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Towards the automation of book typesetting: Conclusion

Towards the automation of book typesetting: Conclusion

Authors:

(1) Sérgio M. Rebelo, University of Coimbra, Centre for Informatics and Systems, University of Coimbra, Faculty of Computer Engineering, Coimbra, Portugal and corresponding author;

(2) Tiago Martins, University of Coimbra, Centre for Informatics and Systems, University of Coimbra, Faculty of Computer Engineering, Coimbra, Portugal and corresponding author;

(3) Diogo Ferreira, University of Coimbra, Centre for Informatics and Systems, University of Coimbra, Faculty of Computer Engineering, Coimbra, Portugal and corresponding author;

(4) Artur Rebelo, University of Coimbra, Centre for Informatics and Systems, University of Coimbra, Faculty of Computer Engineering, Coimbra, Portugal.

5. Conclusion

We have presented a novel approach to computer-aided book design. The presented system implements a generative design process that leverages the scripting capabilities of Adobe InDesign to procedurally typeset books from user-provided content. We have shown that the system is capable of (i) producing book designs that consistently conform to a set of typographic rules, styles, and principles reported in the literature, (ii) producing visually distinct books from the same input content, and (iii) producing visually coherent books with distinct content.

The work presented in this paper may challenge the typical roles of the tool and the designer. First, by automatically generating and recommending design alternatives, the tool plays a more active role in the design process. Second, by modifying and developing custom tools, the designer is no longer just a tool user, but becomes the author of tools tailored to specific requirements. We believe that this shift can be fruitful, as it enables the exploration and discovery of new technical and creative possibilities.

This work can hopefully provide guidance for further research on generative processes to support design research and the search for unique designs. In the specific case of typography, generative approaches such as the one presented in this article can be useful and reveal great potential, especially in the current print-on-demand market and in digital publishing, where each publication can be unique.

Our future work will move towards applying artificial intelligence techniques, such as evolutionary computation and machine learning, to enable deeper exploration of the vast range of book designs that can be achieved with the system and to automatically suggest settings to designers according to their needs or goals.