IEEE

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

Abstract: 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 ...
IEEE

Energy-Efficient Floating-Point MFCC Extraction Architecture for Speech Recognition Systems

Abstract: This brief presents an energy-efficient architecture to extract mel-frequency cepstrum coefficients (MFCCs) for real-time speech recognition systems. Based on the algorithmic property of ...
GitHub

rasbt/python-machine-learning-book-3rd-edition

Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive ...
GitHub

Mel Frequency Cepstral Coefficient computation in C++

This C++ software computes MFCCs of a non segmented vector signal. Segmentation should be previouslly applied. This software uses OMP. You can deactivate OMP by commenting line #59 in /include/myFCC.h ...