Sequence modelling

Neural Machine Translation

Built a 12.5M-pair dataset for Vietnamese diacritic restoration and implemented RNN, GRU, LSTM and Transformer seq2seq models from scratch in PyTorch.

• Built the first large-scale Vietnamese diacritic restoration dataset (12.5M sentence pairs without → with diacritics).
• Implemented Seq2Seq models (RNN, GRU, LSTM, Transformer) from scratch using PyTorch.
• Designed and conducted comprehensive model evaluation with BLEU and ChrF++ metrics, achieving BLEU 81.31 and ChrF++ 88.57 with Transformer, significantly outperforming RNN and GRU baselines.
• Contributed across data construction, model development, and performance evaluation, leading to a robust prototype system for Vietnamese text restoration.