The classical Fourier transform with sliding time window may be inefficient for the characterisation of short events in speech, such as stop consonants, because of a non-adapted time-frequency compromise. In order to investigate this hypothesis, the basic Fourier analysis was compared to two multiresolution methods: a double Fourier transform with two simultaneous windows, varying in size, and a wavelet representation. Our signal processing was tested on the six French stop consonants according to a model of the French cochlear implant Digisonic (which uses the basic Fourier analysis). The stop consonants were analysed with both multiresolution methods, and then processed using cochlear implant specific processing. An automatic recognition was performed, and simulations of stop consonants perceived by implantees were presented to normal-hearing subjects. The results have not shown an improvement with the multiresolution techniques over the classical FFT analysis.