EAGER: Computer Architectures and Algorithms for Adaptive Human Computer Interfaces

人机界面的易用性主要取决于系统的延迟及其适应环境的能力。光照、视觉外观和用户行为的差异会显著改变输入数据。此外，反应时间必须小于100毫秒，才能在用户看来是即时的。要实现高精度，系统需要适应这些变化的特征，同时在短时间内处理大量数据。我们提出了一种自适应实时信号处理系统的计算机体系结构，它将通用处理器与定制硬件相结合。定制硬件对原始信号执行低级、高吞吐量的信号处理，并将其提供给处理器，处理器执行高级信号处理和决策。处理器还执行机器学习算法，改变低级处理的参数，使其适应数据的当前统计属性。该项目将开发基于音频和视频传感器的人机界面，允许用户仅通过手势和语音与计算机交互。这需要在计算机体系结构、嵌入式系统、信号处理、机器学习和人机交互方面取得进展。主要的研究挑战是如何整合不同领域的知识来创建一个功能系统。该系统将作为新型人机交互的原型，并将成为未来不同领域之间合作的基础。

The ease of use of a human computer interface depends critically on the latency of the system and its ability to adapt to the environment. Differences in lighting, visual appearance and user behavior can significantly alter the input data. Furthermore, the reaction time must be less than 100 milliseconds to appear instantaneous to the user. Achieving high accuracy demands a system that adapts to these changing characteristics while processing a significant amount of data in a short amount of time.We propose a computer architecture for adaptive real-time signal processing systems that combines a general purpose processor with custom hardware. The custom hardware performs the low-level, high-throughput signal processing on the raw signals and feeds them to the processor which performs the high level signal processing and decision making. The processor also executes machine learning algorithms that change the parameters of the low-level processing to adapt them to the current statistical properties of the data.This project will develop a human-computer interface based on audio and video sensors that allows a user to interact with the computer through gestures and voice alone. This requires research advances in computer architecture, embedded systems, signal processing, machine learning and human-computer interaction. The major research challenge is in the integration of knowledge from the different areas to create a functional system. This system will serve as a prototype for novel human computer interactions and will be a foundation for future collaboration between the different fields.