Project

Hybrid solutions for the one-microphone speech enhancement problem

Duration
01 January 2019 → Ongoing
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Artificial intelligence
  • Social sciences
    • Cognitive science and intelligent systems
  • Engineering and technology
    • Communications
    • Communications technology
    • Modelling
    • Biological system engineering
    • Signal processing
Keywords
Speech enhancement noise suppression knowledge-based approaches machine learning statistical speech enhancement
 
Project description

Incorporating (hand-crafted) structured models into traditional speech enhancement approaches gives an improvement, albeit constrained by the model's limitations. Alternatively, employing deep neural networks (DNNs) leads to better performance for conditions seen during training. However,
these methods generalise poorly. We propose to systematically incorporate structured knowledge into DNNs, thereby combining significantly improved speech enhancement with greater robustness to unseen conditions.