Patent Document ID: 5457770
Application ID: 08108791

Base Claim:
1. An apparatus comprising: a) input means for inputting an utterance by an unspecified person into an electrical signal; b) characteristic extracting means for receiving the electrical signal from the input means and converting the electrical signal into a time series of discrete characteristic multidimensional vectors; c) phoneme recognition means for receiving the time series of discrete characteristic multidimensional vectors and converting each of said vectors into a time series of phoneme discriminating scores calculated thereby; d) a dictionary for pre-storing a reference pattern for each word to be recognized, each reference pattern comprising at least one phoneme label comprising a continuation time length for each phoneme stored in a data base of said dictionary, said continuation time length being uniformly set to a predetermined time length; e) word recognition means for comparing an input time series of phoneme discriminating scores derived from said phoneme recognition means with each reference pattern stored in said dictionary using a predetermined Dynamic Programming technique so that one of the reference patterns having a maximum matching score to the time series of discriminating scores is a result of word recognition; and f) output means for outputting the word based on the result of word recognition using said word recognition means in an encoded form thereof.

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Claim 2:
2. An apparatus as set forth in claim 1, wherein in said phoneme recognition means continuity of frames representing the respective characteristic vectors and said predetermined Dynamic Programming technique has a matching score gk(i, j) between an i frame input series of phonemes and a j number phoneme of one of reference patterns k derived as: ##EQU3## wherein ak(i, j) denotes an output score value of Neural Networks constituting a phoneme recognition block in the case where an i frame phoneme corresponds to a j number phoneme of a reference pattern k and p denotes a penalty constant to avoid an extreme shrinkage of a series of phonemes input from the Neural Networks, and a total matching score of gk(I, J) is derived when the number of frames of an input series of phonemes is I and the numbers of phonemes of the reference pattern k is J.