Multifunctionality: Driving and constraining forces

For many organizations it has become essential to utilize the available production resources in a flexible and efficient manner. Flexibility seems to no longer be a matter of choice but of necessity. This article focuses on one form of flexibility, namely the extent to which employees are multifunctional or functionally flexible in an organization. It presents a pilot study of 10 organizations in which not only the motives for implementing multifunctionality (the driving forces) are assessed, but also the constraining factors. In the sample it was found that multifunctionality is considered essential, in particular when organizations operate in a volatile and uncertain market. However, the implementation of multifunctionality may be limited in practice due to such factors as the costs of training and employees' preferences and abilities. © 1998 John Wiley & Sons, Inc.     

Evolvable dialogue state tracking for statistical dialogue management

Statistical dialogue management is the core of cognitive spoken dialogue systems (SDS) and has attracted great research interest. In recent years, SDS with the ability of evolution is of particular interest and becomes the cuttingedge of SDS research. Dialogue state tracking (DST) is a process to estimate the distribution of the dialogue states at each dialogue turn, given the previous interaction history. It plays an important role in statistical dialogue management. To provide a common testbed for advancing the research of DST, international DST challenges (DSTC) have been organised and well-attended by major SDS groups in the world. This paper reviews recent progresses on rule-based and statistical approaches during the challenges. In particular, this paper is focused on evolvable DST approaches for dialogue domain extension. The two primary aspects for evolution, semantic parsing and tracker, are discussed. Semantic enhancement and a DST framework which bridges rule-based and statistical models are introduced in detail. By effectively incorporating prior knowledge of dialogue state transition and the ability of being data-driven, the new framework supports reliable domain extension with little data and can continuously improve with more data available. Thismakes it excellent candidate for DST evolution. Experiments show that the evolvable DST approaches can achieve the state-of-the-art performance and outperform all previously submitted trackers in the third DSTC.     

Recommending topics in dialogue

Several types of online chat system have been developed; however, there exist no recommendation systems for the recommendation of topics suitable for discussion with a given individual at a particular time. This paper proposes a hot-topic recommendation system based on analysis of the tweets posted by the user, his/her chat partners, and similar users of his/her chat partners, as well as hashtags trending in Twitter. In experiments, the proposed system, which is based on the well-known Latent Dirichlet Allocation (LDA) algorithm, was shown to outperform existing recommendation systems with regard to computational efficiency as well as prediction accuracy.     

Turn-taking cues in task-oriented dialogue

As interactive voice response systems become more prevalent and provide increasingly more complex functionality, it becomes clear that the challenges facing such systems are not solely in their synthesis and recognition capabilities. Issues such as the coordination of turn exchanges between system and user also play an important role in system usability. In particular, both systems and users have difficulty determining when the other is taking or relinquishing the turn. In this paper, we seek to identify turn-taking cues correlated with human–human turn exchanges which are automatically computable. We compare the presence of potential prosodic, acoustic, and lexico-syntactic turn-yielding cues in prosodic phrases preceding turn changes (smooth switches) vs. turn retentions (holds) vs. backchannels in the Columbia Games Corpus, a large corpus of task-oriented dialogues, to determine which features reliably distinguish between these three. We identify seven turn-yielding cues, all of which can be extracted automatically, for future use in turn generation and recognition in interactive voice response (IVR) systems. Testing Duncan’s (1972) hypothesis that these turn-yielding cues are linearly correlated with the occurrence of turn-taking attempts, we further demonstrate that, the greater the number of turn-yielding cues that are present, the greater the likelihood that a turn change will occur. We also identify six cues that precede backchannels, which will also be useful for IVR backchannel generation and recognition; these cues correlate with backchannel occurrence in a quadratic manner. We find similar results for overlapping and for non-overlapping speech.     

Initiative conflicts in task-oriented dialogue

An initiative conflict is an overlap of speech in which both conversants try to steer the conversation in different directions. In this paper, we investigate how conversants in human-human dialogue deal with such conflicts. First, in investigating why initiative conflicts occur, we find that the offsets of the utterances involved in initiative conflicts tend to be very short, and that initiative conflicts seem more likely to occur when one of the conversants has an urgent conversational goal. These findings strongly suggest that initiative conflicts are unintentional collisions and that conversants try to prevent them from even occurring, unless there is an urgent reason. Second, in investigating how initiative conflicts are resolved, we find that the overlaps tend to last less than two syllables, that volume correlates with who wins initiative conflicts, and that for longer overlaps, the volume of the winner increases in the second half of the overlaps. These findings strongly suggest that initiative conflicts are quickly resolved through an interactive process, using volume as one of the devices. Third, we find that after an initiative conflict is resolved, the winner sometimes repeats the words involved in the overlap; and this happens more when the overlap is more likely to interfere with the other conversant’s understanding. These findings will help us build next-generation mixed-initiative spoken dialogue systems that are natural and efficient to use.     

