The Need: a book you want to search, but it is only paper I have a 19th-century commentary on the five books of Moses. It has six volumes. I wanted all of it inside my own search tool, so I could ask a question in Korean and get the commentary back as one of the sources. The usual way is to scan the pages and turn them into text. That worked badly for me, and the way it worked badly led to the cheaper answer. ...
I have a lot of Bible material that I cannot search together. Sermon recordings turned into text. A commentary that I scanned page by page. A few Bible translations. Each one has its own search, or no search at all. When I wonder “what did the Bible and the preachers say about this?”, I open four things and read. So I built one box where I type a question, and it answers using all of them, with a number after every claim that points to the exact source. ...
I like the idea of running my own AI. No bill, no data leaving my house. So when I needed to clean up a long transcript, I tried the local way first. The result changed my mind about when “free and local” is worth it. The Need: Speech-to-Text Gets Names Wrong Whisper turns a Korean sermon into text very well, but it makes a certain kind of mistake. It hears Bible words as ordinary words. A town name becomes a nonsense word. A book of the Bible becomes a different book. And one example I like: the Korean word for Psalms, sipyeon (시편), sounds almost like “ten pyeon” (10편). Whisper wrote “10” where the speaker said “Psalms”. ...
A transcript without speaker names is hard to use. If an audio file has two people talking, I need to know which words came from which person. My pipeline can label speakers automatically. The question was whether I could trust the labels. I did not want to trust them just because the output looked clean. So I made an answer key by hand, and I let the computer grade itself against it. ...