Towards a Model for Spoken Conversational Search
This work addresses the problem of formalizing user-system interactions for researchers and developers in conversational AI and information retrieval, but it is incremental as it focuses on foundational analysis rather than new methods or systems.
The paper tackled the lack of conceptualization in spoken conversational search (SCS) by exploring conversational moves in audio-only search interactions, resulting in the creation of SCSdata and the first annotation schema SCoSAS to investigate interactivity.
Conversation is the natural mode for information exchange in daily life, a spoken conversational interaction for search input and output is a logical format for information seeking. However, the conceptualisation of user-system interactions or information exchange in spoken conversational search (SCS) has not been explored. The first step in conceptualising SCS is to understand the conversational moves used in an audio-only communication channel for search. This paper explores conversational actions for the task of search. We define a qualitative methodology for creating conversational datasets, propose analysis protocols, and develop the SCSdata. Furthermore, we use the SCSdata to create the first annotation schema for SCS: the SCoSAS, enabling us to investigate interactivity in SCS. We further establish that SCS needs to incorporate interactivity and pro-activity to overcome the complexity that the information seeking process in an audio-only channel poses. In summary, this exploratory study unpacks the breadth of SCS. Our results highlight the need for integrating discourse in future SCS models and contributes the advancement in the formalisation of SCS models and the design of SCS systems.