A Large-Scale Vietnamese Lip-Reading Dataset for Visual Speech Recognition

The Vietnamese Lip Reading (VLR) dataset is a large-scale audiovisual corpus created to support word-level visual speech recognition in Vietnamese. It consists of segmented video clips paired with time-aligned transcriptions at the word level. The video content was collected from publicly available Vietnamese YouTube videos, selected for clear frontal face visibility and natural speaking conditions.

To ensure consistency and visual clarity, each video was automatically processed to center the speaker’s face within the frame. The accompanying transcriptions were generated using automated speech recognition and provide precise timing information for each word spoken. These aligned video-text pairs were drawn from a diverse set of speakers and recording scenarios, capturing the natural variability of Vietnamese spoken language in uncontrolled, real-world environments.

The final dataset includes approximately 116,000 segmented video–transcript pairs. Its scale captures the complexity of Vietnamese visual speech and provides a structured resource suitable for various modeling and analysis tasks.

越南唇语识别（Vietnamese Lip Reading, VLR）数据集是一款大规模音视频语料库，旨在支撑越南语单词级视觉语音识别任务。该数据集由经过分割的视频片段与时间对齐的单词级转录文本组成。其视频内容采集自公开可用的越南语YouTube视频，筛选标准为正面面部清晰可见且说话场景自然。
为保证一致性与视觉清晰度，所有视频均经过自动处理，将说话者面部置于画面中央。配套的转录文本通过自动语音识别生成，可为每个说出的单词提供精准的时间信息。这些对齐后的视频-文本对源自多样化的说话者与录制场景，覆盖了非受控真实环境中越南语口语的自然变化性。
最终的数据集包含约11.6万条分割后的视频-转录文本配对样本。其规模足以覆盖越南语视觉语音的复杂性，同时提供了适用于各类建模与分析任务的结构化资源。