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CoSE-E: A Benchmark for Code-switched Speech Evaluation in Enterprise Settings

Paper recorded by Signals 4 on 2026-09-28 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-28 on arXiv · recorded by Signals 4 on 2026-09-29

Category: cs.CL · 自然语言处理 · first seen 2026-09-29

Abstract

Code-switching (CS), a seamless alternation between languages within a single utterance, remains a critical challenge in automatic speech recognition (ASR). While prior works focus on conversational CS-ASR, enterprise settings demand evaluation of operational impact beyond edit-distance errors: how code-switching transcription errors propagate to downstream voice agent task failures. In this work,

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#8 most recent of 279 cs.CL papers we have recorded · ↑ newer: Rubric Rewards from Item Response Theory · ↓ older: Which the Eye Fears: Writing with Read-Blindness Explains Massive Acti
Cite this page: CoSE-E: A Benchmark for Code-switched Speech Evaluation in Enterprise Settings: the #8 most recent of 279 cs.CL papers we have recorded (as of 2026-09-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/cose-e-a-benchmark-for-code-switched-speech-evaluation-in-enterprise-settings.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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