# Rediscovering the Slavic Continuum in Representations Emerging from Neural Models of Spoken Language Identification

arXiv: https://arxiv.org/abs/2010.11973 · HTML: https://mlsanity.com/paper/2010.11973/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Oct 2020.

## Built on by (most cited first, 14 of 14)

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## Abstract (arXiv)

Deep neural networks have been employed for various spoken language recognition tasks, including tasks that are multilingual by definition such as spoken language identification. In this paper, we present a neural model for Slavic language identification in speech signals and analyze its emergent representations to investigate whether they reflect objective measures of language relatedness and/or non-linguists' perception of language similarity. While our analysis shows that the language representation space indeed captures language relatedness to a great extent, we find perceptual confusability between languages in our study to be the best predictor of the language representation similarity.