An Event-Driven Distribution Model for Automatic Insertion of Illustrations in Narrative Discourse: A Study Based on the Shahnama Narrative
Mahdavi, M Amin
Book designers and manuscript artists have inserted illustrations into narrative works for centuries now. This practice is an intelligent behaviour that requires specialised knowledge of the text and the external parameters affecting the selection and placement criteria. This thesis offers a model for automation of illustration insertion into a narrative discourse. The model presented here is a significant improvement to the crudest method of dividing the text into equal parts and inserting one illustration into each part. This study starts from the position that narratives are expressions of mental representations of a sequence of events in various modes of discourse. Here, this mental representation is referred to as ‘the story’. When coupled with a mode of discourse, the story becomes a narrative. Thus, a story can be expressed as oral, written, pictorial, or film narratives. If they all express the same sequence of events, they are telling the same story. In an illustrated narrative, while the written discourse expresses the event sequence in the form of sentences, illustrations depict them using pictorial elements. The insertion of illustration into written narrative is analogous to collating two texts into one, based on their event content. In this process, sentential representation of events are collated against the pictorial expressions of the same events. Thus, for the purposes of automation, this study claims that an investigation into the locations of events can lead to potential locations for illustration insertions. However, the list of potential illustration locations can be improved further through eliminating the events that are not depictable. This model is also able to further improve on the insertion policy by incorporating event constraints as parameters for event priorities. If a set of event types is given preference in the illustration policy, the model is able to prioritise the list accordingly. Furthermore, the model is able to allow the samedegree of customisation for preferred characters, locations, or time in the story. The prioritisation can be applied to the entire narrative, or smaller chunks of the narrative text such as chapters or sections. The model is developed via the study of the verb roots of sentences – denoting the event types – in the discourse of Mohl’s critical edition of the Shāhnāma, the Persian epic composed by Abu al Qāsium Firdausī in 400/1010. A collection of 109 illustrated manuscripts of the Shāhnāma was considered in this study. These manuscripts come from various traditions of Persian paintings and cover a long period from the early 14th century to the late 19th century. A population of nearly 6,000 Shāhnāma illustrations were annotated. Each illustration is linked to a sentence in the narrative. The bottom-up approach to the study of verb distribution in the written discourse against the illustration location distribution indicates that illustration distribution follows the same trend as that of the depictable event distribution in the discourse. Particular event tokens displayed a high rate of illustration rendering them as all time favourite events. In summary, this study claims that investigation into the distribution of events in a narrative discourse provides a model for the insertion of illustrations into a narrative work.