Optimized cross-corpus speech emotion recognition framework based on normalized 1D convolutional neural network with data augmentation and feature selection

This publication has 33 references indexed in Scilit:

• Attentive Convolutional Neural Network Based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech
  2017
• Evaluating deep learning architectures for Speech Emotion Recognition
  Neural Networks, 2017
• A first look into a Convolutional Neural Network for speech emotion detection
  2017
• Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network
  2016
• Knowledge-based Framework for Intelligent Emotion Recognition in Spontaneous Speech
  Procedia Computer Science, 2016
• Convolutional Neural Networks for Speech Recognition
  IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2014
• Deep neural networks for acoustic emotion recognition: Raising the benchmarks
  2011
• Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies
  IEEE Transactions on Affective Computing, 2010
• Emotion recognition in human-computer interaction
  IEEE Signal Processing Magazine, 2001
• A new inverse-filtering technique for deriving the glottal air flow waveform during voicing
  The Journal of the Acoustical Society of America, 1973