Creating a chatbot that can understand and use a language other than English can be an ambitious task. Chatbots are still in their early days and even though there are many NLP libraries available, most of them support only the English language. From stopwords and POS taggers to pretrained word2vec models, it can be time-consuming to work on an NLP problem in a different language.
We at SmartCat tried a bit of a different approach in creating a bot that uses the Serbian language. Using a large dataset of unlabeled sentences written in Serbian and performing ML methods, we were able to create a chatbot that resulted in a very decent performance. It was able to return an expected response 9/10 times. Interested in how we did it? Keep on reading.