1. A speech recognition system comprising a frequency analyzer which performs frequency analysis of the input speech into a number of channels, performs logarithmic conversion and extracts a frequency spectrum, a voiced interval detector which detects voiced intervals on the basis of the said frequency spectrum, a spectrum normalizer which determines a least square fit line for the frequency spectrum and normalizes the frequency spectrum with reference to the least square fit line to provide a normalized frequency spectrum pattern, a spectrum reference pattern memory in which spectrum reference patterns are stored in advance, a spectrum similarity calculator which calculates the similarity between the said normalized spectrum pattern and a spectrum reference pattern for each of a plurality of recognition categories, and an identifier which, as the result of the spectrum similarity calculation, outputs the name of the recognition category which has the highest similarity, the speech recognition system further comprising: (a) a second feature pattern calculator which calculates a second feature pattern, said second feature pattern calculator (a) including a spectrum variation pattern calculator which, for each frame in a voiced interval, calculates for each channel, as the second feature pattern, a spectrum variation pattern which quantifies the degree and the direction of the transition between channels of the normalized spectrum with the advance of time around the said frame, and (b) a second feature reference pattern memory in which second feature reference patterns have previously been stored, said second feature reference pattern memory (b) including a spectrum variation reference pattern memory in which spectrum variation reference patterns, as said second feature reference patterns, have previously been stored, and (c) a second feature similarity calculator which calculates the similarity between the said second feature pattern and the second feature reference patterns with respect to each recognition category, said second feature similarity calculator (c) including a spectrum variation similarity calculator which calculates the similarity between the said spectrum variation pattern and the spectrum variation reference patterns with respect to each of the recognition categories, and in that (d) in the identifier, the overall similarity is calculated for each of the recognition categories by reference to both the similarity of the spectrum and the similarity of the second feature, and the category giving the largest overall similarity is output as the recognition result.