Practical guide to Attention mechanism for NLU tasks

Chatbots, virtual assistants, augmented analytic systems typically receive user queries such as "Find me an action movie by Steven Spielberg". The system should correctly detect the intent "find_movie" while filling the slots "genre" with value "action" and "directed_by" with value "Steven Spielberg". This is a Natural Language Understanding (NLU) task kown as Intent Classification & Slot Filling. State-of-the-art performance is typically obtained using recurrent neural network (RNN) based approaches, as well as by leveraging an encoder-decoder architecture with sequence-to-sequence models. In this article we demonstrate hands-on strategies for improving the performance even further by adding Attention mechanism.