Customer care dialog management, an inverse reinforcement learning approach
Details
Event
NIPS (Neural Information Processing Systems) 2014 Workshop
2014-12-13
Speakers
Dent, Kyle
Event
Customer care dialog management, an inverse reinforcement learning approach
In the last decade weve seen advances in speech recognition, natural language understanding, natural language generation, and speech synthesis to such an extent that conversational interfaces are becoming possible. Indeed, personal assistants like Apple Siri, Microsoft Cortana, and Nuance DMA have brought conversational agents into popular use. In addition, task-based agents have begun to partially automate activities like hotel reservations and limited banking functions. However, rich and demanding tasks such as those needed to automate customer care environments especially those performing troubleshooting require significant progress to become viable. Many dialog systems are still based on deterministic approaches with a pre-defined set of tasks where adaptability is limited.
Additional information
Focus Areas
Our work is centered around a series of Focus Areas that we believe are the future of science and technology.
Licensing & Commercialization Opportunities
We’re continually developing new technologies, many of which are available for Commercialization.
News
Our scientists and staffers are active members and contributors to the science and technology communities.