AI-powered detection of filler words for precise editing.

AI-Automated Podcasts: Trends and New Tools

Summary: - This episode by Andrés Díaz explains how AI can detect filler words to enable precise editing for better pace, clarity, and credibility. - Fillers are words or short pauses that signal thinking; AI analyzes not just the words but prosody, pauses, and intonation, using NLP, signal analysis, and deep learning. - A practical workflow: record in high quality, let AI generate a rough transcription, then identify fillers by latency and prosody; you can remove them, replace with natural pauses, or turn them into smooth transitions. - A five-step DIY plan: 1) record well and design a filler guide, 2) transcribe accurately and align punctuation, 3) apply AI filler detection, 4) decide to remove/replace/pause, 5) review by listening with/without headphones. - Facts and features: Spanish fillers often include “este” with a pause; AI can distinguish fillers from emphasis on keywords; real-time detection is possible; tools can generate filler reports, support voice practice, and create editing templates; SEO keywords for discoverability are suggested. - Practical tip: pair each detected filler with an action (set silence duration, use a logical connector, or rephrase) and consider a rule like removing/replacing if a filler repeats more than twice in 40 seconds. - The message emphasizes balancing AI guidance with human judgment to maintain pace, clarity, and personality; outcomes aim for precise editing that keeps listeners engaged. - The episode also invites engagement, offers advertising contact, and ends with contact information for Andrés Díaz. Remeber you can contact me at [email protected]