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Aging speech recognition with speaker adaptation techniques: Study on medium vocabulary continuous Bengali speech

机译:说话人适应技术对语音的老化识别:中词汇连续孟加拉语语音研究

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摘要

The article describes the speech recognition system development in Bengali language for aging population with various adaptation techniques. Variability in acoustic characteristics among different speakers degrades speech recognition accuracy. In general, perceptual as well as acoustical variations exists among speakers, but variations are more pronounced between young and aged population. Deviation in voice source features between two age groups, affect the speech recognition performance. Existing automatic speech recognition algorithms demands large amount of training data with all variability to develop a robust speech recognition system. However, speaker normalization and adaptation techniques attempts to reduce inter-speaker or intra-speaker acoustic variability without having large amount of training data. Here, conventional acoustic model adaptation method e.g. vocal tract length normalization, maximum likelihood linear regression and/or maximum a posteriori are combined in the current study to improve recognition accuracy. Moreover, maximum mutual information estimation technique has been implemented in this study.
机译:本文介绍了孟加拉语通过多种适应技术为老年人口开发的语音识别系统。不同扬声器之间的声学​​特性的差异降低了语音识别的准确性。通常,说话者在听觉和听觉上都存在差异,但是年轻人和老年人之间的差异更为明显。两个年龄组之间的语音源功能差异会影响语音识别性能。现有的自动语音识别算法要求具有各种可变性的大量训练数据,以开发鲁棒的语音识别系统。但是,说话者归一化和自适应技术试图在没有大量训练数据的情况下减少说话者之间或说话者内部的声音变化。在此,传统的声学模型自适应方法例如在当前研究中,结合了声道长度归一化,最大似然线性回归和/或最大后验,以提高识别准确性。此外,本研究中已实现了最大的互信息估计技术。

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