This is an open source project (formerly named Listen, Attend and Spell - PyTorch Implementation) for end-to-end ASR implemented with Pytorch, the well known deep learning toolkit.
Role in this project:
Back-end Developer & ML Engineer Contributions:52 commits, 17 PRs, 139 pushes in 1 year 6 months
Contributions summary:Alexander made several contributions focused on end-to-end ASR implementation using PyTorch. Their work included adding and modifying code related to data loading, model training, and evaluation, especially adding a validation set, and defining data pipelines. Further contributions involved debugging and optimizing CTC prefix scoring, a critical component in ASR. Additionally, the user worked on training loop implementations, suggesting the user had a hands-on role in both the model and underlying infrastructure.
asrdeep-learningpytorch
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:35 pushes, 1 branch in 6 years 5 months
templategithub-pages-templatemmistakesmistakesjekyll