7. A non-transitory computer-readable recording medium having recorded thereon a program containing instructions for causing a computer to execute the following steps: (a) selecting, from learning texts for a plurality of fields for generating language models for the fields, a phrase that includes a word whose appearance frequency satisfies a set condition on a field-by-field basis, and generating an identification language model for identifying the field of input speech using the selected phrases; (b) executing speech recognition on the input speech using the identification language model, and outputting text data and a confidence for each word included in the text data as a recognition result; and (c) specifying a field that includes the most words whose confidences are greater than or equal to a set value based on the text data, the confidences of the words, and the words included in the learning texts for the fields, and determining that the specified field is the field of the input speech, wherein step (a) includes the steps of: (a1) with use of the learning texts for the fields, generating, for each field, an appearance frequency list in which the words included in the corresponding learning text are arranged based on appearance frequency, and in which a word other than a noun and a word that appears in a plurality of learning texts for different fields have been removed; (a2) for each field, specifying a word whose appearance frequency satisfies a set condition from the appearance frequency list, and selecting a phrase that includes the specified word from the learning text; and (a3) generating the identification language model using the phrases selected for each field, wherein in step (c), the words included in the text data and the appearance frequency lists for the fields are compared, an appearance frequency list that includes the most words whose confidences are greater than or equal to a set value is specified, and it is determined that the field of the specified appearance frequency list is the field of the input speech, wherein the program further causes the computer to execute the steps of: (d) acquiring the phrases selected in step (a) for each field other than the specified field, adding the acquired phrases as a learning text to the language model in the specified field, and reconstructing the language model in the specified field; and (e) again executing speech recognition on the input speech using the language model reconstructed in step (d).
7. A non-transitory computer-readable recording medium having recorded thereon a program containing instructions for causing a computer to execute the following steps: (a) selecting, from learning texts for a plurality of fields for generating language models for the fields, a phrase that includes a word whose appearance frequency satisfies a set condition on a field-by-field basis, and generating an identification language model for identifying the field of input speech using the selected phrases; (b) executing speech recognition on the input speech using the identification language model, and outputting text data and a confidence for each word included in the text data as a recognition result; and (c) specifying a field that includes the most words whose confidences are greater than or equal to a set value based on the text data, the confidences of the words, and the words included in the learning texts for the fields, and determining that the specified field is the field of the input speech, wherein step (a) includes the steps of: (a1) with use of the learning texts for the fields, generating, for each field, an appearance frequency list in which the words included in the corresponding learning text are arranged based on appearance frequency, and in which a word other than a noun and a word that appears in a plurality of learning texts for different fields have been removed; (a2) for each field, specifying a word whose appearance frequency satisfies a set condition from the appearance frequency list, and selecting a phrase that includes the specified word from the learning text; and (a3) generating the identification language model using the phrases selected for each field, wherein in step (c), the words included in the text data and the appearance frequency lists for the fields are compared, an appearance frequency list that includes the most words whose confidences are greater than or equal to a set value is specified, and it is determined that the field of the specified appearance frequency list is the field of the input speech, wherein the program further causes the computer to execute the steps of: (d) acquiring the phrases selected in step (a) for each field other than the specified field, adding the acquired phrases as a learning text to the language model in the specified field, and reconstructing the language model in the specified field; and (e) again executing speech recognition on the input speech using the language model reconstructed in step (d). 8. The non-transitory computer-readable recording medium according to claim 7 , wherein a language model is prepared in advance for each of the fields, and the computer is caused to further execute the step of: (f) again executing speech recognition on the input speech using the language model in the specified field from among the language models prepared in advanced.