Phase-aware Speech Enhancement with Deep Complex U-Net

Understand

Most deep learning-based models for speech enhancement have mainly focused on estimating the magnitude of spectrogram while reusing the phase from noisy speech for reconstruction.

• This is due to the difficulty of estimating the phase of clean speech.
• To improve speech enhancement performance, we tackle the phase estimation problem in three ways.
• First, we propose Deep Complex U-Net, an advanced U-Net structured model incorporating well-defined complex-valued building blocks to deal with complex-valued spectrograms.