|Goals:||Build a chatbot that is able to generate diverse responses.|
|Assistant:||Yubo Xie (yubo DOT xie AT epfl DOT ch)|
|Keywords:||Generative dialog model; natural language processing|
By training a generative neural model on massive dialog data, a chatbot can already respond in a way that makes sense. However, sometimes the replies generated by chatbots are generic and dull (for example “I don’t know”), and lack some specificity according to the conversation context. One explanation is that these utterances appear more frequently in the training set, which leads to a higher probability of being generated. This project aims at increasing the diversity of the responses generated by chatbots, while still keeping them on the conversation topic.
The student is expected to:
|Related Skills:||Basic knowledge in natural language processing and neural networks|
|Suitable for:||Master student. Interested student should contact Yubo Xie (yubo DOT xie AT epfl DOT ch) and Pearl Pu (pearl DOT pu AT epfl DOT ch) along with a copy of your CV as well as your transcript.|