Abstract: Everyone goes through periods of mental stress in their daily lives. While small amounts of stress can enhance focus, alertness, and performance, excessive stress negatively affects ...
A research team from Tsinghua University has developed an optical computing system that dramatically reduces latency in feature extraction - one of the most critical stages in real-time data ...
feature_extraction_functions.py: a set of feature extraction functions from RDShi-SpeakerCount. MFCC: Mel-frequency cepstral coefficients calculation. MFCC.py, MFCCTest.py: Compute the MFCC feature.
Despite advancements in technology such as applications like Shazam that can identify music within seconds, the trend mainly applies to well-known instruments. Cultural instruments are virtually ...
pyAudioAnalysis provides easy-to-call wrappers to execute audio analysis tasks. Eg, this code first trains an audio segment classifier, given a set of WAV files stored in folders (each folder ...
Abstract: The Mel-Frequency Cepstral Coefficients (MFCC) feature extraction method is a leading approach for speech feature extraction and current research aims to identify performance enhancements.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results