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Difference between revisions of "Cleaning for Poems"

From Algolit

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For this exhibition we're working with 3% of the Mundaneum's archive. These documents have first been scanned or photographed. To make the documents searchable they are transformed into text using Optical Character Recognition software (OCR). OCR are algorithmic models that are trained on other texts. They have learned to identify characters, words, sentences and paragraphs. The software often makes 'mistakes'. It might recognize a wrong character, it might get confused by a stain an unusual font or the other side of the page shining through.  
 
For this exhibition we're working with 3% of the Mundaneum's archive. These documents have first been scanned or photographed. To make the documents searchable they are transformed into text using Optical Character Recognition software (OCR). OCR are algorithmic models that are trained on other texts. They have learned to identify characters, words, sentences and paragraphs. The software often makes 'mistakes'. It might recognize a wrong character, it might get confused by a stain an unusual font or the other side of the page shining through.  
  
While these mistakes are often considered noise, confusing the training, they can also be seen as poetic interpretations of the algorithm. They show us the limits of the machine. And they also reveal how the algorithm might work, what material it has seen in training and what is new, they say something about the standards of it's makers. In this installation you can choose how you treat the algorithm's misreadings, pick your degree of poetic cleanness, print your poem and take it home.  
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While these mistakes are often considered noise, confusing the training, they can also be seen as poetic interpretations of the algorithm. They show us the limits of the machine. And they also reveal how the algorithm might work, what material it has seen in training and what is new, they say something about the standards of it's makers. In this installation we ask your help in verifying our dataset. As a reward we'll present you with a personal algorithmic improvisation.
  
 
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Revision as of 09:26, 13 March 2019

by Algolit

For this exhibition we're working with 3% of the Mundaneum's archive. These documents have first been scanned or photographed. To make the documents searchable they are transformed into text using Optical Character Recognition software (OCR). OCR are algorithmic models that are trained on other texts. They have learned to identify characters, words, sentences and paragraphs. The software often makes 'mistakes'. It might recognize a wrong character, it might get confused by a stain an unusual font or the other side of the page shining through.

While these mistakes are often considered noise, confusing the training, they can also be seen as poetic interpretations of the algorithm. They show us the limits of the machine. And they also reveal how the algorithm might work, what material it has seen in training and what is new, they say something about the standards of it's makers. In this installation we ask your help in verifying our dataset. As a reward we'll present you with a personal algorithmic improvisation.


Concept, code, interface: Gijs de Heij