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

• URL: http://arxiv.org/abs/2010.11973v1
• Date: Thu, 22 Oct 2020 18:18:19 GMT
• Title: Rediscovering the Slavic Continuum in Representations Emerging from Neural Models of Spoken Language Identification
• Authors: Badr M. Abdullah, Jacek Kudera, Tania Avgustinova, Bernd M\"obius, Dietrich Klakow
• Abstract summary: We present a neural model for Slavic language identification in speech signals. We analyze its emergent representations to investigate whether they reflect objective measures of language relatedness.
• Score: 16.369477141866405
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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