In-vehicle Noise and Enhanced Speech Intelligibility

In-Car speech recognition will be pervasive over the coming years. The goal of speech enhancement is to increase the quality and intelligibility of speech in a noisy environment. The focus of the present research is to evaluate the effect of speech enhancement on the intelligibility of spoken language in a moving vehicle. Here, an ECoS network is used as a model to evaluate the intelligibility. A baseline performance was established using clean speech data. This data was then mixed with various types of in-vehicle noise at several signal-to-noise ratios. Speech enhancement techniques were applied to the noisy speech data. The performance of the ECoS model was evaluated when the noisy and enhanced speech was presented. Several factors were found to affect the recognition rate, including noise type and noise volume.