Understand TPR, FPR, FAR, FRR and EER Metrics in Voiceprint Recognition – Machine Learning Tutorial

By | June 21, 2022

In order to evaluate a voiceprint recognition model, we need compute eer metric. In this tutorial, we will introduce some metrics TPR, FPR, FAR, FRR to help you understand how to compute ERR.

TPR and FPR

TPR and FPR can be computed as follows:

TPR = TP / (TP + FN)

FPR = FP / (FP + TN)

TPR vs FPR in machine learning

You can learn more on these two metrics in here:

Understand TPR, FPR, Precision and Recall Metrics in Machine Learning – Machine Learning Tutorial

FAR and FRR

This tutorial gives us some basic introduction on them.

Compute FAR, FRR and EER Metrics in TensorFlow – TensorFlow Tutorial

Here:

FAR = False Acceptance Rate

FRR = False Rejection Rate

EER  =FAR = FRR

From paper: Robust Performance Metrics for Authentication Systems, we can find:

FPR is sometimes called the false accept rate (FAR). It means FPR = FAR

The false negative rate (FNR) which is alternatively called the false reject rate (FRR). It means FNR = FRR

FNR = 1-TPR = FRR

How to compute EER?

When FAR = FRR, we can get EER. Moreover, we can compute it by ROC curve.

ROC curve looks like:

EER in ROC Curve

In ROC curve, the x axis is FPR (FAR), the y axis is TPR. The line from (0, 1) and (1.0) is FRR.

Then we can compute EER easily.

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