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Existing multilingual speech NLP works focus on a relatively small subset oflanguages, and thus current linguistic understanding of languages predominantlystems from classical approaches. In this work, we propose a method to analyzelanguage similarity using deep learning. Namely, we train a model on theWilderness dataset and investigate how its latent space compares with classicallanguage family findings. Our approach provides a new direction forcross-lingual data augmentation in any speech-based NLP task.

Automatically Identifying Language Family from Acoustic Examples in Low Resource Scenarios