Korean text normalization and language preparation package for LM in Kaldi-based ASR system

Keyword Search Recipe for Subword ASR

Simple-to-use scoring function for arbitrarily tokenized texts.

Subword-augmented Embedding for Cloze Reading Comprehension (COLING 2018)

johnny - a neural network graph based DEPendency Parser

Effective Subword Segmentation for Text Comprehension (TASLP 2019)

Unsupervised Word Segmentation using Minimum Description Length for Neural Machine Translation (NMT)

An implementation of subword division algorithm proposed in T. Mikolov (2012).

A framework for generating subword vocabulary from a tensorflow dataset and building custom BERT tokenizer models.

This repository contains source code implementation of assignments for NTU's MSAI course AI6127 on Deep Neural Networks for Natural Language Processing (2019 Sem 2).

Tokenization is a way of separating a piece of text into smaller units called tokens. Here, tokens can be either words, characters, or subwords. Hence, tokenization can be broadly classified into 3 types – word, character, and subword (n-gram characters) tokenization.

The concept of DAWGs is based on: Blumer, A. et al. (1985). The smallest automation recognizing the subwords of a text. Theoretical Computer Science, 40, 31–55.

Subword Neural Machine Translation