This is a guide to get started with Botium NLU/NLP Testing Step 1: Connect Botium to Your Conversational AI Step 2: Prepare Datasets for Training and Testing This is the step where most of the effort is involved: the machine learning algorithms involved in NLP - and most of the state-of-the-art NLP engines out there are based on some kind of machine learning - are only as good as the data they have been trained on. It is both a question of quality as well as quantity. Step 3: Start a Test Session on Botium In the previous steps, we connected Botium with your NLU engine and prepared the test dataset. In this step we will start the first test session. Step 4: Identify NLP-related Issues and Solutions The Botium Dashboard visualizes the NLP performance metrics and suggests steps for improving it. It will show any pieces of test data that either did not return the expected intent, did return the expected intent but with a low confidence score, or did return the expected intent, but with a confidence score close to another intent’s. Step 5: Annotate and Augment Training Dataset As you have now identified some issues in your NLU performance it is time to augment the training data to improve the NLU performance. Step 6: Training your NLU engine For your convenience and for fast feedback cycles, Botium brings a Test Case Wizard for uploading training data from Botium to your NLU engine of choice and start the training process. Step 7: Validate Improvements Parent topic: NLU / NLP Testing Related articles Botium NLU / NLP Analytics Support Botium Asserters Translating Botium Test Cases The Value of Botium Testing How to Automate Testing of Your WhatsApp Chatbot Comments 0 comments Please sign in to leave a comment.