Classification of Autistic and Non-Autistic Children's Speech: A Cross-Linguistic Study in Finnish, French, and Slovak
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866912948482473984 |
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| author | Kakouros, Sofoklis Myllylä, Ida-Lotta |
| author_facet | Kakouros, Sofoklis Myllylä, Ida-Lotta |
| contents | We present a cross-linguistic study of speech in autistic and non-autistic children speaking Finnish, French, and Slovak. We combine supervised classification with within-language and cross-corpus transfer experiments to evaluate classification performance within and across languages and to probe which acoustic cues are language-specific versus language-general. Using a large set of acoustic-prosodic features, we implement speaker-level classification benchmarks as an analytical tool rather than to seek state-of-the-art performance.
Within-language models, evaluated with speaker-level cross-validation, yielded heterogeneous results. The Finnish model performed best (Accuracy 0.84, F1 0.88), followed by Slovak (Accuracy 0.63, F1 0.68) and French (Accuracy 0.68, F1 0.56). We then tested cross-language generalization. A model trained on all pooled corpora reached an overall Accuracy of 0.61 and F1 0.68. Leave-one-corpus-out experiments, which test transfer to an unseen language, showed moderate success when testing on Slovak (F1 0.70) and Finnish (F1 0.78), but poor transfer to French (F1 0.42). Feature-importance analyses across languages highlighted partially shared, but not fully language-invariant, acoustic markers of autism.
These findings suggest that some autism-related speech cues generalize across typologically distinct languages, but robust cross-linguistic classifiers will likely require language-aware modeling and more homogeneous recording conditions. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_06327 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Classification of Autistic and Non-Autistic Children's Speech: A Cross-Linguistic Study in Finnish, French, and Slovak Kakouros, Sofoklis Myllylä, Ida-Lotta Audio and Speech Processing We present a cross-linguistic study of speech in autistic and non-autistic children speaking Finnish, French, and Slovak. We combine supervised classification with within-language and cross-corpus transfer experiments to evaluate classification performance within and across languages and to probe which acoustic cues are language-specific versus language-general. Using a large set of acoustic-prosodic features, we implement speaker-level classification benchmarks as an analytical tool rather than to seek state-of-the-art performance. Within-language models, evaluated with speaker-level cross-validation, yielded heterogeneous results. The Finnish model performed best (Accuracy 0.84, F1 0.88), followed by Slovak (Accuracy 0.63, F1 0.68) and French (Accuracy 0.68, F1 0.56). We then tested cross-language generalization. A model trained on all pooled corpora reached an overall Accuracy of 0.61 and F1 0.68. Leave-one-corpus-out experiments, which test transfer to an unseen language, showed moderate success when testing on Slovak (F1 0.70) and Finnish (F1 0.78), but poor transfer to French (F1 0.42). Feature-importance analyses across languages highlighted partially shared, but not fully language-invariant, acoustic markers of autism. These findings suggest that some autism-related speech cues generalize across typologically distinct languages, but robust cross-linguistic classifiers will likely require language-aware modeling and more homogeneous recording conditions. |
| title | Classification of Autistic and Non-Autistic Children's Speech: A Cross-Linguistic Study in Finnish, French, and Slovak |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2603.06327 |