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Name: Nils L. Westhausen
Type: User
Bio: PhD candidate at the Communication Acoustics group at the University of Oldenburg. Working on speech enhancement and separation.
Location: Oldenburg
Name: Nils L. Westhausen
Type: User
Bio: PhD candidate at the Communication Acoustics group at the University of Oldenburg. Working on speech enhancement and separation.
Location: Oldenburg
Function to implement a power complementary filter bank. The filter bank is based on the paper: "Complementary N-Band IIR Filterbank Based on 2-Band Complementary Filters" written by Alexis Favrot and Christof Faller (2010)
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
This repo contains the scripts, models and required files for the Interspeech 2020 Deep Noise Suppression (DNS) Challenge. We are open sourcing clean speech and noise files as well. Participants of this challenge will use the scripts from this repo to create data to train their noise suppressors. They will compare their method with our baseline noise suppressor and report the results.
Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.
This Repostory contains the pretrained DTLN-aec model for real-time acoustic echo cancellation.
An open source dataset for source separation
A Code Style Checker and Analyzer for Matlab Code
Implementation of a wavread and wavwrite with audioread and audiowrite to replace the old MATLAB functions, which were removed in MATLAB R2015b.
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
SMS-WSJ: Spatialized Multi-Speaker Wall Street Journal database for multi-channel source separation and recognition
A wrapper around speech quality metrics MOSNet, BSSEval, STOI, PESQ, SRMR, SISDR
This repository contains the trained models and some audio samples for the tPLCnet.
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