Opera Rolandi archive: Difference between revisions

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|12.11. (week 9)
|12.11. (week 9)
|Step 1: Segmentation model training, fine tuning & testing
|Step 1: Segmentation model training, fine tuning & testing
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|19.11. (week 10)
|19.11. (week 10)
|Step 2: Information extraction & cleaning
|Step 2: Information extraction & cleaning
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|26.11. (week 11)
|26.11. (week 11)
|Finishing Step 2
|Finishing Step 2
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|03.12. (week 12)
|03.12. (week 12)
|Step 3: Information storing & network visualization
|Step 3: Information storing & network visualization
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|10.12. (week 13)
|10.12. (week 13)
|Finishing Step 3 and Finalize Report and Wikipage (Step 4: Generalization)
|Finishing Step 3 and Finalize Report and Wikipage (Step 4: Generalization)
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|17.12. (week 14)
|17.12. (week 14)
| Final Presentation
| Final Presentation
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Revision as of 09:34, 14 November 2020

Abstract

The Fondazione Giorgio Cini has digitized 36000 pages from Ulderico Rolandi's opera libretti collection. This collection contains contemporary works of 17th- and 18th-century composers. These opera libretti have a diverse content, which offered us a large amount of possibilities for analysis.

This project chose to concentrate on a way to illustrate the characters’ interactions in the Rolandi's libretti collection through network visualization. We also highlighted the importance of each character in the libretto they figure in. To achieve this, we retrieved important information using Deep Learning models and OCR. We started from a subset of Rolandi’s libretti collection and generalized this algorithm for all Rolandi’s libretti collection.

Planning

Week To do
12.11. (week 9) Step 1: Segmentation model training, fine tuning & testing
19.11. (week 10) Step 2: Information extraction & cleaning
26.11. (week 11) Finishing Step 2
03.12. (week 12) Step 3: Information storing & network visualization
10.12. (week 13) Finishing Step 3 and Finalize Report and Wikipage (Step 4: Generalization)
17.12. (week 14) Final Presentation

Resources

Methodology

Challenges

Links