Natural Language Processing (NLP) engineer and computational linguist with over 10 years of experience in both knowledge-based and data-driven technologies. Most of my work has focused on multilingual NLP pipelines and methods for extracting structure from unstructured data. I have covered a wide range of areas including machine translation (ProMT, WebInterpret), automatic summarization (Sumplify), chatbots (Maluuba, Telefónica), and sentiment analysis and text classification (AYLIEN). I have a passion for data formalization, experimental evaluation, and error-driven development.

Speech

Topic: Recent advances in applied chatbot technology

Short Description: Chatbots (aka conversational agents and spoken dialogue systems) allow users to interface with computers using natural language. Users can ask questions or issue commands in their native language, and the chatbot then returns the exact answer or performs any actions necessary to arrive at the state of affairs expressed by the user.
Besides the direct applications of chatbots in IoT (Amazon Alexa, Apple’s Siri) and IT (the historical field of Information Retrieval as a whole can be seen as a sub-problem of spoken dialogue systems), chatbots’ main appeal for technologists is their location at the intersection of all major Natural Language Processing technologies and many of the deepest questions in Cognitive Science today.
In this talk, I will explore those questions in the context of an applied industry setting and I will introduce a Python framework suitable for addressing them, together with an overview of the state-of-the-art in chatbot technology and some original techniques.