In our lab meeting tomorrow, Anahita will introduce a Neural method for Word Alignment. A Zoom link will be posted to Twist on the morning of the meeting.
Neural Hidden Markov Model for Word Alignment
Abstract: We present our results for neuralizing an unsupervised Hidden Markov Model (HMM) for word alignment. This work proposes a hidden Markov model with neural network-based lexicon and alignment models, which are trained jointly using the Baum-Welch algorithm. Our experimental results show that neural HMM generally outperforms its GIZA++ IBM4 baseline.
Tuesday, Apr 28st, 09:30 a.m.