Documentation Guide for VERN

Making a Request

V.E.R.N. can be accessed via an API by POST request to http://vern.stage.vernai.com/analyze

V.E.R.N. requires the following Header configuration. Replace the Authorization value with your API Key.

Header: {
'Authorization': 'XXXXX:XXXXXXXXXXX',
'Content-Type': 'application/json',
'Accept': 'application/json'
}

Send the message you would like analyzed via the “text” key in the POST form data.

Body: {
text: "Sample message"
}

Response

V.E.R.N. returns the following JSON response. It includes the message that was analyzed along with a breakdown of the confidence rating on a scale of 0.00 to 100.00

{
"text": "Sample message",
"scores": [
{
"name": "sadness",
"value": 0
},
{
"name": "anger",
"value": 12.5
},
{
"name": "humor",
"value": 0
}
]
}

Understanding the Results

V.E.R.N. scores the results of an analysis on a percent confidence scale between 0.00 – 100.00. The higher the confidence rating, the more likely the detected emotion exists within the message. Our current standard is that a rating of 51% shows a statistical significant likelihood the emotion is present.

A single message may contain multiple emotions cues as we tend to package a lot of data when we communicate in order to convey complex emotions. More complex emotions may be found through the combinations of core emotives (Humor, Anger, Sadness, Happiness).

The applications of V.E.R.N. can vary based on the context being applied. They can either be used to help score communication for emotional content or be used within the context of a decision matrix where specific responses are triggered if an emotional threshold is reached.

V.E.R.N. emotional recognition AI enables system understanding of human emotions.

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