Department of Communications Engineering University of Paderborn

Repositories

• padertorch

  A collection of common functionality to simplify the design, training and evaluation of machine learning models based on pytorch with an emphasis on speech processing.

  audio speech pytorch
  Python MIT 6 11 0 0 Updated May 20, 2020

• paderbox

  Paderbox: A collection of utilities for audio / speech processing

  audio speech toolbox
  Python MIT 5 11 0 0 Updated May 20, 2020

• pb_chime5

  Speech enhancement system for the CHiME-5 dinner party scenario
  Python MIT 20 58 0 0 Updated May 20, 2020

• nara_wpe

  Different implementations of "Weighted Prediction Error" for speech dereverberation

  audio signal-processing enhancement audio-processing dereverberation
  Python MIT 93 179 6 1 Updated May 6, 2020

• python_crashkurs
  Jupyter Notebook 0 1 0 0 Updated May 5, 2020

• lazy_dataset

  lazy_dataset: Process large datasets as if it was an iterable.
  Python MIT 5 6 3 1 Updated Mar 24, 2020

• sms_wsj

  SMS-WSJ: Spatialized Multi-Speaker Wall Street Journal database for multi-channel source separation and recognition
  Python MIT 8 35 1 0 Updated Mar 3, 2020

• upb_audio_tagging_2019

  UPB system for the Kaggle competition "Freesound Audio Tagging 2019"
  Python MIT 1 1 0 0 Updated Feb 18, 2020

• sins
  Python MIT 0 4 0 0 Updated Feb 18, 2020

• pb_bss

  Collection of EM algorithms for blind source separation of audio signals

  multi-channel speech-processing bss em-algorithm source-separation beamforming speech-enhancement
  Python MIT 27 93 1 0 Updated Feb 11, 2020

• dlp_mpi
  Python 2 2 0 0 Updated Dec 8, 2019

• 2019_ad_xidian
  HTML 0 0 0 0 Updated Aug 22, 2019

• pb_test_data

  Example audio signals to test our repositories
  1 0 0 0 Updated Aug 5, 2019

• python_crashkurs_doc
  0 0 0 0 Updated Apr 18, 2019

• nn-gev

  Neural network supported GEV beamformer
  Python 69 97 5 0 Updated Feb 19, 2018

• nachrichtentechnik

  Jupyter noteboooks for the lecture "Nachrichtentechnik" (communications engineering) with explanations in german.
  Jupyter Notebook 0 2 0 0 Updated Oct 16, 2017

• oaf

  Jupyter notebooks for the lecture "Optimal and adaptive filters"
  Jupyter Notebook 4 3 0 0 Updated Mar 18, 2017

• LatticeWordSegmentation

  Software to apply unsupervised word segmentation on lattices or text sequences using a nested hierarchical Pitman Yor language model
  C++ 9 16 0 0 Updated Nov 24, 2016

• nhpylm

  Python bindings for a c++ based implementation of the Nested Hierarchical Pitman-Yor Language model
  C++ 5 12 0 0 Updated Nov 24, 2016

• chainer

  Forked from chainer/chainer

  A flexible framework of neural networks for deep learning
  Python MIT 1,365 0 0 0 Updated Nov 10, 2016

• sacred

  Forked from IDSIA/sacred

  Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
  Python MIT 295 0 0 0 Updated Jul 5, 2016