How to Implement a Beam Search Decoder for Natural Language Processing - Machine Learning Mastery

Natural language processing tasks, such as caption generation and machine translation, involve generating sequences of words. Models developed for these problems often operate by generating probability distributions across the vocabulary of output words and it is up to decoding algorithms to sample the probability distributions to generate the most likely sequences of words. In this tutorial, you will discover the greedy search and beam search decoding algorithms that can be used on text generation problems. How to Implement Beam Search Decoder for Natural Language Processing Photo by See1,Do1,Teach1, some rights reserved. In natural language processing tasks such as caption generation, text summarization, and machine translation, the prediction required is a sequence of words.