"When I was working on speech understanding systems at SRI in the 1970s, other research team members were responsible for syntax and grammar — determining the structure and building a computer representation of the meaning of an individual sentence. Everyone involved in early speech understanding systems knew that wasn’t enough. When people talk, the context matters. They use pronouns and definite descriptions. They depend on each other to interpret those imprecise expressions appropriately in context. For example, depending on the setting, “the cup” might mean my coffee cup or the cup you received as a gift. We knew that if we were going to have a system that could carry on a dialogue and be able to handle the way people actually spoke, we needed to have a computational model of dialogue that could track context. Many researchers thought if they sat in a chair and thought really hard, they could figure it out. I expected that wouldn’t work and devised a way to capture dialogue about the same topic from many different pairs of people. This was actually the first “Wizard of Oz” experiment in dialogue systems, though that name came later. I placed two people in separate rooms and had one give the other instructions in how to put together a piece of equipment — an air compressor. My analysis of the way they talked led to the first computational model of discourse."