Results 111 to 120 of about 10,198 (208)

MFCC global features selection in improving speech emotion recognition rate

, 2015
Feature selection is one of the important aspects that contribute most to the emotion recognition system performance as well as the database and the classification technique used.
Salam, Md. Sah, Zaidan, Noor Aina
core  

Dual-branch hierarchical fusion network for voice-based classification of type 2 diabetes mellitus using multi-vowel acoustic features. [PDF]

Front Med Technol
Jiang P, Zhang W, Li A, Li P.
europepmc   +1 more source

Predicting competitive outcomes in professional e-sports from 60-second pre-match voice acoustics using machine learning. [PDF]

Front Psychol
Kadri G, Santos RIM, Aguiar FO, Otani VHO, Uchida RR, Marques LM.   +5 more
europepmc   +1 more source

Music Instrument Identification Using MFCC: Erhu as an Example

, 2012
[[abstract]]In the analysis of musical acoustics, we usually use the power spectrum to describe the difference between timbres from two music instruments.
Chih-Wen Weng;Cheng-Yuan Lin;Jyh-Shing Roger Jang
core  

Tumor microenvironment responsive nano-immunoregulator for precision cancer photodynamic immunotherapy. [PDF]

Mater Today Bio
Chang X, Yu M, Wei P, Cheng J, Wu Y.
europepmc   +1 more source

Spatial-Temporal Relation Enhancement for Speech Emotion Recognition from Acoustic Signals Using Fibonacci Encoding with Diverse Feature Fusion. [PDF]

Sensors (Basel)
Huang S, Zhang J, Xu J, Zhang Q, Li Z, Wang S, Qiu Z, Xiong Z, Liang J, Fu C.   +9 more
europepmc   +1 more source

ForNet: classification of critical forest acoustic events using discriminative CNN representations and ensemble learning. [PDF]

Sci Rep
Krishnamoorthy D, Sai VS, Vishal R, Benezeth Y.   +3 more
europepmc   +1 more source

Multi-QuadEmoNet: cat and dog emotion classification model from animal vocalization using multi-stage LSTM-GRU paradigm. [PDF]

Front Vet Sci
Pearline SSRA, Subbiah G, Sanu A, Charumathi Venkatesan K.   +3 more
europepmc   +1 more source

Longitudinal voice biomarker trajectory modelling for Parkinson's disease severity: domain-adaptive transfer learning on mPower real-world smartphone data. [PDF]

Front Digit Health
Johnson DR, Logeswari G.
europepmc   +1 more source

EEG-based harmful brain activity classification using deep learning and feature fusion. [PDF]

Sci Rep
Unnisa Z, Jaffar A, Akram S, Din I, Khan K, Masood Bhatti S.   +5 more
europepmc   +1 more source