Experimental results show that phonetic classification based on the triphone can greatly improve system performance. The proposed method reduces the error rate by 28% compared with a baseline system.

实验表明：基于语音学分类的三音子单元对识别性能有明显的改善，系统的首选误识率相对基线系统降低了28%。

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The classification error rate for normal and early stage DR samples reached 21.35% using a linear classifier and the leave-one-out method.

使用线性分类器进行分类，并用“留一法”统计结果，正常人和早期DR病例的分类错误率为21.35%。

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Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.

最小错识率(MCE) HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。

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