0.08mm² 128nW MFCC engine for ultra-low power, always-on smart sensing applications

• Main Authors: Chong, Yi Sheng, Goh, Wang Ling, Ong, Yew Soon, Nambiar, Vishnu P., Do, Anh Tuan
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2022
• Subjects: Engineering::Electrical and electronic engineering; Fault Detection; Image Edge Detection
• Online Access: https://hdl.handle.net/10356/159307
• Institution: Nanyang Technological University

Mel frequency cepstral coefficient (MFCC) features are widely used in applications such as keyword spotting, bearing fault detection and heart sound classification. This work proposes a low power MFCC engine that enables its use for battery-powered edge applications. Three hardware algorithm co-opti...