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The Effects of Electrode Locations on Silent Speech Recognition using High-Density sEMG

机译:电极位置对高密度sEMG沉默语音识别的影响

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In circumstances when silent speech is necessary, it is an attractive technology to use the surface electromyography (sEMG) signals recorded from electrodes placed on the face and neck regions for automatic speech recognition. For this technology, the electrode location is an important factor for the performance of speech recognition. However, it remains unclear how the electrode positions affect the performance, so there is no guideline for electrode placement in practical applications. Thus, the method of high-density sEMG was proposed to record sEMG signals from four electrode arrays over the facial and neck muscles. The high-density sEMG signals were utilized to analyze the effects of the electrode locations on the classification accuracies when increasing the category number of speaking tasks. The results showed that the increase in category numbers of speaking tasks would lead to the decline of classification accuracies, no matter which of the four electrode arrays were used. Meanwhile, the declining rates were the highest when using signals from the face electrodes (F-40ch), while those were the lowest when using the neck electrodes (NO-40ch and NE-40ch). There was no significant difference in the accuracies between the cases of the NO-40ch and NE-40ch electrodes. The findings indicated that the muscles on the neck region might be a more important contributor for automatic silent speech recognition. The study might provide new clues and guidelines for electrode placement when using sEMG for automatic silent speech recognition, which is important to develop a practical communication system for dysphonia.
机译:在需要静音语音的情况下,使用从放置在面部和颈部区域的电极记录的表面肌电信号(sEMG)信号进行自动语音识别是一项有吸引力的技术。对于这项技术,电极位置是语音识别性能的重要因素。但是,尚不清楚电极位置如何影响性能,因此在实际应用中没有关于电极放置的准则。因此,提出了高密度sEMG的方法来记录来自面部和颈部肌肉上的四个电极阵列的sEMG信号。当增加说话任务的类别数量时,高密度sEMG信号用于分析电极位置对分类准确性的影响。结果表明,无论使用四个电极阵列中的哪一个,说话任务类别数量的增加都会导致分类准确性的下降。同时,使用面部电极(F-40ch)的信号下降率最高,而使用颈部电极(NO-40ch和NE-40ch)的下降率最低。 NO-40ch和NE-40ch电极的精度之间没有显着差异。研究结果表明,颈部区域的肌肉可能是自动沉默语音识别的重要贡献者。当使用sEMG进行自动无声语音识别时,这项研究可能会为电极放置提供新的线索和指导方针,这对于开发实用的发音障碍交流系统很重要。

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