IEEE Access, 2017 Environmental noise and reverberation conditions severely degrade the performance of forensic speaker verification. Robust feature extraction plays an important role in improving forensic speaker verification performance.
Bouchra Senadji +2 more
exaly +3 more sources
Significance of chirp MFCC as a feature in speech and audio applications
Computer Speech and LanguageA novel feature, based on the chirp z-transform, that offers an improved representation of the underlying true spectrum is proposed. This feature, the chirp MFCC, is derived by computing the Mel frequency cepstral coefficients from the chirp magnitude spectrum, instead of the Fourier transform magnitude spectrum.
Johanan Joysingh S
exaly +3 more sources
Learnable MFCCs for Speaker Verification [PDF]
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021 Accepted to ISCAS ...
Xuechen Liu 0001 +2 more
openaire +4 more sources
Comparative Study of different types of RNN in Speech Classification [PDF]
The Egyptian Journal of Language Engineering, 2021 This paper introduces different models for pre-processing classification and their performance in Automatic Speech Recognition system. Different Recurrent Neural Network (RNN) architectures have been tested for this problem, such as RNN cells (RNN ...
Tarek Said, Amr Gody, Ayat Ragheb
doaj +1 more source
Optimizing MFCC parameters for the automatic detection of respiratory diseases
Applied AcousticsVoice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) is widely used for automatic analysis, with MFCC extraction commonly relying on default parameters.
, Visara Urovi, Yuyang Yan
exaly +4 more sources
Speech analysis for the detection of Parkinson’s disease by combined use of empirical mode decomposition, Mel frequency cepstral coefficients, and the K-nearest neighbor classifier [PDF]
ITM Web of Conferences, 2022 Parkinson’s disease (PD) is one of the neurodegenerative diseases. The neuronal loss caused by this disease leads to symptoms such as lack of initiative, depressive states, psychological disorders, and impairment of cognitive functions as well as voice ...
Boualoulou N. +3 more
doaj +1 more source
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.
Zrar Kh. Abdul +1 more
doaj +1 more source
Arabic Speaker Identification System Using Multi Features [PDF]
Engineering and Technology Journal, 2020 The performance regarding the Speaker Identification Systems (SIS) has enhanced because of the current developments in speech processing methods, however, an improvement is still required with regard to text-independent speaker identification in the ...
Rawia Mohammed, Nidaa Hassan, Akbas Ali
doaj +1 more source
Speech Recognition Algorithm in a Noisy Environment Based on Power Normalized Cepstral Coefficient and Modified Weighted-KNN [PDF]
Engineering and Technology Journal, 2023 Speech recognition is widely used in robot control and automation. Nevertheless, the use of speech recognition in robots is limited due to its susceptibility to background noise.
Mohammed Safi, Eyad Abbas
doaj +1 more source
A Novel S-LDA Features for Automatic Emotion Recognition from Speech using 1-D CNN [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2022 Emotions are explicit and serious mental activities, which find expression in speech, body gestures and facial features, etc. Speech is a fast, effective and the most convenient mode of human communication.
Pradeep Tiwari, A. D. Darji
doaj +1 more source