Automatic Speaking Assessment of Spontaneous L2 Finnish and Swedish

Ragheb Al-Ghezi*, Ekaterina Voskoboinik, Yaroslav Getman, Anna Von Zansen, Heini Kallio, Mikko Kurimo, Ari Huhta, Raili Hildén

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
42 Downloads (Pure)

Abstract

The development of automated systems for evaluating spontaneous speech is desirable for L2 learning, as it can be used as a facilitating tool for self-regulated learning, language proficiency assessment, and teacher training programs. However, languages with fewer learners face challenges due to the scarcity of training data. Recent advancements in machine learning have made it possible to develop systems with a limited amount of target domain data. To this end, we propose automatic speaking assessment systems for spontaneous L2 speech in Finnish and Finland Swedish, comprising six machine learning models each, and report their performance in terms of statistical evaluation criteria.

Original languageEnglish
Pages (from-to)421-444
Number of pages24
JournalLanguage Assessment Quarterly
Volume20
Issue number4-5
DOIs
Publication statusPublished - 2023
MoE publication typeA1 Journal article-refereed

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  • DigiTala: Aka-Digi Tala

    Kurimo, M., Al-Ghezi, R., Getman, Y. & Voskoboinik, E.

    01/09/201931/08/2023

    Project: Academy of Finland: Other research funding

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