Biologically inspired speech processing

在过去的四年中，我们成功地开发了生物启发的多麦克风语音处理系统，我们寻求进一步开发生物启发的语音定位，增强和识别系统。我们的最终目标是开发自动语音识别系统，可以可靠地理解人类说话者的口语，并在实际条件下。虽然人类可以相对容易地执行这种语音识别，但在计算机硬件中模仿这种能力一直是一个难以捉摸的目标。 当今的语音识别系统在存在噪声和混响的情况下是不可靠的，使得它们在蜂窝电话、手持计算机和汽车中的实际应用是不可能的。因此，我们要问的基本问题是：是什么生物学过程使到达耳朵的声波能够被正确识别，即使在存在噪音的情况下？在回答这个问题时，我们的两个主要目标是1）研究生物声音处理系统（从昆虫到人类），以及2）在电子硬件中复制这些过程。第二个目标也需要进一步研究和认真执行。在我们以前开发的双麦克风人工语音处理系统中，我们发现标准的计算机处理器在计算能力和整体设计效率方面是不够的。因此，我们利用定制设计的硬件实现以及可重新配置的硬件来开发新的优化处理结构。关于我们的第二个目标，一个类似的实施研究，探索自定义硬件实施方案以及可重构硬件，将进行。最后，我们寻求开发实时和可靠的语音处理系统，可以显着改变人类与计算机交互和通信的方式。

Having successfully developed biologically-inspired multi-microphone speech processing systems in the past four years, we seek to further develop biologically inspired speech localization, enhancement, and recognition systems. Our ultimate goal is to develop automatic speech recognition systems that can understand the spoken words of a human speaker reliably and in practical conditions. While humans can perform such speech recognition with relative ease, mimicking this capability in computer hardware has been an elusive goal.   Today's speech recognition systems are unreliable in the presence of noise and reverberations, making their practical utilization on cell phones, hand held computers, and in cars impossible. Consequently, the fundamental question to ask is: what are the biological processes that allow sound waves arriving at the ears to be correctly recognized, even in the presence of noise? In answering this question, our primary two goals are 1) to study biological sound processing systems (from those of insects to those of humans), and 2) to replicate these processes in electronic hardware. The second goal also requires further study and a careful implementation. In our previous development of a dual-microphone artificial speech processing system, we found that standard computer processors were inadequate in terms of computational power and overall design effectiveness. As a result, we utilized custom-designed hardware implementations as well as reconfigurable hardware to develop new optimized processing structures. Regarding our second goal, a similar implementation study, exploring both custom hardware implementation options as well as reconfigurable hardware, will be conducted. In the end, we seek to develop real-time and reliable speech processing systems that can significantly alter how humans interact and communicate with computers.