Nippon Telegraph and Telephone Corporation

Tohoku University

Ntt Corporation

Sho Takase

Jun Suzuki

Masaaki Nagata

Shun Kiyono

Kentaro Inui

Naoaki Okazaki

Makoto Morishita

Hidetaka Kamigaito

An information learning apparatus includes a memory and a processor configured to perform generating, for each of processing units constituting an input sequence included in training data, a third embedded vector based on a first embedded vector for the processing unit and a second embedded vector corresponding to an unknown word; executing a process based on a learning target parameter, with the third embedded vector generated for each of the processing units as an input; and learning, for a processing result by the executing, the parameter based on an error of an output corresponding to the input sequence in the training data.

Embedding an unknown word in an input sequence

Disclosed is a natural language processing technique according to a neural network of high interpretive ability. One embodiment of the present disclosure relates to an apparatus including a trained neural network into which first natural language text is input and that is trained to output second natural language text and alignment information, the second natural language text being in accordance with a predetermined purpose corresponding to the first natural language text, and the alignment information indicating, for each part of the second natural language text, which part of the first natural language text is a basis of information for generation; and an analyzing unit configured to output, upon input text being input into the trained neural network, a predicted result of output text in accordance with a predetermined purpose, and alignment information indicating, for each part of the predicted result of the output text, which part of the input text is a basis of information for generation.

Device, method and program for natural language processing

To generate a vector representing a word in consideration of the importance of the character string of the word. A character N-gram vector acquisition unit acquires a vector representing each of character N-grams included in a word. A weight calculation unitcalculates a weight for a vector representing each of the character N-grams on the basis of the vector representing each of the character N-grams included in the word, and a character N-gram vector combining unitgenerates a composite vector obtained by combining the vector representing each of the character N-grams on the basis of the vector representing each of the character N-grams included in the word and the weight for the vector representing each of the character N-grams.

Word coding device, analysis device, language model learning device, method, and program

Growing community of inventors

Musashino, Japan

Sho Takase