mirror of
https://github.com/gsi-upm/senpy
synced 2024-11-14 12:42:27 +00:00
178 lines
5.5 KiB
ReStructuredText
178 lines
5.5 KiB
ReStructuredText
Automatic Model Conversion
|
|
--------------------------
|
|
|
|
Senpy includes support for emotion and sentiment conversion.
|
|
When a user requests a specific model, senpy will choose a strategy to convert the model that the service usually outputs and the model requested by the user.
|
|
|
|
Out of the box, senpy can convert from the `emotionml:pad` (pleasure-arousal-dominance) dimensional model to `emoml:big6` (Ekman's big-6) categories, and vice versa.
|
|
This specific conversion uses a series of dimensional centroids (`emotionml:pad`) for each emotion category (`emotionml:big6`).
|
|
A dimensional value is converted to a category by looking for the nearest centroid.
|
|
The centroids are calculated according to this article:
|
|
|
|
.. code-block:: text
|
|
|
|
Kim, S. M., Valitutti, A., & Calvo, R. A. (2010, June).
|
|
Evaluation of unsupervised emotion models to textual affect recognition.
|
|
In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text (pp. 62-70).
|
|
Association for Computational Linguistics.
|
|
|
|
|
|
|
|
It is possible to add new conversion strategies by `Developing a conversion plugin`_.
|
|
|
|
|
|
Use
|
|
===
|
|
|
|
Consider the following query to an emotion service: http://senpy.gsi.upm.es/api/emotion-anew?i=good
|
|
|
|
The requested plugin (emotion-random) returns emotions using the VAD space (FSRE dimensions in EmotionML):
|
|
|
|
.. code:: json
|
|
|
|
|
|
[
|
|
{
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@type": "Emotion",
|
|
"emoml:pad-dimensions_arousal": 5.43,
|
|
"emoml:pad-dimensions_dominance": 6.41,
|
|
"emoml:pad-dimensions_pleasure": 7.47,
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744784.8789825"
|
|
}
|
|
],
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744784.8789825"
|
|
}
|
|
]
|
|
|
|
|
|
|
|
|
|
To get the equivalent of these emotions in Ekman's categories (i.e., Ekman's Big 6 in EmotionML), we'd do this:
|
|
|
|
http://senpy.gsi.upm.es/api/emotion-anew?i=good&emotion-model=emoml:big6
|
|
|
|
This call, provided there is a valid conversion plugin from Ekman's to VAD, would return something like this:
|
|
|
|
.. code:: json
|
|
|
|
[
|
|
{
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@type": "Emotion",
|
|
"onyx:algorithmConfidence": 4.4979,
|
|
"onyx:hasEmotionCategory": "emoml:big6happiness"
|
|
}
|
|
],
|
|
"prov:wasDerivedFrom": {
|
|
"@id": "Emotions0",
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@id": "Emotion0",
|
|
"@type": "Emotion",
|
|
"emoml:pad-dimensions_arousal": 5.43,
|
|
"emoml:pad-dimensions_dominance": 6.41,
|
|
"emoml:pad-dimensions_pleasure": 7.47,
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562745220.1553965"
|
|
}
|
|
],
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562745220.1553965"
|
|
},
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562745220.1570725"
|
|
}
|
|
]
|
|
|
|
|
|
That is called a *full* response, as it simply adds the converted emotion alongside.
|
|
It is also possible to get the original emotion nested within the new converted emotion, using the `conversion=nested` parameter:
|
|
|
|
http://senpy.gsi.upm.es/api/emotion-anew?i=good&emotion-model=emoml:big6&conversion=nested
|
|
|
|
.. code:: json
|
|
|
|
[
|
|
{
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@type": "Emotion",
|
|
"onyx:algorithmConfidence": 4.4979,
|
|
"onyx:hasEmotionCategory": "emoml:big6happiness"
|
|
}
|
|
],
|
|
"prov:wasDerivedFrom": {
|
|
"@id": "Emotions0",
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@id": "Emotion0",
|
|
"@type": "Emotion",
|
|
"emoml:pad-dimensions_arousal": 5.43,
|
|
"emoml:pad-dimensions_dominance": 6.41,
|
|
"emoml:pad-dimensions_pleasure": 7.47,
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744962.896306"
|
|
}
|
|
],
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744962.896306"
|
|
},
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744962.8978968"
|
|
}
|
|
]
|
|
|
|
|
|
|
|
Lastly, `conversion=filtered` would only return the converted emotions.
|
|
|
|
|
|
.. code:: json
|
|
|
|
[
|
|
{
|
|
"@type": "EmotionSet",
|
|
"onyx:hasEmotion": [
|
|
{
|
|
"@type": "Emotion",
|
|
"onyx:algorithmConfidence": 4.4979,
|
|
"onyx:hasEmotionCategory": "emoml:big6happiness"
|
|
}
|
|
],
|
|
"prov:wasGeneratedBy": "prefix:Analysis_1562744925.7322266"
|
|
}
|
|
]
|
|
|
|
Developing a conversion plugin
|
|
==============================
|
|
|
|
Conversion plugins are discovered by the server just like any other plugin.
|
|
The difference is the slightly different API, and the need to specify the `source` and `target` of the conversion.
|
|
For instance, an emotion conversion plugin needs the following:
|
|
|
|
|
|
.. code:: yaml
|
|
|
|
|
|
---
|
|
onyx:doesConversion:
|
|
- onyx:conversionFrom: emoml:big6
|
|
onyx:conversionTo: emoml:fsre-dimensions
|
|
- onyx:conversionFrom: emoml:fsre-dimensions
|
|
onyx:conversionTo: emoml:big6
|
|
|
|
|
|
|
|
.. code:: python
|
|
|
|
|
|
class MyConversion(EmotionConversionPlugin):
|
|
|
|
def convert(self, emotionSet, fromModel, toModel, params):
|
|
pass
|
|
|
|
|
|
More implementation details are shown in the `centroids plugin <https://github.com/gsi-upm/senpy/blob/master/senpy/plugins/postprocessing/emotion/centroids.py>`_.
|