Error Rate is Not Enough: Costs of Augmentation in Low-Resource ASR

Paper recorded by Signals 4 on 2026-10-09 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.CL · 自然语言处理 · first seen 2026-10-12

Abstract

Data augmentation is standard practice for low-resource automatic speech recognition (ASR), but its benefits are almost always reported as aggregate error rates, leaving open why and when a method helps. On four low-resource languages and English at five data sizes, we cross two augmentations that modify existing audio (speed perturbation and SpecAugment) with two that modify text transcriptions a

Read on arXiv →