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  • Assessment of Speech Development of Russian-speaking Children Under Three Years of Age Using MLU and IPSyn Methods Based on Longitudinal Data

Assessment of Speech Development of Russian-speaking Children Under Three Years of Age Using MLU and IPSyn Methods Based on Longitudinal Data

Student: Mariia Diachkova

Supervisor: Svetlana Dorofeeva

Faculty: Faculty of Humanities

Educational Programme: Fundamental and Computational Linguistics (Bachelor)

Year of Graduation: 2024

MLU and IPSyn are methods for assessing children's speech development. They were originally offered for English, but are now actively adapting to Russian. In this paper, we answered several questions. Can these methods significantly predict age based on longitudinal data? What is the appropriate sample size for the application of these methods? How do MLU and Ipsum relate to each other in assessing children's speech? The study was implemented based on longitudinal data from seven Russian-speaking children aged 20 to 32 months. The recordings were collected as part of the CHILDES project. The construction of linear models with mixed effects showed that both tools significantly predict age based on longitudinal data. In addition, it was found that the corpus sizes of 50, 75 and 100 statements provide informative results for the evaluation of children's speech using MLU and IPSyn methods. Also, both tools are highly consistent with each other in assessing children's speech.

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