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Scientific article
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English

CALL-SLT: A Spoken CALL System Based on Grammar and Speech Recognition

Contributors

Rayner, Emmanuel; Tsourakis, Nikolaos; Baur, Claudia; Bouillon, Pierrette; Gerlach, Johanna

Published in

Linguistic Issues in Language Technology, vol. 10, no. 2

Publication date

2014

Abstract

We describe CALL-SLT, a speech-enabled Computer-Assisted Language Learning application where the central idea is to prompt the student with an abstract representation of what they are supposed to say, and then use a combination of grammar-based speech recognition and rule-based translation to rate their response. The system has been developed to the level of a mature prototype, freely deployed on the web, with versions for several languages. We present an overview of the core system architecture and the various types of content we have developed. Finally, we describe several evaluations, the last of which is a study carried out over about a week using 130 subjects recruited through the Amazon Mechanical Turk, in which CALL-SLT was contrasted against a control version where the speech recognition component was disabled. The improvement in student learning performance between the two groups was significant at p < 0.02.

Keywords

  • CALL
  • Speech
  • Grammar
  • Evaluation

UNIGE affiliation entities

Citation (ISO format)

RAYNER, Emmanuel et al. CALL-SLT: A Spoken CALL System Based on Grammar and Speech Recognition. In: Linguistic Issues in Language Technology, 2014, vol. 10, n° 2. doi: 10.33011/lilt.v10i.1353

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Article (Published version)

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Technical informations

Creation

08/11/2014 10:17:00

First validation

08/11/2014 10:17:00

Update

27/01/2026 16:00:16

Status update

27/01/2026 16:00:16

Last indexation

27/01/2026 16:04:13
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