PodcastsToText Launches AI Podcast Studio With Transcription, Speaker Detection, Chapters and Show Notes

PodcastsToText: Transcript Editor with AI features

NEW YORK – September 25, 2026 – PodcastsToText has launched a podcast studio that transcribes an episode from a Spotify, Apple Podcasts, YouTube or TikTok link, separates and names the speakers, and generates chapters, show notes and social copy from the full transcript.

What changed

• A three-zone editor. The episode and its artwork sit on the left, the transcript in the middle, and an inspector on the right carrying chapters, speakers, summary, show notes, translation and a question box. Clicking any word seeks the audio to it.
• Speaker detection you can correct. Speakers are detected automatically, then renamed, coloured, merged and marked as host. A merge is stored as an alias rather than a rewrite, so it can be undone, and every export reads the corrected names.
• YouTube and TikTok. A YouTube link uses the video’s own caption track where one exists, and the video itself becomes the playback source inside the editor. A TikTok link pulls the real audio, so the transcript is timed against media we hold rather than an embed we cannot seek.
• AI chapters, show notes and content. Chapters carry real timestamps taken from the transcript and appear in the editor as a coloured spine down the left edge of the words. From the same transcript, PodcastsToText can generate a summary, blog post, newsletter, social posts for X, LinkedIn and Instagram, SEO metadata, a YouTube description and pull quotes. The generated content is saved with the episode and can be regenerated whenever needed.
• Translation. A finished transcript can be translated in place and long episodes resume across requests rather than failing at a timeout.
• Ask the episode. A chat box in the inspector answers questions about the episode and keeps the conversation in context, so follow-up questions can be asked without starting over.

Why it matters

Transcription has been a solved problem for years. What has not been solved is the gap between a wall of text and anything a publisher can use: until now, getting chapters, show notes and social copy out of an episode meant exporting a transcript, pasting it into a chatbot in pieces small enough to fit, and reassembling the answers by hand.

That last step is where the accuracy was being lost. A two-hour episode does not fit in one model call, and a tool that quietly truncates it produces show notes describing the first half hour, fluently, with nothing on the page saying so. PodcastsToText splits a long episode, condenses each part, and generates from the whole thing. Chapter lists cover the full runtime rather than stopping a third of the way in and looking complete.

The practical result for a podcaster is that an episode goes from a published link to a transcript, a chapter list, show notes and a week of social drafts in one sitting, and every one of those artefacts is editable in the place it was made.

Availability

The studio is live now at podcaststotext.com. No installation is required, and no file upload is needed for a public episode: the link is enough. Transcripts export as plain text, SRT and VTT subtitles, timed JSON, Word and PDF.

“I kept watching people export a perfectly good transcript and then spend an hour pasting it into a chatbot in chunks to get a chapter list out of it. The transcript was never the deliverable. What people actually want is the chapters, the show notes and the pull quotes, and they want them to be about the whole episode rather than the first thirty minutes that happened to fit in the context window.”
— Marios Stylianou, Founder, PodcastsToText

ABOUT PODCASTSTOTEXT

PodcastsToText turns spoken audio into text people can actually use.

Paste a Spotify, Apple Podcasts, YouTube or TikTok link, or upload a file, and it returns a timestamped transcript with speaker labels, then an editing studio that generates chapters, show notes, summaries and social copy from it.

The same engine is available to developers as a REST API and to AI agents as a hosted MCP server. It was founded in 2025 by Marios Stylianou and is self-funded.

Media Contact
Company Name: PodcastsToText
Contact Person: Marios Stylianou
Email: Send Email
Country: Cyprus
Website: podcaststotext.com