Speech
- Acoustic event detection - quantization, distillation, separable covolutions to make models smaller and faster;
- Surprise surprise - tuning a large model for speakers with speech impairments improves quality;
- Google’s state-of-the-art speaker duarization;
- How CMU Sphinx works;
- A very cool and from the likes of it - working paper - real time voice cloning;
NLP
- NLP trends from ACL 2019;
- Yet another better BERT;
- The Illustrated GPT-2 (Visualizing Transformer Language Models);
- Facebook finally embraces FastText for misspellings;
- Key idea - use pre-trained transformers for distillation;
- Add robustness to - NMT by adding adversarial examples to train data;
- Transformer with 8B parameters;
- State of transfer learning in NLP - kind of meh article;
- OpenAI huge GPT follow-up;
ML / market
Cool libraries / papers / etc
- Inplace BatchNorm - memory usage reduction for CV;
QRNN explanation;
- Yet another LSTM replacement - SRU. Similar to QRRN - it requires additional dependencies;
- Cycle consistency for repeating actions in video;
- Dealing with artifacts in medical CV - just train a model to filter them out;
- Useful DS sampling algorithms;
- Wavefunction collapse algorithm;
Python / coding
Cool random stuff
- Automated fly brain slicing with CNNs;
- Idea - hardware-encoded limitations for embedded ML devices;
- Lottery ticket hypothesis revisited;
- Advances in conversational AI by - FAIR:

- Key problem - dialogue consistency;
- “Сreated a new NLI data set called Dialogue NLI, which is used to both improve and evaluate the consistency of dialogue models”;