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An alignment matching method to explore pseudosyllable properties across different corpora

机译:一种对齐匹配方法,用于探索不同语料库的假音节属性

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In previous work we have defined a pseudosyllable unit for an English read speech recognition task. In this study we inves tigate the robustness of extraction of the pseudosyllable units and investigate how such units can be integrated into speech recognition systems. An evaluation method that maps hypoth esis phonemes to reference phonemes is proposed. Analysis is performed on pseudosyllables extracted from two different sets of speech data. Mutual information is used to look at the rela tionship between different pseudosyllabic aspects and the error patterns of hypothesis phonemes. It is shown that the pseudo syllable extraction algorithm is robust and gives units with con sistent statistics. Pseudosyllables which have a phone triplet structure tend to have lower insertion error. In temporal regions where pseudosyllables overlap with each other, more insertion errors may occur.
机译:在先前的工作中,我们为英语阅读语音识别任务定义了一个假音节单元。在这项研究中,我们研究了伪音节单元提取的鲁棒性,并研究了如何将这些单元集成到语音识别系统中。提出了一种将假说音素映射到参考音素的评估方法。对从两组不同的语音数据中提取的伪音节进行分析。相互信息用于查看不同假音节方面与假设音素错误模式之间的关系。结果表明,伪音节提取算法是鲁棒的,并且给单元提供一致的统计信息。具有电话三联体结构的假音节倾向于具有较低的插入误差。在伪音节彼此重叠的时间区域中,可能会发生更多的插入错误。

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