Mel frequency cepstral coefficient and its applications: A review

ZK Abdul, AK Al-Talabani - IEEE Access, 2022 - ieeexplore.ieee.org
Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

A survey of speaker recognition: Fundamental theories, recognition methods and opportunities

MM Kabir, MF Mridha, J Shin, I Jahan, AQ Ohi - IEEE Access, 2021 - ieeexplore.ieee.org
Humans can identify a speaker by listening to their voice, over the telephone, or on any
digital devices. Acquiring this congenital human competency, authentication technologies …

Generating holistic 3d human motion from speech

H Yi, H Liang, Y Liu, Q Cao, Y Wen… - Proceedings of the …, 2023 - openaccess.thecvf.com
This work addresses the problem of generating 3D holistic body motions from human
speech. Given a speech recording, we synthesize sequences of 3D body poses, hand …

Trends in audio signal feature extraction methods

G Sharma, K Umapathy, S Krishnan - Applied Acoustics, 2020 - Elsevier
Audio signal processing algorithms generally involves analysis of signal, extracting its
properties, predicting its behaviour, recognizing if any pattern is present in the signal, and …

[HTML][HTML] Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: cough, voice, and …

KK Lella, A Pja - Alexandria Engineering Journal, 2022 - Elsevier
The problem of respiratory sound classification has received good attention from the clinical
scientists and medical researcher's community in the last year to the diagnosis of COVID-19 …

Backdoor attack against speaker verification

T Zhai, Y Li, Z Zhang, B Wu, Y Jiang… - ICASSP 2021-2021 …, 2021 - ieeexplore.ieee.org
Speaker verification has been widely and successfully adopted in many mission-critical
areas for user identification. The training of speaker verification requires a large amount of …

One-class support vector classifiers: A survey

S Alam, SK Sonbhadra, S Agarwal… - Knowledge-Based …, 2020 - Elsevier
Over the past two decades, one-class classification (OCC) becomes very popular due to its
diversified applicability in data mining and pattern recognition problems. Concerning to …

Lung sound classification using cepstral-based statistical features

N Sengupta, M Sahidullah, G Saha - Computers in biology and medicine, 2016 - Elsevier
Lung sounds convey useful information related to pulmonary pathology. In this paper, short-
term spectral characteristics of lung sounds are studied to characterize the lung sounds for …

A digital liquid state machine with biologically inspired learning and its application to speech recognition

Y Zhang, P Li, Y Jin, Y Choe - IEEE transactions on neural …, 2015 - ieeexplore.ieee.org
This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-
large-scale-integration (VLSI)-based machine learning applications. To the best of the …

[HTML][HTML] Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough …

KK Lella, A Pja - AIMS public health, 2021 - ncbi.nlm.nih.gov
The issue in respiratory sound classification has attained good attention from the clinical
scientists and medical researcher's group in the last year to diagnosing COVID-19 disease …