Deep learning

• Developing deep learning algorithms for various signal processing, including speech and brain signal.

Speech processing

• Text-to-speech (TTS) synthesis
  • Developing neural vocoder using domain-specific knowledge.
  • Developing TTS system based on deep learning algorithms used in natural language processing (NLP).
• Speech enhancement using deep learning
  • Developing noise-robust speech enhancement method based on neural vocoders.
  • Developing neural networks based on domain-specific knowledge for speech enhancement to reduce model complexity.
• Audio-video speech enhancement (AVSE)
  • Developing speech enhancement method using features extracted from video.

Brain Computer Interface

• Analysis for brain signal
  • Developing deep learning based feature extraction algorithms for electroencephalograms (EEG) to improve performance of BCI system.
• Motor imagery classification
  • Developing deep learning/machine learning algorithms for improving classification accuracy.
• Sleep stage classification
  • Developing neural networks for sleep stage classification.
  • Developing neural encoder based on attention mechanism to capture features represented on EEG waves.