Class ContentSafetyLabels

Simply include the content_safety parameter in your POST request when submitting audio files for transcription, and set this parameter to true.

Once the transcription is complete, and you get the result, there will be an additional key content_safety_labels in the JSON response. Below, we'll drill into the data that is returned in the content_safety_labels key.

Each label will be returned with a confidence score and a severity score. It is important to note that these two keys measure two very different things. The severity key will produce a score that shows how severe the flagged content is on a scale of 0–1. For example, a natural disaster with mass casualties would be a 1, whereas a wind storm that broke a lamppost would be a 0.1.

In comparison, confidence displays how confident the model was in predicting the label it predicted, also on a scale of 0-1.

We can break this down further by reviewing the following label:

    "labels": [
        {
            "label": "health_issues",
            "confidence": 0.8225132822990417,
            "severity": 0.15090347826480865
        }
    ],

In the above example, the Content Safety model is indicating it is 82.25% confident that the spoken content is about Health Issues; however, it is measured at a low severity of 0.1509. This means the model is very confident the content is about health issues, but the content was not severe in nature (ie, was likely about a minor health issue).

The severity_score_summary key lists each label that was detected along with low, medium, and high keys.

    "severity_score_summary": {
        "health_issues": {
            "low": 0.7210625030587972,
            "medium": 0.2789374969412028,
            "high": 0.0
        }
    }

The value of the low, medium, and high keys reflect the API's confidence that the label is "low," "medium," or "high" in severity throughout the entire audio file. This score is based on the intersection of the length of the audio file, the frequency of low/medium/high severity tags through the file, and the confidence score for each of those occurrences.

By default, the content safety model will return any label with a confidence of 50% or greater. If you wish to set a higher or lower threshold, simply add the content_safety_confidence: {number} parameter to your POST request. This parameter will accept an integer value between 25 and 100, inclusive.