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An alignment matching method to explore pseudosyllable properties across different corpora

机译:探讨不同基层伪座属性的对齐匹配方法

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In previous work we have defined a pseudosyllable unit for an English read speech recognition task. In this study we investigate 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 hypothesis 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 relationship 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 consistent 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:在以前的工作中,我们已经为英语读取语音识别任务定义了一个伪旋塞单元。在这项研究中,我们研究了伪座单元的提取的鲁棒性,并研究了如何集成在语音识别系统中的这种单元。提出了一种映射假设音素来参考音素的评估方法。对从两组不同的语音数据提取的伪座可进行分析。互信息用于查看不同伪座的方面与假设音素的误差模式之间的关系。结果表明,伪音节提取算法具有稳健性,并提供具有一致统计信息的单位。具有手机三重态结构的伪座倾向于具有较低的插入误差。在临时区域,其中伪座的彼此重叠,可能发生更多插入误差。

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