OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset

• URL: http://arxiv.org/abs/2301.06375v1
• Date: Mon, 16 Jan 2023 11:40:50 GMT
• Title: OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset
• Authors: Jeongkyun Park, Jung-Wook Hwang, Kwanghee Choi, Seung-Hyun Lee, Jun Hwan Ahn, Rae-Hong Park, Hyung-Min Park
• Abstract summary: Open Large-scale Korean Audio-Visual Speech (OLKAVS) dataset is the largest among publicly available audio-visual speech datasets. The dataset contains 1,150 hours of transcribed audio from 1,107 Korean speakers in a studio setup with nine different viewpoints and various noise situations.
• Score: 14.619865864254924
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Inspired by humans comprehending speech in a multi-modal manner, various audio-visual datasets have been constructed. However, most existing datasets focus on English, induce dependencies with various prediction models during dataset preparation, and have only a small number of multi-view videos. To mitigate the limitations, we recently developed the Open Large-scale Korean Audio-Visual Speech (OLKAVS) dataset, which is the largest among publicly available audio-visual speech datasets. The dataset contains 1,150 hours of transcribed audio from 1,107 Korean speakers in a studio setup with nine different viewpoints and various noise situations. We also provide the pre-trained baseline models for two tasks, audio-visual speech recognition and lip reading. We conducted experiments based on the models to verify the effectiveness of multi-modal and multi-view training over uni-modal and frontal-view-only training. We expect the OLKAVS dataset to facilitate multi-modal research in broader areas such as Korean speech recognition, speaker recognition, pronunciation level classification, and mouth motion analysis.

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