Adaptive Blowing Interaction Method Based on a Siamese Network

Adaptive Blowing Interaction Method Based on a Siamese Network
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基于连体网络的自适应吹气交互方法

DOI:
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发表时间:
2020
期刊:
影响因子:
3.9
通讯作者:
Chenglei Yang
Chenglei Yang
中科院分区:
计算机科学3区
文献类型:
--
作者:
Yeqing Chen;Yulong Bian;Wei Gai;Chenglei Yang

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呼吸是一种自然的、可直接控制的人类活动。目前,一些研究认为呼吸是一种直接的输入控制机制。在这些工作中所依赖的设备通常是复杂的,昂贵的,不方便穿着,有时也不足以控制。呼吸交互的使用也仅限于某个场景,并不普遍。本文提出了一种自适应交互方法,该方法是一种自然的、直接可控的基于吹气的交互,只需要使用耳机麦克风就可以获得吹气动作的声音波形,不需要昂贵的设备,可以方便地随时随地使用。这种吹气交互采用连体网络实现“自适应”--第一步适应噪音干扰,包括环境噪音和用户自身说话干扰,第二步适应不同的用户和设备,即吹气交互被不同的人使用或在不同的设备上使用,交互方式可以准确识别吹气的类型。本文还开发了几个应用程序的吹相互作用方法来测试算法。经过测试证明,该接口不仅增加了用于交互的吹气类型,而且有效地消除了正常音量说话的干扰,解决了个体差异问题。
Breathing is a natural and directly controllable human activity. Currently, some works have considered breath as a direct input controlling mechanism. The equipment relied upon in these works is generally complicated, expensive, inconvenient to wear, and sometimes insufficiently controllable. The use of breathing interaction is also limited to a certain scene and is not universal. This paper proposes an adaptive interaction method, which is a natural and directly controllable interaction based on blowing air that only uses headset microphones to obtain the sound waveform of the blowing action without requiring expensive equipment, and that can be used conveniently anytime and anywhere. This blowing interaction uses a Siamese network to achieve “self-adaptation” - the first step adapts to noise interference, including environmental noise and the user’s own speaking interference, and the second step adapts to different users and equipment, that is, the blowing interaction is used by different people or on different equipment, and the interaction mode can accurately identify the type of blowing. This paper also develops several applications of the blowing interaction method to test the algorithm. During tests, it’s proved that this interface not only increases the type of blowing used for interaction but also eliminates interference from speaking in a normal volume effectively and addresses the problem of individual differences.
使用 LPC 和受限玻尔兹曼机检测呼吸频率和呼吸深度
DOI: --
发表时间: 2019
影响因子: 5.1
作者:
Hamke, E.;Martinez-Ramon, M.;Raeschi, A.;Jordan, R.
通讯作者: Jordan, R.