1. A language understanding device comprising: a language understanding model storing unit configured to store, as a language understanding model, word transition data, filler transition data and concept weighting data, said word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, filler transition data including pre-transition states, fillers matching an arbitrary word, filler weight information, and post-transition states, and said concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates based on words included in a word sequence being input which is obtained by a speech recognition process and present states, said understanding result candidates including the predefined outputs, and in accordance with the word transition data read out from the language understanding model storing unit, to accumulate word weights so as to obtain a cumulative word weight as a numeric value for each of the understanding result candidates, and to sequentially perform state transition operations by which transitions to the post-transition states are carried out; the finite state transducer processing unit is further configured to accumulate filler weights in accordance with the filler transition data read out from the language understanding model storing unit so as to obtain a cumulative filler weight as a numeric value for each of the understanding result candidates, and to perform the state transition operations by which transition to the post-transition states are carried out; a concept weighting processing unit configured to accumulate concept weights, which correspond to the concepts included in the understanding result candidates output from the finite state transducer processing unit, in accordance with the concept weighting data read out from the language understanding model storing unit so as to obtain a cumulative concept weight as a numeric value for each of the understanding result candidates; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates based on the cumulative word weight, the cumulative filler weight and the cumulative concept weight for each understanding result candidate, wherein the understanding result determination unit is configured to determine the understanding result as the understanding result candidate having a highest value for a summed cumulative word weight, cumulative filler weight and cumulative concept weight.
1. A language understanding device comprising: a language understanding model storing unit configured to store, as a language understanding model, word transition data, filler transition data and concept weighting data, said word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, filler transition data including pre-transition states, fillers matching an arbitrary word, filler weight information, and post-transition states, and said concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates based on words included in a word sequence being input which is obtained by a speech recognition process and present states, said understanding result candidates including the predefined outputs, and in accordance with the word transition data read out from the language understanding model storing unit, to accumulate word weights so as to obtain a cumulative word weight as a numeric value for each of the understanding result candidates, and to sequentially perform state transition operations by which transitions to the post-transition states are carried out; the finite state transducer processing unit is further configured to accumulate filler weights in accordance with the filler transition data read out from the language understanding model storing unit so as to obtain a cumulative filler weight as a numeric value for each of the understanding result candidates, and to perform the state transition operations by which transition to the post-transition states are carried out; a concept weighting processing unit configured to accumulate concept weights, which correspond to the concepts included in the understanding result candidates output from the finite state transducer processing unit, in accordance with the concept weighting data read out from the language understanding model storing unit so as to obtain a cumulative concept weight as a numeric value for each of the understanding result candidates; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates based on the cumulative word weight, the cumulative filler weight and the cumulative concept weight for each understanding result candidate, wherein the understanding result determination unit is configured to determine the understanding result as the understanding result candidate having a highest value for a summed cumulative word weight, cumulative filler weight and cumulative concept weight. 2. The language understanding device according to claim 1 , the language understanding model storing unit is further configured to store the word weight information and the concept weight information which are determined depending on speech recognition accuracy during the speech recognition process, and the understanding result determination unit is further configured to determine the understanding result based on the cumulative word weight obtained based on the word weight information which depends on the speech recognition accuracy and the cumulative concept weight obtained based on the concept weight information which depends on the speech recognition accuracy for each understanding result candidate.