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Preprocessing for elderly speech recognition of smart devices

机译：智能设备老年人语音识别的预处理

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摘要

Due to the increasing aging population in modern society and to the proliferation of smart devices, there is a need to enhance speech recognition among smart devices in order to make information easily accessible to the elderly as it is to the younger population. In general, speech recognition systems are optimized to an average adult's voice and tend to exhibit a lower accuracy rate when recognizing an elderly person's voice, due to the effects of speech articulation and speaking style. Additional costs are bound to be incurred when adding modifications to current speech recognitions systems for better speech recognition among elderly users. Thus, using a preprocessing application on a smart device can not only deliver better speech recognition but also substantially reduce any added costs. Audio samples of 50 words uttered by 80 elderly and young adults were collected and comparatively analyzed. The speech patterns of the elderly have a slower speech rate with longer inter-syllabic silence length and slightly lower speech intelligibility. The speech recognition rate for elderly adults could be improved by means of increasing the speech rate, adding a 1.5% increase in accuracy, eliminating silence periods, adding another 4.2% increase in accuracy, and boosting the energy of the formant frequency bands for a 6% boost in accuracy. After all the preprocessing, a 12% increase in the accuracy of elderly speech recognition was achieved. Through this study, we show that speech recognition of elderly voices can be improved through modifying specific aspects of differences in speech articulation and speaking style. In the future, we will conduct studies on methods that can precisely measure and adjust speech rate and find additional factors that impact intelligibility.
机译：由于现代社会中老龄化人口的增加以及智能设备的普及，需要增强智能设备之间的语音识别，以使老年人和年轻人一样容易获得信息。通常，由于语音清晰度和说话风格的影响，语音识别系统针对普通成年人的语音进行了优化，并且在识别老年人的语音时倾向于表现出较低的准确率。当增加对当前语音识别系统的修改以在老年人中更好地识别语音时，必然会产生额外的费用。因此，在智能设备上使用预处理应用程序不仅可以提供更好的语音识别，还可以大大降低任何增加的成本。收集并比较了80位老年人和年轻人发出的50个单词的音频样本。老年人的言语模式语速较慢，音节间的沉默时间较长，言语清晰度较低。老年人的语音识别率可以通过提高语音速率，增加1.5％的准确度，消除静音期，增加4.2％的准确度以及增加共振峰频段的能量来提高（6） ％提高准确性。经过所有的预处理，老年人语音识别的准确性提高了12％。通过这项研究，我们表明，通过修改语音清晰度和说话风格差异的特定方面，可以改善老年人语音的语音识别。将来，我们将研究可精确测量和调整语速并发现影响清晰度的其他因素的方法。

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  • 来源
    《Computer speech and language》 |2016年第3期|110-121|共12页
  • 作者

    Soonil Kwon; Sung-Jae Kim; Joon Yeon Choeh;

  • 作者单位

    Interaction Technology Laboratory, Department of Digital Contents, Sejong University, 98 Gunja-Dong, Gwangjin-Gu, Seoul 143-747, Republic of Korea;

    Interaction Technology Laboratory, Department of Digital Contents, Sejong University, 98 Gunja-Dong, Gwangjin-Gu, Seoul 143-747, Republic of Korea;

    Interaction Technology Laboratory, Department of Digital Contents, Sejong University, 98 Gunja-Dong, Gwangjin-Gu, Seoul 143-747, Republic of Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Elderly voice interface; Speech recognition; Aging society;

    机译：老人语音接口;语音识别;老龄化社会;

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