1. A speech-recognition device which acquires an internal recognition result from its recognition processing of input speech data and an external recognition result from recognition processing of said input speech data by one or more external recognition devices external to the speech-recognition device to determine a final recognition result, the speech-recognition device comprising: memory including: an acoustic model in which feature quantities of speeches are modeled; a language model in which notations and readings of recognition-object words of the speech-recognition device are stored; and a reading dictionary in which pairs of the notations and the readings of the recognition-object words and words other than the recognition-object words are stored; and circuitry configured to: transmit said input speech data to the one or more external recognition devices; analyze the input speech data to calculate a feature vector; perform, using the acoustic model, pattern collation between the calculated feature vector and each word stored in the language model to calculate their respective acoustic likelihoods; output, as the internal recognition result, a corresponding notation, a corresponding reading, and a corresponding acoustic likelihood of top one or more high-ranking words; acquire the external recognition result from recognition processing of the input speech data by the one or more external recognition devices, extract a reading corresponding to a notation included in said external recognition result using the reading dictionary, and output a result composed of said external recognition result and the extracted reading; perform, using the acoustic model, pattern collation between the calculated feature vector and the output result to calculate an acoustic likelihood for the external recognition result; and compare the corresponding acoustic likelihood of the internal recognition result with the acoustic likelihood of the external recognition result to determine the final recognition result.
1. A speech-recognition device which acquires an internal recognition result from its recognition processing of input speech data and an external recognition result from recognition processing of said input speech data by one or more external recognition devices external to the speech-recognition device to determine a final recognition result, the speech-recognition device comprising: memory including: an acoustic model in which feature quantities of speeches are modeled; a language model in which notations and readings of recognition-object words of the speech-recognition device are stored; and a reading dictionary in which pairs of the notations and the readings of the recognition-object words and words other than the recognition-object words are stored; and circuitry configured to: transmit said input speech data to the one or more external recognition devices; analyze the input speech data to calculate a feature vector; perform, using the acoustic model, pattern collation between the calculated feature vector and each word stored in the language model to calculate their respective acoustic likelihoods; output, as the internal recognition result, a corresponding notation, a corresponding reading, and a corresponding acoustic likelihood of top one or more high-ranking words; acquire the external recognition result from recognition processing of the input speech data by the one or more external recognition devices, extract a reading corresponding to a notation included in said external recognition result using the reading dictionary, and output a result composed of said external recognition result and the extracted reading; perform, using the acoustic model, pattern collation between the calculated feature vector and the output result to calculate an acoustic likelihood for the external recognition result; and compare the corresponding acoustic likelihood of the internal recognition result with the acoustic likelihood of the external recognition result to determine the final recognition result. 8. The speech-recognition device of claim 1 , wherein the circuitry is configured to use a Viterbi algorithm for said pattern collation between the calculated feature vector and each word stored in the language model, and for said pattern collation between the calculated feature vector and the output result.