15. The speech recognition apparatus according to claim 13, wherein for x(k)=(t,j),k-1.gtoreq.n.gtoreq.1, the matching path includes either of (1) x(k-1)=(t-1,j-n) or x(k-1)=(t-1,j), (2) x(k-1)=(t-1,j-1) or x(k-1)=(t-1,j), x(k-m)=(t-1,j-m) for m=2, . . . ,n, (3) x(k-m)=(t,j-m), x(k-n)=(t-1,j-n) for m=1, . . . ,n-1, (4) x(k-m)=(t,j-m), x(k-n)=(t-1,j-n) for m=1, . . . ,n-1 and (5) x(k-1)=(t-1,j-1) or x(k-1)=(t-1,j), x(k-m)=(t-1,j-m) for m=2, . . . ,n and w(x(k))=1 for the path(1), w(x(k))=1,w(x(k-m+1))=0 for the path(2), w(x(K-m+1))=0, w(x(k-n+1))=1 for the path(3) and w(x(k-m+1))=1/n for the paths (4) and (5).
13. 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 of a.sub.t(k) and b.sub.j(k) is specified as below, ##EQU79## and an accumulated similarity degree along the path of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) is specified as below, ##EQU80## wherein for 1.ltoreq.n.ltoreq.k-1, if t(k)-t(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1.