Is word error rate a good indicator for spoken language understanding accuracy
Is word error rate a good indicator for spoken language understanding accuracy
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单词错误率是口语理解准确性的一个很好的指标吗
DOI：
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发表时间：
2003
期刊：
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通讯作者：
Ciprian Chelba
中科院分区：
文献类型：
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作者：
Ye;A. Acero;Ciprian Chelba
语音界的传统观点是，给定固定的理解分量，更好的语音识别准确度是更好的口语理解准确度的良好指标。这项工作的结果表明，情况并非总是如此。比降低单词错误率更重要的是，应该训练用于识别的语言模型以匹配用于理解的优化目标。在这项工作中，我们应用了口语理解模型作为语音识别中的语言模型。该模型是通过基于实例的学习算法获得的，该算法优化了理解精度。虽然语音识别单词错误率比trigram模型高46%，但整体槽理解错误可以减少多达17%。
It is a conventional wisdom in the speech community that better speech recognition accuracy is a good indicator for better spoken language understanding accuracy, given a fixed understanding component. The findings in this work reveal that this is not always the case. More important than word error rate reduction, the language model for recognition should be trained to match the optimization objective for understanding. In this work, we applied a spoken language understanding model as the language model in speech recognition. The model was obtained with an example-based learning algorithm that optimized the understanding accuracy. Although the speech recognition word error rate is 46% higher than the trigram model, the overall slot understanding error can be reduced by as much as 17%.