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Recognition of Chinese names in continuous speech for directory assistance applications

机译:在连续语音中识别中文名称以进行目录辅助应用

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The aim of this paper is to enable continuous speech input for directory assistance tasks. We are focusing on handling of long lists of Chinese names. Compared with the more restrictive isolated word input scenario the name error rate for the continuous task is much larger. By concentrating on the name segment, we investigate two methods in order to bridge the performance gap. First, a confidence measure-based rescoring approach to pickup the most confident name is presented. Then, a segmentation-based two-pass method, first estimating the time segmentation of the name and secondly, applying the isolated word recognition technique is studied. The obtained results for both methods reveal a significant name recognition error rate reduction by up to 42% relatively.
机译:本文的目的是为目录服务任务提供连续的语音输入。我们专注于处理一长串中文名称。与限制性更强的隔离单词输入方案相比,连续任务的名称错误率要大得多。通过专注于名称段,我们研究了两种方法以弥合性能差距。首先,提出了一种基于置信度度量的评分方法来选择最可信的名称。然后,研究了一种基于分段的两遍方法,该方法首先估计名称的时间分段,其次研究应用孤立词识别技术。两种方法所获得的结果表明,名称识别错误率相对降低了多达42%。

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