Automatic Speaking Assessment of Spontaneous L2 Finnish and Swedish

Ragheb Al-Ghezi, Katja Vosboinik, Yaroslav Getman, Anna von Zansen, Heini Kallio, Mikko Kurimo, Ari Huhta, Raili Hilden

Forskningsoutput: TidskriftsbidragArtikelVetenskapligPeer review

Sammanfattning

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.
Originalspråkengelska
TidskriftLanguage Assessment Quarterly
Volym20
Nummer4-5
Sidor (från-till)421-444
Antal sidor24
ISSN1543-4303
DOI
StatusPublicerad - 26 dec. 2023
MoE-publikationstypA1 Tidskriftsartikel-refererad

Vetenskapsgrenar

  • 516 Pedagogik
  • 213 El-, automations- och telekommunikationsteknik, elektronik

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