Dynamic Noise Adaptation

We consider the problem of robust speech recognition in the car environment. We present a new dynamic noise adaptation algorithm, called DNA, for the robust front-end compensation of evolving semi-stationary noise as typically encountered in the car setting. A large dataset of in-car noise was collected for the evaluation of the new algorithm. This dataset was combined with the Aurora II framework to produce a new, publicly available framework, called DNA + AURORA II, for the evaluation of adaptive noise compensation algorithms. We show that DNA consistently outperforms several existing, related state-of-the-art front-end denoising techniques