论文标题
Clovacall：韩国目标对话框语音语料库，用于自动语音识别联络中心
ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers
论文作者
论文摘要
通过呼叫的自动语音识别（ASR）对于各种应用程序，包括联络中心（AICC）服务在内的各种应用程序至关重要。但是，尽管ASR的发展进步，但大多数公开可用的基于呼叫的语音语料库（例如总成）是老式的。此外，大多数现有的呼叫语料库都是英语，主要关注开放型域对话框或一般场景，例如有声读物。在这里，我们在11,000多人（即Clovacall Corpus）的一个面向目标的对话方案下介绍了一个新的大型韩国呼叫的演讲语料库。克洛瓦卡尔（Clovacall）包括大约60,000对简短的句子及其在餐厅预订域中的相应口语。我们使用两个标准ASR模型通过密集实验来验证数据集的有效性。此外，我们发布了Clovacall数据集和基线源代码，可通过https://github.com/clovaai/clovacall提供。
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.
