ASR in classroom today: Automatic visualization of conceptual network in science classrooms

Daniela Caballero*, Roberto Araya, Hanna Kronholm, Jouni Viiri, André Mansikkaniemi, Sami Lehesvuori, Tuomas Virtanen, Mikko Kurimo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

7 Citations (Scopus)


Automatic Speech Recognition (ASR) field has improved substantially in the last years. We are in a point never saw before, where we can apply such algorithms in non-ideal conditions such as real classrooms. In these scenarios it is still not possible to reach perfect recognition rates, however we can already take advantage of these improvements. This paper shows preliminary results using ASR in Chilean and Finnish middle and high school to automatically provide teachers a visualization of the structure of concepts present in their discourse in science classrooms. These visualizations are conceptual networks that relate key concepts used by the teacher. This is an interesting tool that gives feedback to the teacher about his/her pedagogical practice in classes. The result of initial comparisons shows great similarity between conceptual networks generated in a manual way with those generated automatically.

Original languageEnglish
Title of host publicationData Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings
Number of pages4
Volume10474 LNCS
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventEuropean Conference on Technology Enhanced Learning - Tallinn, Estonia
Duration: 12 Sep 201715 Sep 2017
Conference number: 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10474 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceEuropean Conference on Technology Enhanced Learning
Abbreviated titleEC-TEL


  • Automatic speech recognition
  • Classroom dialogue
  • Conceptual network
  • Teacher discourse

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