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Hands-free device control using sound picked up in the ear canal

机译:使用耳道中拾取的声音进行免提设备控制

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Hands-free control of unmanned ground vehicles is essential for soldiers, bomb disposal squads, and first responders. Having their hands free for other equipment and tasks allows them to be safer and more mobile. Currently, the most successful hands-free control devices are speech-command based. However, these devices use external microphones, and in field environments, e.g., war zones and fire sites, their performance suffers because of loud ambient noise: typically above 90dBA. This paper describes the development of technology using the ear as an output source that can provide excellent command recognition accuracy even in noisy environments. Instead of picking up speech radiating from the mouth, this technology detects speech transmitted internally through the ear canal. Discreet tongue movements also create air pressure changes within the ear canal, and can be used for stealth control. A patented earpiece was developed with a microphone pointed into the ear canal that captures these signals generated by tongue movements and speech. The signals are transmitted from the earpiece to an Ultra-Mobile Personal Computer (UMPC) through a wired connection. The UMPC processes the signals and utilizes them for device control. The processing can include command recognition, ambient noise cancellation, acoustic echo cancellation, and speech equalization. Successful control of an iRobot PackBot has been demonstrated with both speech (13 discrete commands) and tongue (5 discrete commands) signals. In preliminary tests, command recognition accuracy was 95% with speech control and 85% with tongue control.
机译:对士兵,炸弹处理小组和急救人员而言,无人驾驶地面车辆的免提控制至关重要。将他们的手放到其他设备和任务上可以使他们更安全,更灵活。当前,最成功的免提控制设备是基于语音命令的。但是,这些设备使用外部麦克风,并且在野外环境(例如战区和火场)中,由于嘈杂的环境噪声(通常高于90dBA),其性能会受到影响。本文介绍了使用耳朵作为输出源的技术的发展,该技术即使在嘈杂的环境中也可以提供出色的命令识别精度。这项技术无需捡拾从嘴里发出的语音,而是检测内部通过耳道传输的语音。谨慎的舌头运动还会在耳道内造成气压变化,并可用于隐形控制。开发了一种获得专利的听筒,其麦克风指向耳道,可以捕获由舌头运动和语音产生的这些信号。信号通过有线连接从听筒传输到超便携式个人计算机(UMPC)。 UMPC处理信号并将其用于设备控制。该处理可以包括命令识别,环境噪声消除,声学回声消除和语音均衡。已通过语音(13个离散命令)和舌头(5个离散命令)信号演示了iRobot PackBot的成功控制。在初步测试中,语音控制的命令识别准确率为95%,舌头控制的准确率为85%。

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