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semantic_chunking_of_a_youtube_video

The objective of this project is to extract high-quality, meaningful (semantic) segments from a specified YouTube video.

Workflow:

1.Download Video and Extract Audio: Download the video and separate the audio component.

2.Transcription of Audio: Using Whisper.ai an open-source Speech-to-Text model to transcribe the audio.

3.Time-Align Transcript with Audio: Describe the methodology and steps for aligning the transcript with the audio.

4.Semantic Chunking of Data: Slicing the data into audio-text pairs, using both semantic information from the text and voice activity information from the audio, with each audio-chunk being less than 15s in length.

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