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

arXiv:2609.35645 · cs.SD, cs.CL, cs.LG, eess.AS · Submitted 2026-09-28 · Read on arXiv

cs.SD, cs.CL, cs.LG, eess.AS

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/pipecat-ai/stt-benchmark

Terminology

• Benchmark — 27× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Fidelity — 6× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Answer Error Rate — 4× in this paper
• Alternation — 2× in this paper · explained in 1 episode
• Annotator Agreement — 2× in this paper · explained in 1 episode
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Character Error Rate — 1× in this paper
• Commentary — 1× in this paper · explained in 2 episodes
• Cross-lingual Transfer — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review
• EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents
• Voxtral
• Canary-1B-v2 & Parakeet-TDT-0.6B-v3: Efficient and High-Performance Models for Multilingual ASR and AST
• Gemma 4 Technical Report
• Qwen3-Omni Technical Report

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