A Low-Power Keyword Spotting Chip with Multiplier-Free MFCC Feature Extractor

被引:0
作者
Yang, Jingsen [1 ]
机构
[1] Fudan Univ, Inst Brain Inspired Circuits & Syst, State Key Lab Integrated Chips & Syst, Shanghai 201203, Peoples R China
基金
中国国家自然科学基金;
关键词
Fast Fourier transform (FFT); keyword spotting (KWS); Mel Frequency Cepstral Coefficients (MFCC); neural network (NN); DESIGN; AMPLIFIER;
D O I
10.1587/elex.22.20250008
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Mel-frequency cepstral coefficients (MFCC), an FFT-based speech feature extraction (FEx) algorithm, is a significant power con sumer in low-power keyword spotting (KWS) chips. This work presents KWS chip with an energy-efficient FEx, with an expanded-3bit-twiddle FFT (E3bT-FFT) algorithm which reduces power of FFT by 5.7x. Meanwhile, a multiplier-free MFCC (MF-MFCC) is proposed, effectively eliminating power-hungry multipliers and reducing the MFCC computational load 7.3x. Fabricated in a 65-nm CMOS process, the chip occupies 0.17 mm(2) and consumes 2.3 mu W, with the computation unit in FEx consuming just 76 nW, and achieves 94.9% accuracy on a 1-Word KWS with Google Speech Commands dataset (GSCD).
引用
收藏
页数:7
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