ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers
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 i...
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Zusammenfassung: | 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. |
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DOI: | 10.48550/arxiv.2004.09367 |