Digital multimedia systems are creating many new opportunities for rapid access to content archives. In order to explore these collections using search applications, the content must be annotated with significant features. An important and often overlooked aspect of human interpretation of multimedia data is the affective dimension. Affective labels of content can be extracted automatically from within multi-media data streams. These can then be used for content-based retrieval and browsing. In this study affective features extracted from multimedia audio content are mapped onto a set of keywords with predetermined emotional interpretations. These labels are then used to demonstrate affect-based retrieval on a range of feature films.