This repository is the main hub of work my MSc Dissertation "Word Embedding Reconstruction with Subword Embeddings for Language Modelling", available here
This repository is a mix of my own work and forks from other repositories.
charCNN is a reimplementation of Learning to Generate Word Representations using Subword Information, which I use as a reconstruction method.
cr_clean is a fork of Compact Reconstruction, which I use as a reconstruction method.
pyTorch_LM is a fork of a word level LM pyTorch tutorial,
which I include the ability to use pre-trained embeddings and then use to build a language model and evaluate perplexity of various embeddings.
distance_measuring has inital tests of the quality of the reconstructed embeddings compared to reference embeddings, such as cosine similarity and P@n
results/embedding_comparison is where I put my results!
utils has a few repo-wide scripts for making baseline embeddings, limiting the character set in embeddings, etc.