DOI

Coherence and cohesion are crucial for organizing text semantics and syntax. They both may be described in terms of topic-focus structure, but the surface syntactic topic-focus structure does not coincide with that of deep semantics, and the automatic analysis of coherence which refers to the meaning of the whole text is complicated. The paper presents a Topic-Focus Annotating Parser (TFAP) that was trained on the corpus of Russian unprepared child oral narratives (213 narratives elicited by native Russian children aged from two years seven months to seven years six months). According to the results, children develop their narrative skills both in coherence and cohesion, but at the earlier stages of language acquisition, parsing errors reflect the speaker’s low level of narrative skills, while at the later stages (from five years seven months to seven years six months), when the basic rules of narrative organization are already acquired, parsing errors may be caused by the deficiencies of the parser. The topic-focus schemes we obtained support Leonid Sakharny’s theoretical approach to cognitive representation of coherence.

Язык оригиналаанглийский
Название основной публикацииSpeech and Computer
Подзаголовок основной публикации20th International Conference, SPECOM 2018, Leipzig, Germany, September 18–22, 2018, Proceedings
Место публикацииCham
ИздательSpringer Nature
Страницы145-154
ISBN (электронное издание)978-3-319-99579-3
ISBN (печатное издание)978-3-319-99578-6
DOI
СостояниеОпубликовано - 1 янв 2018
Событие20th International Conference on Speech and Computer - Leipzig, Германия
Продолжительность: 18 сен 201822 сен 2018

Серия публикаций

НазваниеLecture Notes in Computer Science
ИздательSpringer Nature
Том11096
ISSN (печатное издание)0302-9743

конференция

конференция20th International Conference on Speech and Computer
Сокращенное названиеSPECOM 2018
Страна/TерриторияГермания
ГородLeipzig
Период18/09/1822/09/18

    Предметные области Scopus

  • Теоретические компьютерные науки
  • Компьютерные науки (все)

ID: 71303139