Method of speech recognition

Claim 1

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1 .sup.(k)(i-h) R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value R J .sup.(k)(i).

Claim 2

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1 .sup.(k)(i-h) R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value R J .sup.(k)(i).

Claim 5

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1.sup.(k)(i-1),R.sub.j-1.sup.(k)(i-2),R.sub.j-1.sup.(k)(i-3), . . . ,R.sub.j-1.sup.(k)(i-4)) where j=2, 3, . . . , J; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value R J .sup.(k)(i).

Claim 6

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1.sup.(k)(i-1),R.sub.j-1.sup.(k)(i-2),R.sub.j-1.sup.(k)(i-3), . . . ,R.sub.j-1.sup.(k)(i-4)) where j=2, 3, . . . , J; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value R J .sup.(k)(i).

Claim 7

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+opt(R.sub.j-1.sup.(k)(i-h),R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character opt denotes an operator of selecting an optimal member of terms in related parentheses; deriving an optimal value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the optimal value R J .sup.(k)(i).

Claim 8

A method of speech recognition, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number variable as k=1, 2 . . . , K, the letter J denotes a predetermined natural number common for all the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+opt(R.sub.j-1.sup.(k)(i-h),R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character opt denotes an operator of selecting an optimal member of terms in related parentheses; deriving an optimal value R J .sup.(k)(i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the optimal value R J .sup.(k)(i).

Claim 11

A method of speech recognition using word spotting, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number and is variable in the range k=1, 2 . . . , K, the letter J denotes a predetermined natural number corresponding to a common length of standard pattern for each of the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; and a matching process based on non-linear expansion and contraction, including: calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1.sup.(k)(i-h),R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value of R J .sup.(k) (i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value of R J .sup.(k)(i).

Claim 12

A method of speech recognition using word spotting, comprising the steps of: predetermining a series of parameter vectors a 1 .sup.(k), a 2 .sup.(k), . . . , a J .sup.(k) representative of standard patterns of speeches of preset words (k) respectively, where the letter k denotes a preset-word identifying number and is variable in the range k=1, 2 . . . , K, the letter J denotes a predetermined natural number corresponding to a common length of standard pattern for each of the preset words and the letter K denotes a predetermined natural number representing a vocabulary size; deriving parameter vectors x i representative of data of respective frames of an input signal, wherein the adscript i denotes a frame number; calculating similarities d j .sup.(k) (i) between the parameter vectors a j .sup.(k) and the parameter vectors x i by using a formula: d.sub.j.sup.(k) (i)=a.sub.j.sup.(k) ·x.sub.i, where j=1, 2, . . . , J; and a matching process based on non-linear expansion and contraction, including: calculating parameters R j .sup.(k)(i) for the respective preset words by referring to the following recurrence formulas: R.sub.1.sup.(k)(i) =d.sub.1.sup.(k) (i) R.sub.j.sup.(k)(i) =d.sub.j.sup.(k) (i)+max (R.sub.j-1.sup.(k)(i-h),R.sub.j-1.sup.(k)(i-h-1),R.sub.j-1.sup.(k)(i-h-2), . . . ,R.sub.j-1.sup.(k)(i-h-m)) where j=2, 3, . . . , J; the characters h and m denote preset positive integers; and the character max denotes an operator of selecting a maximal member of terms in related parentheses; deriving a maximum value of R J .sup.(k) (i) for each k and each i; and determining one of the preset words as a recognition result, the determined word corresponding to the maximum value of R J .sup.(k)(i).