Using output probability distribution for oov word rejection

Shilei Huang, Xiang Xie, Pascale Fung
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引用次数: 2

Abstract

This paper proposes a method to calculate the confidence score for out-of-vocabulary (OOV) word verification based on the Output Probability Distribution (OPD) of phoneme HMMs. Compared with input vector for dynamic garbage model, OPD vector contains more information than the sorted probabilities. Confidence score of each phoneme is calculated by SVM with OPD vectors as input. Hypotheses are accepted or rejected based on this confidence score. Experimental results showed that the proposed method achieved lower EER in word verification task than the conventional dynamic garbage model.
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使用输出概率分布进行oov字拒绝
本文提出了一种基于音素hmm的输出概率分布(OPD)计算词汇外(OOV)单词验证置信度分数的方法。与动态垃圾模型的输入向量相比,OPD向量比排序概率包含更多的信息。以OPD向量为输入,利用支持向量机计算每个音素的置信度。假设被接受或拒绝是基于这个置信度得分。实验结果表明,与传统的动态垃圾模型相比,该方法在单词验证任务中获得了更低的EER。
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