Recent work has looked to understand user perceptions of speech agent capabilities as dialogue partners (termed partner models), and how this affects user interaction. Yet, partner model effects are currently inferred from language production as no metrics are available to quantify these subjective perceptions more directly. Through three phases of work, we develop and validate the Partner Modelling Questionnaire (PMQ): an 18-item self-report semantic differential scale designed to reliably measure people’s partner models of non-embodied speech interfaces. Through confirmatory factor analysis, we confirm that the PMQ scale consists of three factors: communicative competence and dependability, human-likeness in communication and communicative flexibility. Our studies show that the measure consistently demonstrates good internal reliability, strong test-retest reliability over 4- and 12-week intervals, and predictable convergent/divergent validity. Based on our findings, we discuss the multidimensional nature of partner models, while identifying key future research avenues that the development of the PMQ facilitates. Notably, this includes the need to identify the activation, sensitivity, and dynamism of partner models in speech interface interaction.

Speech-enabled smart speakers are common devices used for numerous tasks in everyday life. While speech-enabled technologies are widespread, using one’s voice as a computing modality introduces new accessibility challenges for people with speech disfluencies such as stammering (also known as stuttering). This paper investigates the smart speaker user experiences of people who stammer over three weeks. We conducted diary studies and semi-structured interviews with 11 individuals to identify their daily routines, difficulties with successful interactions, and strategies to overcome these barriers. Our analysis demonstrates key factors such as device location, its affordances, and the structure of commands had a strong impact on user experience. Participants highlighted different linguistic strategies to try and overcome interaction difficulties and discussed the potential of using smart speakers for speech and language therapy. We emphasise the need to further understand the experiences of people who stammer in smart speaker design to increase their accessibility.

Casual conversation, where people engage in social talk or phatic communion (Coupland et al., 1992) (i.e., non-task oriented talk) is acknowledged as important in facilitating collaboration among c...

Limited linguistic coverage for Intelligent Personal Assistants (IPAs) means that many interact in a non-native language. Yet we know little about how IPAs currently support or hinder these users. Through native (L1) and non-native (L2) English speakers interacting with Google Assistant on a smartphone and smart speaker, we aim to understand this more deeply. Interviews revealed that L2 speakers prioritised utterance planning around perceived linguistic limitations, as opposed to L1 speakers prioritising succinctness because of system limitations. L2 speakers see IPAs as insensitive to linguistic needs resulting in failed interaction. L2 speakers clearly preferred using smartphones, as visual feedback supported diagnoses of communication breakdowns whilst allowing time to process query results. Conversely, L1 speakers preferred smart speakers, with audio feedback being seen as sufficient. We discuss the need to tailor the IPA experience for L2 users, emphasising visual feedback whilst reducing the burden of language production.