Creating Conversational Assistants: Challenges and Solutions
Conversational assistants are all around us – as smart speakers in our homes, on our smartphones, in our cars. The Conversational AI market is expanding dramatically and major technology companies are producing ever larger language models and datasets to support the development of conversational assistants. However, the use of these assistants is currently mainly restricted to one shot conversations involving commands or questions, or in some cases to fulfilling well-defined tasks. More open conversations are still within the realm of research, yet these systems will be needed for new areas of application such as conversational commerce, healthcare and mental health support, and the promotion of active and healthy ageing in older people. Traditional approaches based on best-practice guidelines are compared with new neural dialogue based approaches. The presentation concludes with a brief look at some recent projects in which I have been involved and the different ways in which they are addressing the challenges faced by designers and developers of conversational assistants.
Michael McTear is an Emeritus Professor at Ulster University with a special interest in spoken language technologies. He has been researching in the field of spoken dialogue systems for more than 20 years and is the author of several books, including Spoken Dialogue Technology: Toward The Conversational User Interface (Springer, 2004), Spoken Dialogue Systems (Morgan and Claypool, 2010), with Kristiina Jokinen, The Conversational Interface: Talking to Smart Devices (Springer, 2016), with Zoraida Callejas and David Griol, and Conversational AI ( Morgan & Claypool 2020). Michael has delivered keynote addresses and tutorials at many academic conferences and workshops, including SpeechTEK, Conversational Interaction, ProjectVoice, REWORK AI Assistant Summit, and the European Chatbot Conferences. Currently Michael is involved in several research and development projects investigating the use of conversational agents in socially relevant projects such as mental health monitoring, and home monitoring of older persons.