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Realizing speech to gesture conversion by keyword spotting

机译:通过关键词识别实现语音到手势的转换

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The paper proposed a method to realize a speech-to-gesture conversion for communication between normal and speech-impaired people. Keyword spotting was employed to recognize the keywords from input speech signals. At the same time, the three dimensional gesture models of keywords were built by 3D modeling technology according to the “Chinese sign language”. The speech-to-gesture conversion was finally realized by playing the corresponding 3D gestures with OpenGL from the re-sults of keyword spotting. Tests show that the realized keyword spotting achieves 90.1% of average recognition rate on letters and numbers. The converted gestures obtain 4.4 of the mean opinion score. Therefore the proposed method can be applied to the communications between normal and speech-impaired people.
机译:本文提出了一种实现正常人与言语障碍者之间交流的言语-手势转换方法。关键字识别被用来从输入的语音信号中识别关键字。同时,根据“中国手语”,利用3D建模技术建立了关键词的三维手势模型。语音到手势的转换最终是通过从关键字搜索的结果中使用OpenGL播放相应的3D手势来实现的。测试表明,所实现的关键词识别实现了字母和数字平均识别率的90.1%。转换后的手势获得平均意见得分的4.4。因此,所提出的方法可以应用于正常人和言语障碍者之间的通信。

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