Integrating Speech Technology into the iSTART-Early Intelligent Tutoring System

Renu Balyan, Tracy Arner, Tong Li, Ellen Orcutt, Reese M Butterfuss, Panayiota Kendeou, Danielle McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Speech technology (automated speech recognition – ASR and text-to-speech) offers great promise in the field of automated literacy and reading tutors for children. Students in third and fourth grades struggle with generating longer strings of text on a QWERTY keyboard because they still “hunt and peck” for the letters and symbols rather than typing fluently. Thus, in addition to reading comprehension, students’ performance is limited by their ability to translate their ideas into language and then transcribe those words into written text. Fourth grade students produce fewer words and recall less when typing or writing a response relative to speaking. Hence, speech technology is a crucial component in the development of iSTART-Early, an intelligent tutoring system that aims to provide online, automated reading strategy instruction and practice to improve deep comprehension for third and fourth graders. This paper discusses the key components and features of the speech technology incorporated into iSTART-Early. We also discuss some initial findings from pilot studies conducted with adults and youth for this ASR integrated tutoring system. Finally, we discuss considerations for future development of speech technology and integration with intelligent tutoring systems.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 18th International Conference, ITS 2022, Proceedings
EditorsScott Crossley, Elvira Popescu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages362-370
Number of pages9
ISBN (Print)9783031096792
DOIs
StatePublished - 2022
Event18th International Conference on Intelligent Tutoring Systems, ITS 2022 - Virtual, Online
Duration: Jun 29 2022Jul 1 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13284 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Intelligent Tutoring Systems, ITS 2022
CityVirtual, Online
Period6/29/227/1/22

Bibliographical note

Funding Information:
Acknowledgements. The authors would like to recognize the support of the Institute of Education Sciences (IES), U.S. Department of Education through Grant R305A190050, the National Science Foundation - NSF through Award# 2131052, and the Office of Naval Research - ONR through Grant N000142012623. The opinions expressed are those of the authors and do not represent views of the IES, the NSF, or the ONR.

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Automated speech recognition
  • Intelligent tutoring systems
  • Text-to-speech

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