A study on natural expressive speech: Automatic memorable spoken quote detection

Fajri Koto, Sakriani Sakti, Graham Neubig, Tomoki Toda, Mirna Adriani, Satoshi Nakamura

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This paper presents a study on natural expressive speech during public talks. Specifically, we focus on how people convey important messages that may be retained in the audience's consciousness. Our study aims to answer several questions. Why are some public speeches memorable and inspirational for the audience, while others are not? Why are some memorable/inspirational spoken quotes more popular than others? Being able to evaluate why certain spoken words are memorable/inspirational is not a trivial matter, and most studies on memorable quote detection are only limited to textual data. In this study, we use both linguistic and acoustic features of public speeches in TED talks. The results reveal that based on those linguistic and acoustic features, we are able to distinguish memorable spoken quotes and non-memorable spoken quotes with 70.4% accuracy. Furthermore, we also analyze the important factors that affect the memorableness and popularity of spoken quotes.

Original languageEnglish
Title of host publicationNatural Language Dialog Systems and Intelligent Assistants
PublisherSpringer International Publishing
Pages145-152
Number of pages8
ISBN (Electronic)9783319192918
ISBN (Print)9783319192901
DOIs
Publication statusPublished - 29 Oct 2015

Keywords

  • Automatic quote detection
  • Memorable spoken quote
  • Popularity analysis

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