The hottest Transcription Substack posts right now

A reliable four-step pipeline handled hundreds of episodes unattended: raw ASR → deterministic cleanup → editorial LLM pass → publish/sync, running Codex CLI on a remote VM so the whole job could finish without babysitting.
A strict style guide, correction maps, and a locked editorial prompt made the LLM behave like a conservative editor, fixing ASR phonetic errors, names, punctuation, and obvious typos without adding facts or changing meaning.
The results were published with per-episode pages, audio players, navigation, and SEO, and an automated watcher now transcribes new episodes automatically, making the archive searchable for humans and LLMs and enabling future personalized learning tools.

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Attend a virtual lunch with the author of 'Fuckery' to hear about her stories and work
Use Fathom to get a concise summary of virtual meetings, making note-taking easier

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Creating a speaker identification database by utilizing existing data can be achievable in a short amount of time.
Manually labeling missing speakers can enhance the accuracy and functionality of the database.
Segmented transcripts based on speaker identification can enrich the overall user experience.

The ad detector is a work in progress, needing more refinement to distinguish ads from general content.
The detector combines AI models to analyze show content and identify potential advertisements.
Next steps involve improving accuracy, creating a web UI, and expanding the backlog of indexed audio content.

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AI tools like MacWhisper and OpenAI's command-line tools can help automate transcription of lectures, making it easier to generate accurate transcripts of recorded lessons.
The use of AI-powered transcription tools like Whisper model or paying OpenAI can benefit students, including those who are hearing-impaired, by providing high-quality transcriptions that enhance their learning experience.
The advancements in transcription technology have made high-quality voice-to-text transcriptions more reliable and accessible, improving the overall educational experience for all students.

Using apps like Otter AI can make students feel they can zone out during classes. They think they don't have to pay attention because they can always check the notes later.
These tools might lead to less real engagement in learning. If students can just ask a chatbot for the important stuff, why bother attending the lecture?
The focus in education seems to be more on grades than real learning. This shows how the system values shortcuts over meaningful experiences.