Optimum recognition parameters in multiple domains

机译：多个域中的最佳识别参数

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We evaluated large-vocabulary continuous-speech recognizer performance as a function of recognizer tuning parameters for 4 recognition task domains (location, date, time, yes/no) and two different applications (e.g. over-the-telephone reservations) that had some task domains in common. After defining a cost function that included false reject, false accept, and misrecognition errors, we determined optimum parameter values for each domain. The optimum parameter settings differed significantly across domains and even across applications for the same domain. Using a single set of parameter values for all of the tasks in an application can lead to substantial cost penalties for some individual tasks. These results suggest that there can be substantial benefit in using task-specific tuned recognition parameters. We describe a methodology and set of supporting tools for efficiently performing task-specific tuning.

机译：我们评估了大词汇连续语音识别器性能作为4个识别任务域的识别器调整参数（位置，日期，时间，是/否）和两个有一些任务的两个不同的应用程序（例如接线式预留）的函数域名共同。在定义包含错误拒绝的成本函数后，假拒绝和误操作错误，我们确定了每个域的最佳参数值。最佳参数设置跨域跨域甚至跨越同一域的应用程序不同。对于应用程序中所有任务的单一参数值，可以导致某些个人任务的大量成本惩罚。这些结果表明，在使用特定于任务的调谐识别参数时可能存在实质性的好处。我们描述了一种用于有效执行特定于任务的调谐的方法和一组支持工具。

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《IEEE Workshop Interactive Voice Technology for Telecommunications Applications》|1998年||共4页
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Peterson P.; Ann R.; Institute of Electric and Electronic Engineer;
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中图分类自动化技术、计算机技术;
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Optimum recognition parameters in multiple domains

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