This paper evaluates the effectiveness of combining speech modification techniques that enhance transition components with active noise cancellation to improve the intelligibility of speech in noise. Two speech modification techniques were considered. One is based on wavelet-packet analysis, and the second uses a fixed filter, derived from time-frequency analysis, that emphasizes high frequencies. Active noise cancellation was provided by Bose noise-cancelling headphones. The test noise was real, generated by a ground auxiliary generator on the tarmac at an Air National Guard facility. The test signals were speech tokens from the modified rhyme (psycho-acoustic) test, recorded by a male speaker. This paradigm was used to measure word recognition rates at various signal-to-noise ratios. Active noise cancellation by itself provided over 40% increase in word recognition, while the modified speech and fixed filter techniques alone provided up to 20% improvement, depending on the signal-to-noise ratio. In combination, the speech modification approaches provided over 15% additional improvement in intelligibility over noise cancellation alone.