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

• Main Authors: Ha, Jung-Woo, Nam, Kihyun, Kang, Jingu, Lee, Sang-Woo, Yang, Sohee, Jung, Hyunhoon, Kim, Eunmi, Kim, Hyeji, Kim, Soojin, Kim, Hyun Ah, Doh, Kyoungtae, Lee, Chan Kyu, Sung, Nako, Kim, Sunghun
• Format: Journal Article
• Language: English
• Published: 20.04.2020
• Subjects: Computer Science - Computation and Language; Computer Science - Learning; Computer Science - Sound; Statistics - Machine Learning
• DOI: 10.48550/arxiv.2004.09367

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.