UD _ J apanese- CEJC : Dependency Relation Annotation on Corpus of Everyday J apanese Conversation (2023)

Abstract: In this study, we have developed Universal Dependencies (UD) resources for spoken Japanese in the Corpus of Everyday Japanese Conversation (CEJC). The CEJC is a large corpus of spoken language that encompasses various everyday conversations in Japanese, and includes word delimitation and part-of-speech annotation. We have newly annotated Long Word Unit delimitation and Bunsetsu (Japanese phrase)-based dependencies, including Bunsetsu boundaries, for CEJC. The UD of Japanese resources was constructed in accordance with hand-maintained conversion rules from the CEJC with two types of word delimitation, part-of-speech tags and Bunsetsu-based syntactic dependency relations. Furthermore, we examined various issues pertaining to the construction of UD in the CEJC by comparing it with the written Japanese corpus and evaluating UD parsing accuracy.

## introduction universal dependencies (ud) @xcite is a framework for consistent annotation of grammatical elements including parts of speech, morphological features, and syntactic dependencies in various human languages. ud provides a wide range of corpus types, encompassing written as well as spoken language data @xcite . the ud japanese team has also developed and maintained several resources @xcite , including ud_japanese-gsd, ud_japanese-pud @xcite and ud_japanese-bccwj @xcite . additionally, there are distinct versions of these corpora with long-unit word annotations @xcite . however, all of these resources are currently limited to written japanese. therefore, the present study addresses this gap by introducing ud resources for spoken japanese and leveraging the corpus of everyday japanese conversation (cejc). the resulting resource is referred to as ud_japanese-cejc. the cejc @xcite was recently released by ninjal, japan. this corpus represents a significant advancement in spoken language resources, as it comprises a large-scale collection of japanese conversations encompassing more than 200 hours. various types of audio and video data -including chat sessions, consultations, and meetings -were collected for the cejc corpus. the informants were carefully selected to ensure a balanced representation in terms of gender and age. the resource includes transcriptions and word segmentation information along with japanese partof-speech tags. in addition, we have newly annotated bunsetsu (japanese-phrase unit)-based dependencies for a subset of the cejc dataset, specifically in a 20-hour segment. building upon this, @xcite have proposed conversion rules to transform the bunsetsu-based dependencies into ud trees. by applying the conversion method proposed by @xcite , it becomes feasible to transform the cejc corpus into ud corpus, thereby facilitating the development of a substantial japanese ud spoken corpus. we present the outcomes of our endeavor in the development of a spoken ud japanese corpus using the dialogue-based cejc. an overview of our work is depicted in figure 1 . the cejc corpus provides audio and video data along with token mappings for dialogues, enabling the realization of ud mappings. in the following sections, we elaborate on the proposed annotation scheme and present essential statistics of the resulting dataset, drawing upon related research. furthermore, we evaluate the performance of a parser trained on both the ud japanese written and spoken corpora. we also highlight the distinctive features of ud_japanese-cejc in comparison to written and spoken language, with a specific emphasis on disfluencies such as reparanda, repairs, and fillers characteristic of dialogue-based ud. ## design of ud_japanese-cejc the following section provides a concise overview of cejc and outlines the construction of the ud version of cejc. sound file id yes text-sound alignment yes speaker id yes language variety no standard orthography yes capitalization not applicable pronunciation yes speaker overlap yes final punctuation not applicable other punctuation not applicable incomplete words yes fillers yes silent pauses yes incidents yes text-video alignment yes dialog act yes (iso-24617-2) intonation label partially yes ## parser evaluation we conducted experiments to assess the reproducibility and parsability of the cejc corpus. through a comparison between cejc and gsd, we illustrate the distinctions between spoken and written japanese in terms of ud annotation. ## conclusions this study introduces a novel ud japanese resource derived from the corpus of everyday japanese conversation (cejc), representing the first spoken language resource in the ud japanese framework. the ud resource was built upon transcriptions of audio files from individual speakers, accompanied by two types of video recordings (standard camera and omnidirectional 360-degree camera). whereas previous efforts have been limited in their incorporation of text-to-video alignment, this study presents a substantial treebank with video, surpassing existing ud resources in this aspect. in the future, we plan to primarily expand the annotation based on audio information; e.g., overlap markers similar to those used in the ud french rhapsodie @xcite . parser evaluations were conducted to compare the performance of the parser on ud_japanese-cejc (spoken) and gsd (written) datasets. the findings clearly demonstrate the challenges associated with parsing spoken japanese using a model trained on written corpora. the presence of fillers, disfluencies, and repairs significantly impacted tokenisation and pos tagging accuracy, highlighting the unique characteristics of spoken language that must be accounted for to improve parsing performance. to cejc subscribers through the dedicated download site on the cejc platform. additionally, the ud will be made available on the universal dependencies site and the ud japanese github repository 89 in a standoff format. this wider distribution will enable researchers to access and utilize the ud japanese cejc data for various linguistic analyses and applications. the spacy models employed in the conducted experiments will be made publicly available in github repository 10 . these resources will allow researchers and practitioners to utilize the models for their own natural language processing tasks and further contribute to the advancement of linguistic research in the field of japanese spoken language processing.