MSP-MFCC: Energy-Efficient MFCC Feature Extraction Method With Mixed-Signal Processing Architecture for Wearable Speech Recognition Applications

MSP-MFCC: Energy-Efficient MFCC Feature Extraction Method With Mixed-Signal Processing Architecture for Wearable Speech Recognition Applications

Feature extraction is an essential part of automatic speech recognition (ASR) to compress raw speech data and enhance features, where conventional implementation methods based on the digital domain have encountered energy consumption and processing speed bottlenecks. Thus, we propose a Mixed-Signal...

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Bibliographic Details
Main Authors: Qin Li, Yuze Yang, Tianxiang Lan, Huifeng Zhu, Qi Wei, Fei Qiao, Xinjun Liu, Huazhong Yang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Mixed signal processing architecture
energy-efficient feature extraction
mel-frequency cepstrum coefficients (MFCC)
wearable speech recognition application
Online Access:https://ieeexplore.ieee.org/document/9031431/

Internet

https://ieeexplore.ieee.org/document/9031431/

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