Design and Fabrication of Neural Networks for Signal Processing Recognition

在之前的工作中，P.I.已经开发并测试了一个详细的定量模型，用于研究哺乳动物耳蜗如何处理语音信息。他研究了这些信息经过处理后是如何与人类识别的语音相匹配的。在这个项目中，P.I.将继续应用各种学习算法来处理人类语音，从而展示这种处理在语音识别应用中的价值。将探索利用速度数据的真实序列性质的创新学习算法，以及更多临床生物学驱动的学习规则。

In prior work, the P.I. has developed and tested a detailed quantitative model of how speech information is processed in the cochlea of mammals. He has studied how this information, after processing, is allocated with speech sounds, as recognized by humans. In this project, the P.I. will go on to apply various learning algorithms to processed human speech, so as to demonstrate the value of this processing in speech recognition applications. Innovative learning algorithms exploiting the true series nature of speed data will be explored, along with more clinical biologically-motivated learning rules.