Bangla Lip-to-Text Sentence Level Dataset

Published: 22 May 2025| Version 1 | DOI: 10.17632/5hygp4hskz.1
Contributor:
Abdul Hasib Uddin

Description

The dataset is created as follows: Step 1: Original Bangla videos were collected from YouTube Bangladesh National Television Debates and Talk Shows. Step 2: Original videos are cut into 3-second duration mini videos. Step 3: Face area from each frame of these mini videos is segmented using MediaPipe FaceMesh. Step 4: Only those videos were chosen in which all of the frames contain exactly one face. Step 5: Audios are cut and embedded in the chosen videos (folder: Face_Only_Videos_with_Audio). Step 6: Bangla audio-to-text transcriptions of the chosen videos were generated using the Wav2Vec2 foundation model pre-trained on the Mozilla 300m Bengali Commonvoice dataset (folder: First_Transcriptions). Step 7: Videos with no transcription texts were filtered out. Step 8: A simplified transliteration for each of the translations was created (folder: Transliteration_Informal).

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Institutions

  • Khulna University

Categories

Natural Language Processing, Speech Recognition, Visual Language, Video Processing

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