For a project at my university I have to develop a simple chatbot. Since I am new to machine learning, it should be really simple and work like a customer support. The chatbot has to recognize about 10 intents related to some really simple topic. For example I thought that it could give information about a party, so the questions would be something like "Where is the party?, When does the party start? How much does the entry cost?"
The chatbot should classify the question, and out of the classification it should give back a prepared answer. If it cannot assign the question to the one of the 10 intents, it should do nothing or just answer that it does not understand the question. The same may happen if the question has spelling mistakes.
So it should be really simple, but be programmed with the deep learning approach.
My question is, how much data should I have, to train this bot to assign questions to the intents? Would I be able to generate the data by my own, if I reformulate each question on, lets say 20 ways? Or do I have to feed the algorithm with a very large amount of data, even for such simple task?