DOI: 10.1017/S000000000000000 Printed in the United Kingdom A Survey of Statistical User Simulation Techniques for Reinforcement-Learning of Dialogue Management Strategies <s> Degrees of Initiative <s> Abstract ::: This paper discusses some of the aspects of task requirements, user expectations, and technological capabilities that influence the design of a voice interface and then identifies several components of user interfaces that are particularly critical in successful voice applications. Examples from several applications are provided to demonstrate how these components are used to produce effective voice interfaces. <s> BIB001 </s> DOI: 10.1017/S000000000000000 Printed in the United Kingdom A Survey of Statistical User Simulation Techniques for Reinforcement-Learning of Dialogue Management Strategies <s> Degrees of Initiative <s> Menu-based or system driven dialogues are widely used in interfaces to telephone services. The communication structure they impose on the customer differs from human-human dialogues, where control and initiative can switch from one partner to the other. It has often been claimed that mixed initiative dialogues could improve the user friendliness and efficiency of spoken language interfaces. In this paper we investigate whether mixed initiative dialogues do indeed outperform system driven dialogues as interface to a relatively simple service, i.e. a call assistance service that gives access to a small number of companies and agencies through a single premium rate access number. Results show that mixed initiative dialogues are not faster, nor more comfortable than system driven dialogues, at least in this service. We discuss possible explanations for our findings. <s> BIB002 </s> DOI: 10.1017/S000000000000000 Printed in the United Kingdom A Survey of Statistical User Simulation Techniques for Reinforcement-Learning of Dialogue Management Strategies <s> Degrees of Initiative <s> This paper reports experimental results comparing a mixed-initiative to a system-initiative dialog strategy in the context of a personal voice email agent. To independently test the effects of dialog strategy and user expertise, users interact with either the system-initiativeor the mixed-initiative agent to perform three successive tasks which are identical for both agents. We report performance comparisons across agent strategies as well as over tasks. This evaluation utilizes and tests the PARADISE evaluation framework, and discusses the performance function derivable from the experimental data. <s> BIB003
Dialogue management strategies are often classified according to the degree of initiative they take in a dialogue. Systems following a system-initiative strategy take the lead role in a dialogue by asking precise, direct questions such as "Where are you flying from? What is your destination? What is your preferred departure date?". The user is sequentially prompted for every necessary piece of information and his or her response is expected to contain only the requested piece of information. This type of approach is often chosen in commercial applications, because it usually results in short user responses, less out-of-domain utterances and higher recognition performance BIB001 . Mixed-initiative systems on the other hand, share control over the dialogue flow with the user. Systems of this type often start with an open question such as "How can I help you?". They can usually process more complex linguistic constructs and allow the user to specify several pieces of information at the same time. Mixed-initiative systems place less constraints on the information flow between the user and the system and thus potentially allow for more efficient dialogues. An expert user who is familiar with the system for instance, is not forced to step through a long series of prompts. Instead, he or she is able to enter all the necessary information without having to wait for the system to request it   . Given adequate recognition performance, mixed-initiative strategies lead to a more powerful form of dialogue control because they exploit the ability of human language to simultaneously convey multiple pieces of information in a compact representation. Indeed, user frustration with current system-initiative SDS often arises because this advantage is not exploited. A series of yes/no questions for a telephony application, for instance, may just as well be implemented using touch-tone input. Users are often reluctant to use a voice interface if the same functionality can be delivered using a more noise-robust and less errorprone communication channel. With a mixed-initiative strategy, the benefits of using a natural language interface should be more evident to the user. Studies such as BIB002 , however, show that mixed-initiative strategies may not always be preferable given the limited recognition and understanding capabilities of current systems. A system initiative strategy places stronger constraints on the user input and enables the search space of the recognizer to be highly constrained. As a consequence, the recognition performance and goal achievement rate under high-noise conditions is often better when a system-initiative strategy is used. The reduced number of misunderstandings can lead to greater user-satisfaction, despite the strong constraints placed on the dialogue. In choosing between system-initiative and mixed-initiative, one also needs to consider that users draw on previous experiences with spoken dialogue systems and tend to develop a mental model of the system behaviour. Users who are used to traditional forms of system-initiative "slot-filling" dialogue, may expect the SDS to fill one slot after the other. An open question such as "How can I help you?" may appear irritating, since it gives no clear indication as to what response the system expects. Even expert-users often prefer a clearly structured system-initiative dialogue over a mixed-initiative one BIB003 . The perceived dialogue progress is also very important. A system-initiative strategy may be the less efficient form of communication, but it provides an assuring feeling of constant progress. Research has suggested the use of hybrid approaches    ) that allow a mixed-initiative system to back off to system-initiative when dialogue problems are detected. This way, the system can regain control when the dialogue seems to deviate from the correct path or when the recognition performance suffers.