A new concept is proposed that relates to intelligibility of speech in noise. The concept combines traditional estimations of signal-to-noise ratios (S/N) with elements from the modulation transfer function model, which results in the definition of the signal-to-noise ratio in the modulation domain: the (S/N)mod. It is argued that this (S/N)mod, quantifying the strength of speech modulations relative to a floor of spurious modulations arising from the speech-noise interaction, is the key factor in relation to speech intelligibility. It is shown that, by using a specific test signal, the strength of these spurious modulations can be measured, allowing an estimation of the (S/N)mod for various conditions of additive noise, noise suppression, and amplitude compression. By relating these results to intelligibility data for these same conditions, the relevance of the (S/N)mod as the key factor underlying speech intelligibility is clearly illustrated. For instance, it is shown that the commonly observed limited effect of noise suppression on speech intelligibility is correctly “predicted” by the (S/N)mod, whereas traditional measures such as the speech transmission index, considering only the changes in the speech modulations, fall short in this respect. It is argued that (S/N)mod may provide a relevant tool in the design of successful noise-suppression systems.