Interacting with large music collections: Towards the use of environmental metadata

Large music collections afford the listener flexibility in the form of choice, which enables the listener to choose the appropriate piece of music to enhance or complement their listening scenario on-demand. However, bundled with such a large music collection is the demanding task of manually searching through each entry in the collection to find the appropriate song required by the listener. This paper highlights the need for contextual and environmental information, which ultimately defines the listener's listening scenario. Here, the preliminary results of an online music survey are analysed. These results indicate the possibility of how environmental features may be used as metadata to indicate the listener's mood. Therefore, environmental features, such as location, activity, temperature, lighting and weather have great potential as metadata and hence may be used to create a personalised automatic playlist generator for large music collections.