Speech processing can often take place in adverse listening conditions that involve the mixing of speech and background noise. In this study, we investigated processing dependencies between background noise and indexical speech features, using a speeded classification paradigm (Garner, 1974; Exp. 1), and whether background noise is encoded and represented in memory for spoken words in a continuous recognition memory paradigm (Exp. 2). Whether or not the noise spectrally overlapped with the speech signal was also manipulated. The results of Experiment 1 indicated that background noise and indexical features of speech (gender, talker identity) cannot be completely segregated during processing, even when the two auditory streams are spectrally nonoverlapping. Perceptual interference was asymmetric, whereby irrelevant indexical feature variation in the speech signal slowed noise classification to a greater extent than irrelevant noise variation slowed speech classification. This asymmetry may stem from the fact that speech features have greater functional relevance to listeners, and are thus more difficult to selectively ignore than background noise. Experiment 2 revealed that a recognition cost for words embedded in different types of background noise on the first and second occurrences only emerged when the noise and the speech signal were spectrally overlapping. Together, these data suggest integral processing of speech and background noise, modulated by the level of processing and the spectral separation of the speech and noise.