Automatic Speech Recognition (ASR) and Hands Free Communication (HFC) capabilities have become prominent in the automotive industry, with over 50% of new vehicle sales equipped with some level of ASR system. With the common use of mobile personal assistants and smartphones with Bluetooth capability, customer expectations for built in ASR and HFC systems have increased significantly. The performance of these ASR and HFC systems are highly dependent on the level of background or “masking” noise that competes with the speech engine’s ability to correctly convert the driver’s speech to actionable commands. HVAC noise and environmental noise (like road and wind noise) provide high amplitudes of broadband frequency content that affects the signal to noise ratio (SNR) within the vehicle cabin, and work to mask the user’s speech. Managing this noise is a vital key to building a vehicle that meets the customer’s expectations for ASR and HFC performance. However, a Speech Recognition engineer is not likely to be the same person responsible for designing the tires, suspension, sound package and exterior body shape that define the amount of noise present in the cabin. If objective relationships can be drawn between the vehicle level performance of the ASR system, and the system level performance of the individual NVH attributes, a partnership between the groups can be brokered. Hardware can then be selected that works to meets both groups’ goals. In this paper, we examine the NVH attributes and performance metrics that relate to vehicle level ASR performance, and draw the best possible objective relationships between the two. We also examine what acoustic metrics best define the ASR performance in the presence of any kind of steady state noise.