Implementing dialogue independence

Separating the development of the core application from that of its user interface provides encapsulation, flexibility, and reuse advantages, but poses the problem of how to mirror changes to one component in the other. The authors identify three design patterns that achieve this mirroring while maintaining dialogue independence     

Multi-level cooperative dialogue in intelligent front-ends

The control of multi-level cooperative dialogue is considered a difficult problem in knowledge based systems but may be easier to tackle in the more restricted domain of Intelligent Front-Ends. This paper discusses the requirement for multi-level cooperative dialogue in IFE programs and describes several techniques for supporting this form of interaction, using examples from implemented systems.     

Asymmetric quantum dialogue in noisy environment

A notion of asymmetric quantum dialogue (AQD) is introduced. Conventional protocols of quantum dialogue are essentially symmetric as the users (Alice and Bob) can encode the same amount of classical information. In contrast, the proposed scheme for AQD provides different amount of communication powers to Alice and Bob. The proposed scheme offers an architecture, where the entangled state to be used and the encoding scheme to be shared between Alice and Bob depend on the amount of classical information they want to exchange with each other. The general structure for the AQD scheme has been obtained using a group theoretic structure of the operators introduced in Shukla et al. (Phys Lett A 377:518, 2013). The effect of different types of noises (e.g., amplitude damping and phase damping noise) on the proposed scheme is investigated, and it is shown that the proposed scheme for AQD is robust and it uses an optimized amount of quantum resources.     

Characterizing user performance in command-driven dialogue

To learn to use an interactive system, a person typically has to acquire a good deal of new knowledge. The ease of learning will depend on the extent to which the design of the task and the interface capitalizes on the user's pre-existing knowledge and his or her cognitive capabilities for learning. This paper explores the nature of both design decisions and user learning with a command-based system. Three studies were conducted, all involving a task in which secret messages were decoded by means of a sequence of commands (based on the task used by Barnard et al. In Study I, software specialists designed command structures for the task and gave reasons for their choices. In Study II, naive subjects chose between alternative command terms. In Study TTI, subjects learned to use interactive versions of the task in which dialogue factors (command terms and argument structures) were systematically varied. The results enabled the development of user knowledge of the system to be specified in detail. Comparisons across the three studies highlighted the diversity of the factors determining both design decisions and user behaviour.     

An inquiry dialogue system

The majority of existing work on agent dialogues considers negotiation, persuasion or deliberation dialogues; we focus on inquiry dialogues, which allow agents to collaborate in order to find new knowledge. We present a general framework for representing dialogues and give the details necessary to generate two subtypes of inquiry dialogue that we define: argument inquiry dialogues allow two agents to share knowledge to jointly construct arguments; warrant inquiry dialogues allow two agents to share knowledge to jointly construct dialectical trees (essentially a tree with an argument at each node in which a child node is a counter argument to its parent). Existing inquiry dialogue systems only model dialogues, meaning they provide a protocol which dictates what the possible legal next moves are but not which of these moves to make. Our system not only includes a dialogue-game style protocol for each subtype of inquiry dialogue that we present, but also a strategy that selects exactly one of the legal moves to make. We propose a benchmark against which we compare our dialogues, being the arguments that can be constructed from the union of the agents’ beliefs, and use this to define soundness and completeness properties that we show hold for all inquiry dialogues generated by our system.     

Measurement device-independent quantum dialogue

Very recently, the experimental demonstration of quantum secure direct communication (QSDC) with state-of-the-art atomic quantum memory has been reported (Zhang et al. in Phys Rev Lett 118:220501, 2017). Quantum dialogue (QD) falls under QSDC where the secrete messages are communicated simultaneously between two legitimate parties. The successful experimental demonstration of QSDC opens up the possibilities for practical implementation of QD protocols. Thus, it is necessary to analyze the practical security issues of QD protocols for future implementation. Since the very first proposal for QD by Nguyen (Phys Lett A 328:6–10, 2004), a large number of variants and extensions have been presented till date. However, all of those leak half of the secret bits to the adversary through classical communications of the measurement results. In this direction, motivated by the idea of Lo et al. (Phys Rev Lett 108:130503, 2012), we propose a measurement device-independent quantum dialogue scheme which is resistant to such information leakage as well as side-channel attacks. In the proposed protocol, Alice and Bob, two legitimate parties, are allowed to prepare the states only. The states are measured by an untrusted third party who may himself behave as an adversary. We show that our protocol is secure under this adversarial model. The current protocol does not require any quantum memory, and thus, it is inherently robust against memory attacks. Such robustness might not be guaranteed in the QSDC protocol with quantum memory (Zhang et al. 2017).     

