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Exploring the Effect of Differences in the Acoustic Correlates of Adults' and Children's Speech in the Context of Automatic Speech Recognition

机译:在自动语音识别的背景下,探究成人和儿童语音的声学相关性差异的影响

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This work explores the effect of mismatches between adults' and children's speech due to differences in various acoustic correlates on the automatic speech recognition performance under mismatched conditions. The different correlates studied in this work include the pitch, the speaking rate, the glottal parameters (open quotient, return quotient, and speech quotient), and the formant frequencies. An effort is made to quantify the effect of these correlates by explicitly normalizing each of them using the already existing techniques available in literature. Our initial study done on a connected digit recognition task shows that among these parameters only the formant frequencies, the pitch, and the speaking rate affect the automatic speech recognition performance. Significant improvements are obtained in the performance with normalization of these three parameters. With combined normalization of the pitch, the speaking rate, and the formant frequencies, 80% and 70% relative improvements are obtained over the baseline for children's speech and adults' speech recognition under mismatched conditions.
机译:这项工作探讨了在不匹配条件下,由于各种声学相关性的差异而导致的成年人和儿童语音之间的不匹配对自动语音识别性能的影响。在这项工作中研究的不同相关因素包括音调,语速,声门参数(开放商,返回商和语音商)以及共振峰频率。通过使用文献中已有的现有技术对每个相关进行显式标准化,努力量化这些相关的影响。我们对关联数字识别任务的初步研究表明,在这些参数中,仅共振峰频率,音高和发声率会影响自动语音识别性能。通过对这三个参数进行归一化,可以在性能上获得重大改进。通过对音调,语音速率和共振峰频率进行归一化处理,在不匹配条件下,儿童语音和成年人语音识别的基线相对基线可获得80%和70%的相对改善。

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