Bias Mitigation Against Non-native Speakers in Dutch ASR

One of the most important problems that needs tackling for wide deployment of Automatic Speech Recognition (ASR) is the bias in ASR, i.e., ASRs tend to generate more accurate predictions for certain speaker groups while making more errors on speech from others. In this thesis, we aim to reduce bias against non-native speakers of Dutch compared...

Evaluating the Effect of SpecSwap for Purposes of Improving WER Performance of the Western Dutch Region Using the JASMIN-CGN Dataset

A problem prevalent in many modern-day Automatic Speech Recognition (ASR) systems is the presence of bias and its reduction. Bias can be observed when an ASR system performs worse on a subset of its speakers compared to the rest rather than having the same overall generalization for everyone. This can be seen by using Word Error Rates (WER) as a...