HIGHLIGHTS
- who: QIN LI and colleagues from the of Electronic Engineering, Tsinghua University, China have published the research: MSP-MFCC: Energy-Efficient MFCC Feature Extraction Method With Mixed-Signal Processing Architecture for Wearable Speech Recognition Applications, in the Journal: (JOURNAL)
- what: The authors propose a Mixed-Signal Processing (MSP) architecture to efficiently extract Mel-Frequency Cepstrum Coefficients (MFCC) features. The authors design MSP-MFCC to pre-process speech signals in the analog domain which significantly reduces the cost of the analog-to-digital converter (ADC) as well as the computational complexity of the digital backend. The . . .
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