The ubiquitous inverse relationship between word frequency and word rank is commonly known as Zipf’s law. The theoretical underpinning of this law states that the inverse relationship yields decreased effort in both the speaker and hearer, the so-called principle of least effort. Most research has focused on showing an inverse relationship only for written monolog, only for frequencies and ranks of one linguistic unit, generally word unigrams, with strong correlations of the power law to the observed frequency distributions, with limited to no attention to psychological mechanisms such as the principle of least effort. The current paper extends the existing findings, by not focusing on written monolog but on a more fundamental form of communication, spoken dialog, by not only investigating word unigrams but also units quantified on syntactic, pragmatic, utterance, and nonverbal communicative levels by showing that the adequacy of Zipf’s formula seems ubiquitous, but the exponent of the power law curve is not, and by placing these findings in the context of Zipf’s principle of least effort through redefining effort in terms of cognitive resources available for communication. Our findings show that Zipf’s law also applies to a more natural form of communication—that of spoken dialog, that it applies to a range of linguistic units beyond word unigrams, that the general good fit of Zipf’s law needs to be revisited in light of the parameters of the formula, and that the principle of least effort is a useful theoretical framework for the findings of Zipf’s law.

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Zipf's law is a mathematically relatively simple formula stating that the frequency of a word is inversely correlated with its rank. Zipf's law is well-known in computational linguistics and cognitive sciences alike. In the context of agent development, however, Zipf's law has hardly ever been mentioned. This is surprising as principles regarding language likely benefit the development of conversational agents. This paper serves as a starting point to explore the role of Zipf's law in agent development, showing that Zipf's law also applies to dialog. Moreover, it can shed light on human-machine dialog. In addition to word frequency distributions that demonstrate Zipf's law, we also included frequency distributions of words at specific positions in the sentence as well as turn lengths. Zipf's law was found in the far majority of analyses we conducted. In addition, we investigated whether Zipf's law can be used to detect differences between human and agent-generated speech through correlating the distributions and found that even though both the human and agent frequency distributions follow Zipf's law, these distributions are not necessarily similar, shedding light on where agent dialog may distinguish itself from human dialog. The findings in this paper can thus serve as a way to monitor to what extent ubiquitous patterns in human-human dialog are found in humanmachine dialog. CCS CONCEPTS • Computing methodologies → Discourse, dialogue and pragmatics; • Mathematics of computing → Distribution functions.

Human interlocutors automatically adapt verbal and non-verbal signals so that different behaviors become synchronized over time. Multimodal communication comes naturally to humans, while this is not the case for Embodied Conversational Agents (ECAs). Knowing which behavioral channels synchronize within and across speakers and how they align seems critical in the development of ECAs. Yet, there exists little data-driven research that provides guidelines for the synchronization of different channels within an interlocutor. This study focuses on intrapersonal dependencies of multimodal behavior by using cross-recurrence analysis on a multimodal communication dataset to better understand the temporal relationships between language and gestural behavior channels. By shedding light on the intrapersonal synchronization of communicative channels in humans, we provide an initial manual for modality synchronisation in ECAs. CCS CONCEPTS • Human-centered computing → Empirical studies in HCI; • Computing methodologies → Discourse, dialogue and pragmatics.

We introduce an interactive embodied conversational agent for deployment in the healthcare sector. The agent is operated by a software architecture that integrates speech recognition, dialog management, and speech synthesis, and is embodied by a virtual human face developed using photogrammetry techniques. These features together allow for real-time, face-to-face interactions with human users. Although the developed software architecture is domain-independent and highly customizable, the virtual agent will initially be applied to healtcare domain. Here we give an overview of the different components of the architecture. CCS CONCEPTS• Computing methodologies → Artificial intelligence; Rendering; • Computer systems organization → Architectures.