Data for: Towards a Model for Spoken Conversational Search
Description of this data
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.
Experiment data files
This data is associated with the following publication:
Cite this dataset
Trippas, Johanne; Cavedon, Lawrence; Joho, Hideo; Thomas, Paul; Sanderson, Mark; Spina, Damiano (2019), “Data for: Towards a Model for Spoken Conversational Search”, Mendeley Data, v1 http://dx.doi.org/10.17632/hnh26bm7xb.1