ASSESSMENT OF AUTOMATIC SPEAKER VERIFICATION ON LOSSY TRANSCODED SPEECH

In this paper, we investigate the effect of lossy speech compression on text-independent speaker verification task. We have evaluated the voice biometrics performance over several state-of-the art speech codecs including recently released Enhanced Voice Services (EVS) codec. The tests were performed in both codec-matched and codec-mismatched scenarios. The test results show that EVS outperforms other speech codecs used in our test and it can be used to generate speaker models that are quite robust to varying compression levels. It was also shown that if a speech codec of higher quality (EVS, G711) is included in training data (mismatched and partially mismatched scenarios), the automatic speaker verification (ASV) gives better results than in the case of matched scenario.