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.