We have constructed the Corpus of Everyday Japanese Conversation (CEJC) and published it in March 2022. The CEJC is designed to contain various kinds of everyday conversations in a balanced manner to capture their diversity. The CEJC features not only audio but also video data to facilitate precise understanding of the mechanism of real-life social behavior. The publication of a large-scale corpus of everyday conversations that includes video data is a new approach. The CEJC contains 200 hours of speech, 577 conversations, about 2.4 million words, and a total of 1675 conversants. In this paper, we present an overview of the corpus, including the recording method and devices, structure of the corpus, formats of video and audio files, transcription, and annotations. We then report some results of the evaluation of the CEJC in terms of conversant and conversation attributes. We show that the CEJC includes a good balance of adult conversants in terms of gender and age, as well as a variety of conversations in terms of conversation forms, places, activities, and numbers of conversants.

In this paper, we describe the design and development of a new version of the Corpus of Spontaneous Japanese (CSJ), which is a large-scale spoken corpus released in 2004. CSJ contains various annotations that are represented in XML format (CSJ-XML). CSJ-XML, however, is very complicated and suffers from some problems. To overcome this problem, we have developed and released, in 2013, a relational database version of CSJ (CSJ-RDB). CSJ-RDB is based on an extension of the segment and link-based annotation scheme, which we adapted to handle multi-channel and multi-modal streams. Because this scheme adopts a stand-off framework, CSJ-RDB can represent three hierarchical structures at the same time: inter-pausal-unit-top, clause-top, and intonational-phrase-top. CSJ-RDB consists of five different types of tables: segment, unaligned-segment, link, relation, and meta-information tables. The database was automatically constructed from annotation files extracted from CSJ-XML by using general-purpose corpus construction tools. CSJ-RDB enables us to easily and efficiently conduct complex searches required for corpus-based studies of spoken language.