AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR
Evaluating English ASR systems for conversational AI applications remains difficult, as many publicly available corpora are either pre-segmented into short segments, consist of read or prepared speech, or lack explicit dialect annotations to evaluate robustness for a diverse user base. This work presents the AppTek Call-Center Dialogues corpus, a collection of spontaneous, role-played agent-customer conversations spanning fourteen English accents covering sixteen service-oriented scenarios. The dataset was commissioned specifically for evaluation and none of the audio or text was publicly available prior to release, reducing the risk of overlap with existing large-scale pretraining corpor...
| Authors | Eugen Beck, Sarah Beranek, Uma Moothiringote et al. |
|---|---|
| Primary category | cs.CL |
| Published | 30 April 2026 |
| Last updated at source | 30 April 2026 |
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