16. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree calculating means for calculating the distance or the similarity degree specifies the similarity degree of a.sub.t(k) and b.sub.j(k) as follows, ##EQU81## and the similarity degree of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) along the path is specified as follows, ##EQU82## where for 1.ltoreq.n.ltoreq.k-1, if j(k)-j(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1.
16. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree calculating means for calculating the distance or the similarity degree specifies the similarity degree of a.sub.t(k) and b.sub.j(k) as follows, ##EQU81## and the similarity degree of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) along the path is specified as follows, ##EQU82## where for 1.ltoreq.n.ltoreq.k-1, if j(k)-j(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1. 17. The speech recognition apparatus according to claim 16, wherein the matching path is specified as j(k)-j(k-1)=1 and w(x(k))=1.