hussxamg04/apptek_callcenter_dialogues
AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents across multiple service-oriented domains and designed to evaluate models on realistic call-center interactions. 128.6 hours of speech 14 English accent groups 16 service domains 5–15 minute conversations (long-form) Split-channel audio (one… See the full description on the dataset page: https://huggingface.co/datasets/hussxamg04/apptek_callcenter_dialogues.
| Author / organization | hussxamg04 |
|---|---|
| License (as declared) | cc-by-sa-4.0 |
| Downloads | 139 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 9 May 2026 |
| Last updated at source | 9 May 2026 |
Popularity, last 3 days
139 now (-1 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
Recent changes
- 16 Oct 2026 Description: AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents across mult → AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents across mult
Changes detected by Silytics between refreshes of the source.
Related papers
More from hussxamg04
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.