论文标题
A 23 $μ$ W关键字与基于环振荡器的时间域特征提取的关键字发现IC
A 23 $μ$W Keyword Spotting IC with Ring-Oscillator-Based Time-Domain Feature Extraction
论文作者
论文摘要
本文介绍了第一个关键字发现（KWS）IC，该IC使用基于环振荡器的时间域处理技术为其模拟特征提取器（FEX）。其广泛使用时间编码方案的使用允许模拟音频信号以完全时域的方式处理，除了模拟前端的电压到时间转换阶段。与常规电压域设计相比，它得益于基于数字逻辑门的基本构建块，它提供了更好的技术可伸缩性。原型KWS IC在65 nm CMOS过程中制造，占2.03mm $^{2} $，并消散23 $μ$ W功耗，包括模拟FEX和数字神经网络分类器。 16通道的时间域FEX达到54.89 DB动态范围，以16毫秒的帧换档尺寸，而消耗9.3 $μ$ w。测量结果验证了所提出的IC在Google Speech命令数据集（GSCD）上执行12级KWS任务，其精度> 86％，延迟12.4 ms。
This article presents the first keyword spotting (KWS) IC which uses a ring-oscillator-based time-domain processing technique for its analog feature extractor (FEx). Its extensive usage of time-encoding schemes allows the analog audio signal to be processed in a fully time-domain manner except for the voltage-to-time conversion stage of the analog front-end. Benefiting from fundamental building blocks based on digital logic gates, it offers a better technology scalability compared to conventional voltage-domain designs. Fabricated in a 65 nm CMOS process, the prototyped KWS IC occupies 2.03mm$^{2}$ and dissipates 23 $μ$W power consumption including analog FEx and digital neural network classifier. The 16-channel time-domain FEx achieves 54.89 dB dynamic range for 16 ms frame shift size while consuming 9.3 $μ$W. The measurement result verifies that the proposed IC performs a 12-class KWS task on the Google Speech Command Dataset (GSCD) with >86% accuracy and 12.4 ms latency.
