Classifying Smart Personal Assistants: An Empirical Cluster Analysis

The digital age has yielded systems that increasingly reduce the complexity of our everyday lives. As such, smart personal assistants such as Amazon’s Alexa or Apple’s Siri combine the comfort of intuitive natural language interaction with the utility of personalized and situation-dependent information and service provision. However, research on SPAs is becoming increasingly complex and opaque. To reduce complexity, this paper introduces a classification system for SPAs. Based on a systematic literature review, a cluster analysis reveals five SPA archetypes: Adaptive Voice (Vision) Assistants, Chatbot Assistants, Embodied Virtual Assistants, Passive Pervasive Assistants, and Natural Conversation Assistants

A Personalized System for Conversational Recommendations

Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as movies or restaurants, but are still somewhat awkward to use. Our solution is to take advantage of the complementary strengths of personalized recommendation systems and dialogue systems, creating personalized aides. We present a system -- the Adaptive Place Advisor -- that treats item selection as an interactive, conversational process, with the program inquiring about item attributes and the user responding. Individual, long-term user preferences are unobtrusively obtained in the course of normal recommendation dialogues and used to direct future conversations with the same user. We present a novel user model that influences both item search and the questions asked during a conversation. We demonstrate the effectiveness of our system in significantly reducing the time and number of interactions required to find a satisfactory item, as compared to a control group of users interacting with a non-adaptive version of the system

Learning how to learn: an adaptive dialogue agent for incrementally learning visually grounded word meanings

We present an optimised multi-modal dialogue agent for interactive learning of visually grounded word meanings from a human tutor, trained on real human-human tutoring data. Within a life-long interactive learning period, the agent, trained using Reinforcement Learning (RL), must be able to handle natural conversations with human users and achieve good learning performance (accuracy) while minimising human effort in the learning process. We train and evaluate this system in interaction with a simulated human tutor, which is built on the BURCHAK corpus -- a Human-Human Dialogue dataset for the visual learning task. The results show that: 1) The learned policy can coherently interact with the simulated user to achieve the goal of the task (i.e. learning visual attributes of objects, e.g. colour and shape); and 2) it finds a better trade-off between classifier accuracy and tutoring costs than hand-crafted rule-based policies, including ones with dynamic policies.Comment: 10 pages, RoboNLP Workshop from ACL Conferenc

User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

The Fairy Language: Language Maintenance and Social-Ecological Resilience Among the Tarali of Tichurong, Nepal

Sahar Tara is a community in Dolpa, Nepal, one of three villages in the world where the Kaike language is spoken. Kaike speakers are called Tarali. The perpetuation of the Kaike language is attributable to the resilience of Tarali livelihood systems and their continued attachment to place. Using informal interviews, participatory mapping, and participant observation, this research engaged Kaike speakers in an exploration of the relationships among their language, environment, and knowledge systems. Tarali negotiate their social and spiritual lives through highly developed adaptive knowledge about the environment, mitigated by natural forces, deities, and intimate historical ties to the land. As explicitly revealed in the story about the origins of the Kaike language, Tarali define themselves and their collective history in the Tichurong Valley concurrent with their conceptualization and cognition of the landscape. This is also expressed in the abundance of Kaike names with which they categorize and compartmentalize their spatial understandings of where they live and work. Tarali situate themselves on their land and in their environment through site-specific traditions of remembering in the form of oral histories and social narratives, highlighting the important role of language in perpetuating these traditions. In this place-based community where one’s livelihood depends on successful interaction with and adaptation to the specific ecological conditions of Tichurong, language acts as a mediator in articulating social-ecological relationships. This adaptive knowledge is transmitted across generations through Kaike and the continued reenactment of ceremonies, worship, and a particular physical and geographical occupation of space. The maintenance of the Kaike language is dependent upon the resilience afforded by this sustained engagement with a place-based livelihood system