Feb 5, 2021 · We propose Tiny Recurrent U-Net (TRU-Net), a lightweight online inference model that matches the performance of current state-of-the-art models.

Tiny Recurrent U-Net (TRU-Net) is a lightweight online inference model that matches the performance of current (23 Jun 2021) state-of-the-art models.

To this end, we propose Tiny Recurrent U-Net (TRU-Net), a lightweight online inference model that matches the performance of current state-of- the-art models.

REAL-TIME DENOISING AND DEREVERBERATION WTIH TINY RECURRENT U-NET. Raw. trunet.py. import torch. from torch.nn import *. def pointwise(in_channels, out_channels):.

Tiny Recurrent U-Net (TRU-Net), a lightweight online inference model that matches the performance of current state-of- the-art models on benchmark datasets ...

Modern deep learning-based models have seen outstanding performance improvement with speech enhancement tasks. The number of parameters of state-of-the-art ...

The prevalent approach involves supervised learning, which employs a mixture of clean speech and background noise as the training set and clean speech as ...

Feb 5, 2021 · To this end, we propose Tiny Recurrent U-Net (TRU-Net), a lightweight online inference model that matches the performance of current state-of- ...

Real-time Denoising and Dereverberation with Tiny Recurrent U-Net ... Modern deep learning-based models have seen outstanding performance improvement with speech ...

Real-time denoising and dereverberation wtih tiny recurrent u-net. HS Choi, S ... 2020. Phase-aware single-stage speech denoising and dereverberation with u-net.