Deep Learning for Chatbots, Part 2 – Implementing a Retrieval-Based Model in Tensorflow


A positive label means that an utterance was an actual response to a context, and a negative label means that the utterance wasn't – it was picked randomly from somewhere in the corpus. Each record in the test/validation set consists of a context, a ground truth utterance (the real response) and 9 incorrect utterances called distractors. Before starting with fancy Neural Network models let's build some simple baseline models to help us understand what kind of performance we can expect. The Deep Learning model we will build in this post is called a Dual Encoder LSTM network.