AI-assisted removal of filler words from video recordings
Blog post from Daily
The text discusses a demo for removing filler words (disfluencies) from videos using AI-powered workflows with LLMs (Large Language Models). The demo utilizes Deepgram and Whisper as two transcription options, allowing users to remove disfluencies from uploaded MP4 files. The process involves uploading the file, processing it in the background, and then downloading the processed output. The demo showcases how to implement this functionality using Python and Quart, a server framework. It also highlights the importance of human intuition and ingenuity in enhancing LLM-powered applications. Additionally, the text mentions that storage, security, and production use cases should be considered when implementing AI-powered post-processing effects.
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