# ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers

arXiv: https://arxiv.org/abs/2004.09367 · HTML: https://mlsanity.com/paper/2004.09367/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Apr 2020.

## Built on by (most cited first, 13 of 13)

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- [KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark](https://mlsanity.com/paper/2402.17377/) (2024)
- [Inclusivity of AI Speech in Healthcare: A Decade Look Back](https://mlsanity.com/paper/2505.10596/) (2025)
- [Korean Tokenization for Beam Search Rescoring in Speech Recognition](https://mlsanity.com/paper/2203.03583/) (2022)
- [Evaluating Automatic Speech Recognition Systems for Korean Meteorological Experts](https://mlsanity.com/paper/2410.18444/) (2024)
- [KoALa-Bench: Evaluating Large Audio Language Models on Korean Speech Understanding and Faithfulness](https://mlsanity.com/paper/2604.19782/) (2026)
- [Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services](https://mlsanity.com/paper/2609.09889/) (2026)

## Abstract (arXiv)

Automatic speech recognition (ASR) via call is essential for various applications, including AI for contact center (AICC) services. Despite the advancement of ASR, however, most publicly available call-based speech corpora such as Switchboard are old-fashioned. Also, most existing call corpora are in English and mainly focus on open domain dialog or general scenarios such as audiobooks. Here we introduce a new large-scale Korean call-based speech corpus under a goal-oriented dialog scenario from more than 11,000 people, i.e., ClovaCall corpus. ClovaCall includes approximately 60,000 pairs of a short sentence and its corresponding spoken utterance in a restaurant reservation domain. We validate the effectiveness of our dataset with intensive experiments using two standard ASR models. Furthermore, we release our ClovaCall dataset and baseline source codes to be available via https://github.com/ClovaAI/ClovaCall.