Variational mode decomposition based acoustic and entropy features for speech emotion recognition
Automated speech emotion recognition (SER) is a machine-based method for identifying
emotion from speech signals. SER has many practical applications, including improving …
emotion from speech signals. SER has many practical applications, including improving …
Parkinson's detection based on combined CNN and LSTM using enhanced speech signals with variational mode decomposition
Parkinson's disease (PD) can cause many non-motor and motor symptoms such as speech
and smell. One of the difficulties that Parkinson's patients can experience is a change in …
and smell. One of the difficulties that Parkinson's patients can experience is a change in …
Time-frequency analysis of speech signal using Chirplet transform for automatic diagnosis of Parkinson's disease
Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder in the
world after Alzheimer's disease. Early diagnosing PD is challenging as it evolved slowly …
world after Alzheimer's disease. Early diagnosing PD is challenging as it evolved slowly …
Sinusoidal model-based diagnosis of the common cold from the speech signal
Background and objective: Develo** speech signal-based non-invasive diagnosis
techniques is an emerging research field in biomedical signal processing. Detecting the …
techniques is an emerging research field in biomedical signal processing. Detecting the …
Chirplet transform based time frequency analysis of speech signal for automated speech emotion recognition
Nowadays, the recognition of emotion using the speech signal has gained popularity
because of its vast number of applications in different fields like medicine, online marketing …
because of its vast number of applications in different fields like medicine, online marketing …
Speech emotion recognition using mfcc-based entropy feature
The prime objective of speech emotion recognition is to accurately recognize the emotion
from the speech signal. It is a challenging task to accomplish. Speech emotion recognition …
from the speech signal. It is a challenging task to accomplish. Speech emotion recognition …
Detection of common cold from speech signals using deep neural network
This paper presents a deep learning-based analysis and classification of cold speech
observed when a person is diagnosed with the common cold. The common cold is a viral …
observed when a person is diagnosed with the common cold. The common cold is a viral …
An improved framework for Parkinson's disease prediction using Variational Mode Decomposition-Hilbert spectrum of speech signal
Parkinson's disease (PD) is a neuro-degenerative disease due to loss of brain cells, which
produces dopamine. It is most common after Alzheimer's disease specially seen in old age …
produces dopamine. It is most common after Alzheimer's disease specially seen in old age …
Significance of voiced and unvoiced speech segments for the detection of common cold
This work investigates the significance of the voiced and unvoiced region for detecting
common cold from the speech signal. In literature, the entire speech signal is processed to …
common cold from the speech signal. In literature, the entire speech signal is processed to …
Dysfluent Speech Classification Using Variational Mode Decomposition and Complete Ensemble Empirical Mode Decomposition Techniques with NGCU based RNN
Dysfluency refers to discontinuity in speech due to noise or speech disorder, this dysfluency
has unique features in terms of pitch and time based on these characteristics the dysfluent …
has unique features in terms of pitch and time based on these characteristics the dysfluent …