Program
Speech, Language, and Multimodal Resources
Mon-1-10-3 ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers
Jung-Woo Ha(Clova AI Research, NAVER Corp.), Kihyun Nam(Hankuk University of Foreign Stuides), Jin Gu Kang(Clova AI, NAVER Corp.), Sang-Woo Lee(Clova AI Research, NAVER Corp.), Sohee Yang(Clova AI, NAVER Corp.), Hyunhoon Jung(Clova AI, NAVER Corp.), Hyeji Kim(Clova AI, NAVER Corp.), Eunmi Kim(Clova AI, NAVER Corp.), Soojin Kim(Clova AI, NAVER Corp.), Hyun Ah Kim(Clova AI, NAVER Corp.), Kyoungtae Doh(Clova AI, NAVER Corp.), Chan Kyu Lee(Clova AI, NAVER Corp.), Nako Sung(Clova AI, NAVER Corp.) and Sunghun Kim(Clova AI, NAVER Corp.;The Hong Kong University of Science and Technology)
Abstract:
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.
Calls
Program