The performance of current automatic speech recognition (ASR) systems is very sensitive to the presence of room reverberation in the incoming speech signal. We investigate a family of front-end speech representations that focus on slow changes in the the gross spectral structure of speech for their ability to improve the robustness of ASR systems to reverberation. A number of the front ends provide a statistically significant improvement in performance over established front ends such as PLP; however, the performance of ASR systems on highly reverberant speech is still disappointing when compared with the performance of human listeners.