Human and machine recognition as a function of SNR

In-car automatic speech recognition (ASR) is usually evaluated by determining one single word error rate (WER) for an in-car task. This measure does not allow to look at the recogniser behaviour for different levels of noise. Yet this is interesting for car manufacturers in order to predict system performances for different speeds and different car models and thus allow to design speech based applications in a better way. It therefore makes sense to split the single WER into SNR dependent WERs, where SNR stands for the signal to noise ratio, which is an appropriate measure for the noise level. In this paper a SNR measure based on the concept of the Articulation Index is developed, which allows the direct comparison with human recognition performance. 1