Building Parallel Monolingual Gan Chinese Dialects Corpus
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Abstract
Automatic language identification of an input sentence or a text written in similar languages, varieties or dialects is an important task in natural language processing. In this paper, we propose a scheme to represent Gan (Jiangxi province of China) Chinese dialects. In particular, it is a two-level and fine-grained representation using Chinese character, Chinese Pinyin and Chinese audio forms. Guided by the scheme, we manually annotate a Gan Chinese Dialects Corpus (GCDC) including 131.5 hours and 310 documents with 6 different genres, containing news, official document, story, prose, poet, letter and speech, from 19 different Gan regions. In addition, the preliminary evaluation on 2-way, 7-way and 20-way sentence-level Gan Chinese Dialects Identification (GCDI) justifies the appropriateness of the scheme to Gan Chinese dialects analysis and the usefulness of our manually annotated GCDC.