Energy-based features and bi-LSTM neural network for EEG-based music and voice classification.
Isaac ArizaAna M. BarbanchoLorenzo J. TardónIsabel BarbanchoPublished in: Neural Comput. Appl. (2024)
Keyphrases
- eeg signals
- feature vectors
- neural network
- classification accuracy
- feature set
- feature extraction
- learning vector quantization
- feature space
- classification method
- classification models
- pattern recognition
- svm classifier
- extracted features
- feature analysis
- classification process
- recurrent neural networks
- extracting features
- feature maps
- image classification
- classification scheme
- class labels
- audio features
- genre classification
- training process
- machine learning
- benchmark datasets
- supervised learning
- classification algorithm
- musical instrument
- probabilistic neural network
- support vector
- artificial neural networks
- low level
- music information retrieval
- support vector machine
- discriminative features
- feature values
- image features
- feature representation
- support vector machine svm
- business intelligence
- feature selection algorithms
- pattern classification
- multi layer perceptron
- signal processing
- self organizing maps
- spectral features
- feature selection
- sleep stage