Does language matter for spoken word classification? A multilingual generative meta-learning approach
Meta-learning has been shown to have better performance than supervised learning for few-shot monolingual spoken word classification. However, the meta-learning approach remains under-explored in multilingual spoken word classification. In this paper, we apply the Generative Meta-Continual Learning algorithm to spoken word classification. The generative nature of this algorithm makes it viable for use in application, and the meta-learning aspect promotes generalisation, which is crucial in a multilingual setting. We train monolingual models on English, German, French, and Catalan, a bilingual model on English and German, and a multilingual model on all four languages. We find that althoug...
| Authors | Batsirayi Mupamhi Ziki, Louise Beyers, Ruan van der Merwe |
|---|---|
| Primary category | cs.CL |
| Published | 13 May 2026 |
| Last updated at source | 14 May 2026 |
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