Awsome links

This is a collection of my favorite courses, tutorials, demos, articles, lectures, datasets and code repositories on speech processing, machine learning, probability theory and other cool stuff ..

Speech processing 

  • ASR course, University of Edinburgh [PDF lectures] / [Labs (Kaldi)]
  • Kaldi Tutorial, Eleanor Chodroff [Link]
  • Group NMF with speaker and session similarity constraints (Python) [Github repo]
  • Speaker diarization (Python) [Github repo]
  • Building a speaker verification system using SideKit (Python) [Link]
  • Acoustic data augmentation : pitch shift, signals mixing, time stretching, trimming, .. (Python) [Github repo]
  • Acoustic data augmentation (Kaldi) [Github repo]

Acoustic scene analysis & MIR

Machine learning & computer vision

  • 4 Reasons Your Machine Learning Model is Wrong (and How to Fix It) [Link]
  • Sparse coding: A simple exploration [Link]
  • Tips for Training Recurrent Neural Networks [Link]
  • Deep Learning for Image Recognition: why it’s challenging, where we’ve been, and what’s next [Link]
  • The master algorithm, Pedro Domingos : [Youtube video]
  • Upscaling Images with Neural Networks, Geoffrey Litt : [Youtube video]
  • Weakly Supervised Instance Segmentation using Class Peak Response, in CVPR 2018 (Python, Pytorch) [Github repo]
  • Weakly Supervised Object Localization (Python, Keras) [Github repo]
  • Grad-CAM: Gradient-weighted Class Activation Mapping [Github repo]
  • Transfer learning on computer vision datasets (Keras, Python) [Github repo]
  • Deep Quaternion Networks (Python, Keras) [Github repo]
  • Tensor-Train Layer and Tensor-Train Recurrent Neural Networks (including GRU and LSTM) (Python, Keras) [Github repo]
  • Reservoir Computing using Echo State Networks (Python) [Github repo]
  • DeepScores – A Dataset for Segmentation, Detection and Classification of Tiny Objects (Python, TensorFlow) [Paper & code]
  • Weakly Supervised Segmentation (Python, TensorFlow) [Github repo]
  • Bag of Visual words for Object Recognition [link]

Probability theory & statistical inference

  • A visual introduction to probability and statistics, Brown University [Link]
  • Probabilistic Graphical Models, Max Planck Institute  [YouTube lectures]

Natural language processing 


  • Google dataset search engine [Link]
  • Edinburgh DataShare [Link]
  • TIMIT Acoustic-Phonetic Continuous Speech Corpus [Link]
  • Public Datasets for AI [Link]

Data visualization

  • Introduction to the t-SNE algorithm [Link]
  • Poincaré Embeddings for Learning Hierarchical Representations [Github repo]
  • Design at Large - Laurens van der Maaten, Visualizing Data Using Embeddings [Youtube video]

Nonlinear systems

  • Nonlinear measures for dynamical systems (Python) [Github repo]
  • Calculating the Lyapunov Exponent of a Time Series (Python) [Link]
  • Reconstructing phase space and estimating maximal Lyapunov exponent from experimental time series [Link]