
Biography: XU Xiang-hua (1977-), female, Ph. D. candidate, research direction: large vocabulary continuous Mandarin speech recognition and speaker adaptation
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Xiang-hua, X., Jie, Z. Speaker adaptation with transformation matrix linear interpolation. Wuhan Univ. J. Nat. Sci. 9, 927–930 (2004). https://doi.org/10.1007/BF02850801
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DOI: https://doi.org/10.1007/BF02850801