Abstract: The disclosure is for a video caption generation apparatus and method thereof to generate a natural language sentence explaining a video used as input. The disclosure is configured by including an embedding unit to perform a video embedding and a category information embedding, a stack embedding encoder block unit to select a feature by utilizing the embedded video vector and category vector, a video-category attention unit to receive a result of the stack embedding encoder, to generate a similarity matrix and a feature matrix for a video and category information, and to provide a final encoding result, and a decoder module to generate a sentence by utilizing the final encoding result.

Abstract: A device for detecting a morpheme tagging corpus error, of the present invention, includes: an attribute generating unit for generating attributes for word phrases included in an input corpus, by using a kernel to which a rough set theory is applied; and an attribute statistics processing unit for generating part-of-speech tagging corpus error data through the calculation of attributes and frequency count for the same word phrases by counting attributes for the same word phrase among the word phrases, and thus the present invention can detect, quantify, and modify errors included in a corpus (learning data) required in learning for classifier generation and recognition for natural language processing.

Abstract: A device for detecting a morpheme tagging corpus error, of the present invention, includes: an attribute generating unit for generating attributes for word phrases included in an input corpus, by using a kernel to which a rough set theory is applied; and an attribute statistics processing unit for generating part-of-speech tagging corpus error data through the calculation of attributes and frequency count for the same word phrases by counting attributes for the same word phrase among the word phrases, and thus the present invention can detect, quantify, and modify errors included in a corpus (learning data) required in learning for classifier generation and recognition for natural language processing.