Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Component-based approach to automatic poetry generation. / Мосолова, Анна Владимировна; Бондаренко, Иван ; Гусев, Петр Андреевич и др.
Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2019). ред. / Владимир Павлович Селегей. Том 18 Москва, 2019.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Component-based approach to automatic poetry generation
AU - Мосолова, Анна Владимировна
AU - Бондаренко, Иван
AU - Гусев, Петр Андреевич
AU - Малышева, Анастасия Дмитриевна
AU - Водолазский, Даниил Иванович
AU - Боровикова, Мария Николаевна
PY - 2019
Y1 - 2019
N2 - This paper describes two approaches to generating poetic texts on a given topic, one of which we used while participating in ClassicAI, a contest in developing poetry generators in a specific style held by Sberbank. In the first one, we used topic modeling for extracting keywords that a certain topic is characteristic of, applied a text data augmenter to replace parts of the source of the poetry style with thematic words, and then applied a poetic consistency checker to maintain rhyme and rhythm in the output text. In the second one, we used semantic search for obtaining odd lines for the output texts and then phonetic search that selected lines similar in rhyme and rhythm to the given lines and used them as even ones. In this paper, we describe both of our approaches, analyze their benefits and weak spots, provide information on the results of the competition and suggest possible improvements
AB - This paper describes two approaches to generating poetic texts on a given topic, one of which we used while participating in ClassicAI, a contest in developing poetry generators in a specific style held by Sberbank. In the first one, we used topic modeling for extracting keywords that a certain topic is characteristic of, applied a text data augmenter to replace parts of the source of the poetry style with thematic words, and then applied a poetic consistency checker to maintain rhyme and rhythm in the output text. In the second one, we used semantic search for obtaining odd lines for the output texts and then phonetic search that selected lines similar in rhyme and rhythm to the given lines and used them as even ones. In this paper, we describe both of our approaches, analyze their benefits and weak spots, provide information on the results of the competition and suggest possible improvements
M3 - Conference contribution
VL - 18
BT - Computational Linguistics and Intellectual Technologies
A2 - Селегей, Владимир Павлович
CY - Москва
ER -
ID: 23057322