Human-computer dialogue design considerations

The three critical elements of quality human-computer dialogue design include a compilation of existing design guidelines, behavioral research to expand the general dialogue principles, and a computer-aided implementation for retrieval of the guidelines by dialogue authors. The need for empirically based dialogue guidelines relating to generic human-computer taks is stressed. The results of two studies dealing with interactive text editing are presented as examples of research directed toward specifying dialogue design principles and developing formal tools for human-computer dialogue research. One of these studies deals with a methodology for developing user models, and the second study deals with the design of HELP information. Computer-aiding in the form of rule-based systems for selecting appropriate dialogue guidelines and software tools for authoring dialogues are discussed as means for implementing these dialogue design considerations.     

Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems

This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on the partially observable Markov decision process (POMDP), which provides a well-founded, statistical model of spoken dialogue management. However, exact belief state updates in a POMDP model are computationally intractable so approximate methods must be used. This paper presents a tractable method based on the loopy belief propagation algorithm. Various simplifications are made, which improve the efficiency significantly compared to the original algorithm as well as compared to other POMDP-based dialogue state updating approaches. A second contribution of this paper is a method for learning in spoken dialogue systems which uses a component-based policy with the episodic Natural Actor Critic algorithm.The framework proposed in this paper was tested on both simulations and in a user trial. Both indicated that using Bayesian updates of the dialogue state significantly outperforms traditional definitions of the dialogue state. Policy learning worked effectively and the learned policy outperformed all others on simulations. In user trials the learned policy was also competitive, although its optimality was less conclusive. Overall, the Bayesian update of dialogue state framework was shown to be a feasible and effective approach to building real-world POMDP-based dialogue systems.     

Requirements for belief models in cooperative dialogue

Models of rationality typically rely on underlying logics that allow simulated agents to entertain beliefs about one another to any depth of nesting. Such models seem to be overly complex when used for belief modelling in environments in which cooperation between agents can be assumed, i.e., most HCI contexts. We examine some existing dialogue systems and find that deeply-nested beliefs are seldom supported, and that where present they appear to be unnecessary except in some situations involving deception.Use of nested beliefs is associated with nested reasoning (i.e., reasoning about other agents' reasoning). We argue that for cooperative dialogues, representations of individual nested beliefs of the third level (i.e., what A thinks B thinks A thinks B thinks) and beyond are in principle unnecessary unless directly available from the environment, because the corresponding nested reasoning is redundant.Since cooperation sometimes requires that agents reason about what is mutually believed, we propose a representation in which the second and all subsequent nesting levels are merged into a single category. In situations affording individual deeply-nested beliefs, such a representation restricts agents to human-like referring and repair strategies, where an unrestricted agent might make an unrealistic and perplexing utterance.     

Navigational abilities in audial voice-controlled dialogue structures

Four audial navigation structure conditions, designed to support a voice messaging service, each demanding a different degree of cognitive load, were assessed by 40 naive subjects in groups of 10. Three were voice-controlled: Hierarchical , Flexible (direct, no menus) and Guided (Yes/No) and one was keypad-controlled: hierarchical. Voice recognition was simulated by means of a Wizard-of-Oz set-up. The four subject groups were matched regarding spatial ability (High/ Low) as measured by the Duremann-Salde battery. Initial interaction performance was observed over six tasks, without providing the subjects with a conceptual model of the navigation structure or an appropriate command syntax. Neither number of completed tasks (4.6-5.1 out of 6), total completion time (701-849 s), nor subjective attitudes differed significantly across navigation conditions. The simple optimum path measure was significant, favouring the guided (4.1 out of 6) as compared to the flexible structure (2.5 out of 6). A significant interaction effect between total completion time and spatial ability was found. Subjects scoring high on spatial ability obtained shorter task completion time than those scoring low, except for the guided structure, where the opposite effect occurred. The results stress the importance of adapting navigating structure to specific user abilities for user environments such as telephone services. A highly guided navigation style, a structure that maximizes optimum path score, suits users with low spatial ability, especially in the initial learning phase.     

Hierarchical dialogue structures in interactive computer systems

A powerful yet simple-to-use command dialogue has evolved in the development of an interactive graphics system for the computer-aided design of electronic circuits. This dialogue overcomes many of the problems typically encountered in systems with a strongly hierarchical command structure; the user is kept constantly aware of the current state within the hierarchy and is able to manoeuvre rapidly about this structure. The rules for the use of the dialogue are few and simple; mistakes are not catastrophic. The dialogue is equally suited to both naïve and experienced users. The dialogue is described in the context of an interactive graphics environment, but the extension of the principles to any interactive computer system should be obvious.