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SPEAKER ADAPTATION BY CORRELATION (ABC)

机译：扬声器相关性自适应（ABC）

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摘要

This paper describes a new rapid speaker adaptation algorithm using a small amount of adaptation data. This algorithm, termed adaptation by correlation (ABC), exploits the intrinsic correlation among speech units to update the speech models. The algorithm updates the means of each Gaussian based on its correlation with means of the Gaussians which are observed in the adaptation data; the updating formula is derived from the theory of least squares. Our experiments on the ARPA NAB-94 evaluation (Eval-94) and the ARPA Hub4-96 (Hub4-96) tasks indicate that ABC seems more stable than MLLR when the amount of data for adaptation is very small (~ 5 seconds), and that ABC seems to enhance MLLR when they are combined.
机译：本文介绍了一种使用少量自适应数据的新型快速说话人自适应算法。这种称为相关性自适应（ABC）的算法利用语音单元之间的固有相关性来更新语音模型。该算法基于每个高斯均值与适应数据中观察到的高斯均值的相关性来更新均值；更新公式是从最小二乘理论推导出来的。我们对ARPA NAB-94评估（Eval-94）和ARPA Hub4-96（Hub4-96）任务的实验表明，当自适应数据量很小（〜5秒）时，ABC似乎比MLLR更稳定，当它们结合在一起时，ABC似乎可以增强MLLR。

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