Review of speech-to-text recognition technology for enhancing learning

Rustam Shadiev, Wu Yuin Hwang, Nian Shing Chen, Yueh-Min Huang

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

This paper reviewed literature from 1999 to 2014 inclusively on how Speech-to-Text Recognition (STR) technology has been applied to enhance learning. The first aim of this review is to understand how STR technology has been used to support learning over the past fifteen years, and the second is to analyze all research evidence to understand how Speech-to-Text Recognition technology can enhance learning. The findings are discussed from different perspectives as follows: (a) potentials of STR technology, (b) its use by specific groups of users in different domains, (c) quantitative and/or qualitative research methodology used, and (d) STR technology implications. Some STR literature review showed that in earlier stage of development, the STR technology was applied to assist learning only for specific users, i.e., students with cognitive and physical disabilities, or foreign students. Educators and researchers started to apply STR technology in a traditional learning environment to assist broader group of users, while STR technology has been rapidly advancing over the years. The review revealed a number of distinct advantages of using STR for learning. That is, STR-generated texts enable students to understand learning content of a lecture better, to confirm missed or misheard parts of a speech, to take notes or complete homework, and to prepare for exams. Furthermore, some implications over the STR technology in pedagogical and technological aspects were discussed in the review, such as the design of technology-based learning activities, accuracy rate of the STR process and learning behaviors to use STR-texts that may limit the STR educational value. Thus, the review furthermore discussed some potential solutions for the future research.

Original languageEnglish
Pages (from-to)65-84
Number of pages20
JournalEducational Technology and Society
Volume17
Issue number4
Publication statusPublished - 2014 Jan 1

All Science Journal Classification (ASJC) codes

  • Education
  • Sociology and Political Science
  • Engineering(all)

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