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Toward multimodal human-computer interface

机译：迈向多模式人机界面

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Recent advances in various signal processing technologies, coupled with an explosion in the available computing power, have given rise to a number of novel human-computer interaction (HCI) modalities: speech, vision-based gesture recognition, eye tracking, electroencephalograph, etc. Successful embodiment of these modalities into an interface has the potential of easing the HCI bottleneck that has become noticeable with the advances in computing and communication. It has also become increasingly evident that the difficulties encountered in the analysis and interpretation of individual sensing modalities may be overcome by integrating them into a multimodal human-computer interface. We examine several promising directions toward achieving multimodal HCI. We consider some of the emerging novel input modalities for HCI and the fundamental issues in integrating them at various levels, from early signal level to intermediate feature level to late decision level. We discuss the different computational approaches that may be applied at the different levels of modality integration. We also briefly review several demonstrated multimodal HCI systems and applications. Despite all the recent developments, it is clear that further research is needed for interpreting and fitting multiple sensing modalities in the context of HCI. This research can benefit from many disparate fields of study that increase our understanding of the different human communication modalities and their potential role in HCI.
机译：各种信号处理技术的最新进展，加上可用计算能力的迅猛发展，已经带来了许多新颖的人机交互（HCI）模式：语音，基于视觉的手势识别，眼睛跟踪，脑电图仪等。将这些模式成功地实现为接口具有缓解HCI瓶颈的潜力，随着计算和通信的发展，该瓶颈已变得显而易见。越来越明显的是，通过将它们集成到多模式人机界面中，可以克服在分析和解释单个传感模式时遇到的困难。我们研究了实现多模式HCI的几个有希望的方向。我们考虑了一些新兴的人机交互输入方式，以及在从早期信号级别到中间特征级别到后期决策级别各个级别集成它们的基本问题。我们讨论了可用于模式集成的不同级别的不同计算方法。我们还简要回顾了几种已证明的多模式HCI系统和应用。尽管有最近的所有进展，但很明显，在人机交互的背景下，需要进一步的研究来解释和拟合多种传感方式。这项研究可以受益于许多不同的研究领域，这些领域可以增进我们对不同的人类交流方式及其在人机交互中的潜在作用的理解。

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