# Real-World En Call Center Transcripts Dataset with PII Redaction

arXiv: https://arxiv.org/abs/2507.02958 · HTML: https://mlsanity.com/paper/2507.02958/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jun 2025.

## Built on by (most cited first, 3 of 3)

- [Why Synthetic Isn't Real Yet: A Diagnostic Framework for Contact Center Dialogue Generation](https://mlsanity.com/paper/2508.18210/) (2025)
- [INSURE-Dial: A Phase-Aware Conversational Dataset & Benchmark for Compliance Verification and Phase Detection](https://mlsanity.com/paper/2602.18448/) (2026)
- [DG^VoiC: Speaker Clustering for Fraud Investigation under Real Call-Centre Conditions](https://mlsanity.com/paper/2606.28048/) (2026)

## Abstract (arXiv)

We introduce CallCenterEN, a large-scale (91,706 conversations, corresponding to 10448 audio hours), real-world English call center transcript dataset designed to support research and development in customer support and sales AI systems. This is the largest release to-date of open source call center transcript data of this kind. The dataset includes inbound and outbound calls between agents and customers, with accents from India, the Philippines and the United States. The dataset includes high-quality, PII-redacted human-readable transcriptions. All personally identifiable information (PII) has been rigorously removed to ensure compliance with global data protection laws. The audio is not included in the public release due to biometric privacy concerns. Given the scarcity of publicly available real-world call center datasets, CallCenterEN fills a critical gap in the landscape of available ASR corpora, and is released under a CC BY-NC 4.0 license for non-commercial research use.