User:Fako Berkers/emochain: Difference between revisions

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[[Category:Prototyping]]
==Emo chain==
==Emo chain==


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<source lang="python">
<source lang="python">
{'pity': ['humiliation'], 'humiliation': ['weary'], 'angry': ['scared'], 'sarcastic': ['glum'], 'weary': ['pleased'], 'grief': ['sorry'], 'shame': ['sadness'], 'sadness': ['sadness', 'grief'], 'glum': ['happy'], 'serenity': ['angry'], 'sorry': ['shame', 'sorry', 'pity', 'serenity'], 'pleased': ['sorry'], 'scared': ['sarcastic'], 'happy': ['happy', 'EOF;']}
# the emo chain saved in a dict object
{'pity': ['humiliation'], 'humiliation': ['weary'], 'angry': ['scared'], 'sarcastic': ['glum'],  
'weary': ['pleased'], 'grief': ['sorry'], 'shame': ['sadness'], 'sadness': ['sadness', 'grief'],  
'glum': ['happy'], 'serenity': ['angry'], 'sorry': ['shame', 'sorry', 'pity', 'serenity'],  
'pleased': ['sorry'], 'scared': ['sarcastic'], 'happy': ['happy', 'EOF;']}
 
# output from a random read out of the chain
sorry shame sadness sadness sadness grief sorry serenity angry scared sarcastic glum happy happy happy happy happy happy happy happy happy happy
sorry shame sadness sadness sadness grief sorry serenity angry scared sarcastic glum happy happy happy happy happy happy happy happy happy happy
</source>
</source>
[[Category:Prototyping]]
[[Category:Markov chants]]

Latest revision as of 13:52, 14 June 2011

Emo chain

I didn't attach a new medium to the chain code. Instead I worked with the filtering of emotions out of a romantic novel text [1]. In the near future I want to perform the emotions that are generated by the chain. I will be acting to be in love with audience members while at the same time experiencing the instructed emotions. This way the system will simulate a person being in love that goes through different emotions and phases of love. The audience will get to experience that someone is in love with them fed by a wide range of constantly changing emotions. It is my intention that this simulation will give a generated experience. In the future narratives may be generated through simulations in a similar way.

Technically not much has changed since the Markov chain assignment. I just installed a filter upon the input text that makes sure only emotions are part of the chain. I got a list of emotions from a site [2]. From this list I took out the emotion "open", because it was triggered too often since a sentence like "He looked through the open door and saw ..." will falsely match this emotion. You can test the chain by downloading the emotion list, the sample chapter I used and slightly altered Markov chain code in one package here. Below is sample output containing the dictionary holding the chain and a random read out.

# the emo chain saved in a dict object
{'pity': ['humiliation'], 'humiliation': ['weary'], 'angry': ['scared'], 'sarcastic': ['glum'], 
'weary': ['pleased'], 'grief': ['sorry'], 'shame': ['sadness'], 'sadness': ['sadness', 'grief'], 
'glum': ['happy'], 'serenity': ['angry'], 'sorry': ['shame', 'sorry', 'pity', 'serenity'], 
'pleased': ['sorry'], 'scared': ['sarcastic'], 'happy': ['happy', 'EOF;']}

# output from a random read out of the chain
sorry shame sadness sadness sadness grief sorry serenity angry scared sarcastic glum happy happy happy happy happy happy happy happy happy happy