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A spoken dialog system, while commu-nicating with a user, must keep track of what the user wants from the system at each step. This process, termed dialog state tracking, is essential for a success-ful dialog system as it directly informs the system’s actions. The first Dialog State Tracking Challenge allowed for evalua-tion of different dialog state tracking tech-niques, providing common testbeds and evaluation suites. This paper presents a second challenge, which continues this tradition and introduces some additional features – a new domain, changing user goals and a richer dialog state. The chal-lenge received 31 entries from 9 research groups. The results suggest that while large improvements on a competitive base-line are possible, trackers are still prone to degradation in mismatched conditions. An investigation into ensemble learning demonstrates the most accurate tracking can be achieved by combining multiple trackers. 1
Henderson et al. (Wed,) studied this question.