Conversational agents, also known as ChatBots or Dialog Systems, have gained a lot of interest recently. Traditional conversational agent systems usually require significant development effort and are based on complex modules for understanding user inputs, taking decisions and generating meaningful answers. Thanks to the advance of deep learning in close areas such as Neural Machine Translation, recent research is being devoted to data-driven neural conversational models that can learn from human conversations. However, the development of robust and reliable chatbots based purely on deep learning technologies is still an open area of research and it is still common to develop agents based on hybrid approaches using hand-crafted rules and state-of-the-art techniques. This talk is aims at providing an overview of the development of chatbots, while giving a brief review of the state-of-the-art and current challenges.
Carlos Segura, Ph.D., is an Associate Researcher at Telefonica Research in Barcelona, Spain. From 2011 to 2015 he worked at the company Herta Security as the Director of Innovation under the Torres Quevedo program, where his main duties were researching and developing algorithms for speaker and face recognition. He has participated in three national research projects and three EU research projects, and has published many scientific papers in peer-reviewed international journals and international conferences. His research interests include deep learning, machine learning. speech processing, computer vision, and more lately, natural language processing and dialog systems.