Feature-based analysis of oral narratives from Afrikaans and isiXhosa children
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915397560696832 |
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| author | Sharratt, Emma Smith, Annelien Louw, Retief Klop, Daleen de Wet, Febe Kamper, Herman |
| author_facet | Sharratt, Emma Smith, Annelien Louw, Retief Klop, Daleen de Wet, Febe Kamper, Herman |
| contents | Oral narrative skills are strong predictors of later literacy development. This study examines the features of oral narratives from children who were identified by experts as requiring intervention. Using simple machine learning methods, we analyse recorded stories from four- and five-year-old Afrikaans- and isiXhosa-speaking children. Consistent with prior research, we identify lexical diversity (unique words) and length-based features (mean utterance length) as indicators of typical development, but features like articulation rate prove less informative. Despite cross-linguistic variation in part-of-speech patterns, the use of specific verbs and auxiliaries associated with goal-directed storytelling is correlated with a reduced likelihood of requiring intervention. Our analysis of two linguistically distinct languages reveals both language-specific and shared predictors of narrative proficiency, with implications for early assessment in multilingual contexts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_13164 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Feature-based analysis of oral narratives from Afrikaans and isiXhosa children Sharratt, Emma Smith, Annelien Louw, Retief Klop, Daleen de Wet, Febe Kamper, Herman Computation and Language Audio and Speech Processing Oral narrative skills are strong predictors of later literacy development. This study examines the features of oral narratives from children who were identified by experts as requiring intervention. Using simple machine learning methods, we analyse recorded stories from four- and five-year-old Afrikaans- and isiXhosa-speaking children. Consistent with prior research, we identify lexical diversity (unique words) and length-based features (mean utterance length) as indicators of typical development, but features like articulation rate prove less informative. Despite cross-linguistic variation in part-of-speech patterns, the use of specific verbs and auxiliaries associated with goal-directed storytelling is correlated with a reduced likelihood of requiring intervention. Our analysis of two linguistically distinct languages reveals both language-specific and shared predictors of narrative proficiency, with implications for early assessment in multilingual contexts. |
| title | Feature-based analysis of oral narratives from Afrikaans and isiXhosa children |
| topic | Computation and Language Audio and Speech Processing |
| url | https://arxiv.org/abs/2507.13164 |