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arXiv · 2012.00876

Automatically Identifying Language Family from Acoustic Examples in Low Resource Scenarios

Peter Wu·Yifan Zhong·Alan W Black
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Abstract

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

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Peter Wu, Yifan Zhong, Alan W Black. 2020-12-01. Automatically Identifying Language Family from Acoustic Examples in Low Resource Scenarios. https://arxiv.org/abs/2012.00876

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