Abstract: A language processing apparatus includes: a preprocessing unit that splits an input text into a plurality of short texts; a language processing unit that calculates a first feature and a second feature using a trained model for each of the plurality of short texts; and an external storage unit configured to store a third feature for one or more short texts, and the language processing unit uses the trained model to calculate the second feature for a certain short text using the first feature of the short text and the third feature stored in the external storage unit.

Abstract: A dialogue processing apparatus includes one or more computers each including a memory and a processor configured to receive a question Qi as a word string representing a current question in an interactive machine reading comprehension task, a question history {Qi, . . . , Qi?1} as a set of word strings representing previous questions, and an answer history {A1, . . . , Ai?1} as a set of word strings representing previous answers to the previous questions, and use a pre-learned first model parameter, to generate an encoded context vector reflecting an attribute or an importance degree of each of the previous questions and the previous answers; and receive a document P to be used to generate an answer Ai to the question Qi and the encoded context vector, and use a pre-learned second model parameter, to perform matching between the document and the previous questions and previous answers, to generate the answer.

Abstract: A generation unit that takes a question Qi that is a word sequence representing a current question in a dialogue, a document P used to generate an answer Ai to the question Qi, a question history {Qi-1, . . . , Qi-k} that is a set of word sequences representing k past questions, and an answer history {Ai-1, . . . Ai-k} that is a set of word sequences representing answers to the k questions as inputs, and generates the answer Ai by machine reading comprehension in an extractive mode or a generative mode using pre-trained model parameters is provided.