Nec Corporation

Yousuke Sakao

Takahiro Ikeda

Kenji Satoh

Satoshi Nakazawa

Susumu Akamine

Kenjo Satoh

Yoshihiro Ikeda, Legal Representative

In a voice recognizing apparatus, a voice recognizing method, and a program for recognizing voice are provided to carry out voice recognition with high precision. When a call receiving unit in which a plurality of telephone numbers for receiving are assigned to respective contents of calls receives a call from a caller, a calling voice signal input device inputs a calling voice signal of the call, and a receiving telephone number input device inputs the receiving telephone number of the call. A voice correction device then carries out voice correction processing for the calling voice signal in accordance with the receiving telephone number and a voice recognizing device executes voice recognition processing for the calling voice signal in accordance with the receiving telephone number.

Voice recognizing apparatus, voice recognizing method, and program for recognizing voice

[PROBLEMS] To provide a data processing device such as a text mining device capable of extracting characteristic structures properly even in case a plurality of words indicating identical contents or a plurality of words semantically associated are contained in input data. [MEANS FOR SOLVING PROBLEMS] Association node extraction unit () of a text mining device () extracts association nodes containing semantically associated words from a graph obtained as a result of syntax analysis. Association node joint unit () transforms the graph by joint of a part of or a whole of the association nodes. Characteristic structure extraction unit () extracts a characteristic structure from the graph transformed by the association node joint unit.

Data processing device, data processing method, and data processing program

Language analysis meansanalyzes texts read from a text DB, and generates a sentence structure as the analysis result. Similar-structure generation adjustment meansgenerates, from an input of an input device, a determination item for determining whether or not the structures are identical every type of differences between the sentence structures. Similar-structure determination adjustment meansgenerates, from an input of the input device, a determination item for determining whether or not the difference between attribute values is ignored every type of attribute values. Similar-structure generating meansgenerates a similar structure of a partial structure forming the sentence structure obtained by language analysis meansin accordance with the determination item from the similar-structure generation adjustment means, and sets the generated similar structure as an equivalent class of the partial structure on the generation source. Frequent-similar-pattern detection meansignores the attribute value in accordance with the determination item given from the similar-structure determination adjustment means, detects the frequent pattern on the basis of a set of equivalent classes from the similar-structure generating means, and outputs the frequent pattern to an output device

Text mining device, method thereof, and program

Provided is a text mining device capable of showing a user whether the characteristics extracted by a text mining are either common to all texts independently of the citations, in case the text to be mined is configured with texts of a plurality of kinds of different citations, or deviated toward a text of a predetermined citation. The text mining device includes a citation information creating device for creating the citation information of texts containing characteristics extracted from a text set collected from a plurality of citations, and a mining result output device for outputting the characteristics and the citation information in a corresponding manner.

Text mining device, text mining method, and text mining program

With respect to each part at which a word included in a characteristic condition defining a characteristic text set designated by a user through the input device appears in text, the characteristic condition assurance degree calculating unit of the text mining device obtains a reliability of the word from the word reliability storage unit to operate a value of a characteristic condition assurance degree for each text by predetermined operation based on all the obtained reliabilities. The characteristic condition assurance degree calculating unit executes operation such that when a value of each reliability is large, a value of a degree of assurance becomes large. The representative text output unit outputs text whose characteristic condition assurance degree is the highest among texts whose characteristic condition assurance degrees are calculated together with its characteristic condition assurance degree.

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Tokyo, Japan

Yousuke Sakao