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Sequential Adapter Stacking for Cross-Lingual Low-Resource ASR

Paper recorded by Signals 4 on 2026-09-14 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.CL · 自然语言处理 · first seen 2026-09-15

Abstract

Extending large-scale multilingual automatic speech recognition (ASR) models to low-resource languages remains challenging. Model performance is skewed toward high-resource languages and degrades sharply for languages with limited labeled data and pre-training exposure. To address this, we investigate parameter-efficient approaches for transferring knowledge from resource-rich source languages to

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#45 most recent of 186 cs.CL papers we have recorded · ↑ newer: Enabling Streaming User Transcription in Full-Duplex Speech-to-Speech · ↓ older: Look Before You Leap: Factual Decoding with Internal Attribution Signa
Cite this page: Sequential Adapter Stacking for Cross-Lingual Low-Resource ASR: the #45 most recent of 186 cs.CL papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sequential-adapter-stacking-for-cross-lingual-low-resource-asr.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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