Results 31 to 40 of about 3,633,480 (246)
Mel Frequency Cepstral Coefficient and its Applications: A Review
IEEE Access, 2022 Feature extraction and representation has significant impact on the performance of any machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to model features of audio signal and is widely used in various fields. This paper aims to review the applications that the MFCC is used for in addition to some issues that facing the MFCC
Zrar Kh. Abdul +1 more
openaire +3 more sources
Scientific African, 2021 Amyotrophic Lateral Sclerosis (ALS) and Myopathy are the most well-known neuromuscular diseases. Electromyography (EMG) signal is hugely used in the diagnosis of these neuromuscular disorders.
Abdelali Belkhou +2 more
doaj +1 more source
Linear versus mel frequency cepstral coefficients for speaker recognition [PDF]
2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011 Mel-frequency cepstral coefficients (MFCC) have been dominantly used in speaker recognition as well as in speech recognition. However, based on theories in speech production, some speaker characteristics associated with the structure of the vocal tract, particularly the vocal tract length, are reflected more in the high frequency range of speech.
Xinhui Zhou +4 more
openaire +2 more sources
Jurnal Engineering, 2021 Speech-related research has a wide range of applications. Most speech-related researches employ Mel-frequency cepstral coefficients (MFCCs) as acoustic features. However, finding the optimum number of MFCCs is an active research question. MFCC-based speech
Md Rakibul Hasan +2 more
semanticscholar +1 more source
Regional language Speech Emotion Detection using Deep Neural Network [PDF]
ITM Web of Conferences, 2022 Speaking is the most basic and efficient mode of human contact. Emotions assist people in communicating and understanding others’ viewpoints by transmitting sentiments and providing feedback.The basic objective of speech emotion recognition is to enable ...
Padman Sweta, Magare Dhiraj
doaj +1 more source
Speech-based gender recognition using linear prediction and mel-frequency cepstral coefficients
Indonesian Journal of Electrical Engineering and Computer Science, 2022 Gender discrimination and awareness are essentially practiced in social, education, workplace, and economic sectors across the globe. A person manifests this attribute naturally in gait, body gesture, facial, including speech.
Yusnita Mohd Ali +5 more
semanticscholar +1 more source
Application of Teager Energy Operator on Linear and Mel Scales for Whispered Speech Recognition
Archives of Acoustics, 2018 This paper presents experimental results on whispered speech recognition based on Teager Energy Operator for linear and mel cepstral coefficients including the Cepstral Mean Subtraction normalization technique.
Branko R MARKOVIĆ +2 more
doaj +1 more source
Classifying Heart-Sound Signals Based on CNN Trained on MelSpectrum and Log-MelSpectrum Features
Bioengineering, 2023 The intelligent classification of heart-sound signals can assist clinicians in the rapid diagnosis of cardiovascular diseases. Mel-frequency cepstral coefficients (MelSpectrums) and log Mel-frequency cepstral coefficients (Log-MelSpectrums) based on a ...
Wei Chen +8 more
doaj +1 more source
Feature extraction method for reflective sound signal of high pressure water-jet target
Gong-kuang zidonghua, 2014 In order to improve recognition rate of target materials by using reflective sound signal of high pressure water-jet, in view of four common targets of mine, stone, brick and wood block, different feature extraction methods were used to identify target ...
SUN Shuai +4 more
doaj +1 more source
IEEE Access, 2022 Arc faults pose challenges to electric safety, which can cause serious fire hazards. However, the commonly used arc fault detection method is prone to nuisance tripping.
Yao Wang +5 more
semanticscholar +1 more source