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Enhancing automatic speech recognition with an ultrasonic lip motion detector

机译:利用超声波唇部运动检测器增强自动语音识别

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This paper presents the results of experimentation with a simple ultrasonic lip motion detector or "Ultrasonic Mike" in automatic speech recognition. The device is tested in a speaker dependent isolated word recognition task with a vocabulary consisting of the spoken digits from zero to nine. The "Ultrasonic Mike" is used as input to an automatic lip reader. The automatic lip reader uses template matching and dynamic time warping to determine the best candidate for a given test utterance. The device is first tested as a stand alone automatic lip reader achieving accuracy as high as 89%. Next the automatic lip reader is combined with a conventional automatic speech recognizer. Classifier fusion is based on a pseudo probability mass function derived from the dynamic time warping distances. The combined system is tested with various levels of acoustic noise added. In a typical example, at 0 dB, the acoustic recognizer's accuracy was 78%, the lip reader accuracy was at 69%, but the combined accuracy was 93%. This experiment demonstrates that this simple ultrasonic lip motion detector, that has an output data rate 12500 times less than a typical video camera, can improve automatic speech recognition in noisy environments. This experiment also demonstrates an effective classifier fusion algorithm based on dynamic time warping distances.
机译:本文介绍了使用简单的超声波唇部运动检测器或“超声波麦克”进行自动语音识别的实验结果。该设备在与说话者相关的孤立单词识别任务中经过测试,其词汇表中的语音数字从零到九。 “超声波麦克”用作自动嘴唇读取器的输入。自动唇读器使用模板匹配和动态时间扭曲来确定给定测试话语的最佳候选者。该设备首先作为独立的自动嘴唇读取器进行测试,可实现高达89%的准确度。接下来,自动嘴唇读取器与传统的自动语音识别器结合在一起。分类器融合基于从动态时间扭曲距离得出的伪概率质量函数。对组合系统进行了测试,并添加了各种级别的声学噪声。在一个典型示例中,在0 dB时,声学识别器的精度为78%,嘴唇阅读器精度为69%,但组合精度为93%。该实验表明,这种简单的超声波嘴唇运动检测器的输出数据速率是典型摄像机的12500倍,可以改善嘈杂环境中的自动语音识别。该实验还演示了一种基于动态时间规整距离的有效分类器融合算法。

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