# Reliable Editions from Unreliable Components: Estimating Ebooks from Print Editions Using Profile Hidden Markov Models

arXiv: https://arxiv.org/abs/2204.01638 · HTML: https://mlsanity.com/paper/2204.01638/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Apr 2022.

## Built on by (most cited first, 1 of 1)

- [ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis](https://mlsanity.com/paper/2207.09765/) (2022)

## Abstract (arXiv)

A profile hidden Markov model, a popular model in biological sequence analysis, can be used to model related sequences of characters transcribed from books, magazines, and other printed materials. This paper documents one application of a profile HMM: automatically producing an ebook edition from distinct print editions. The resulting ebook has virtually all the desired properties found in a publisher-prepared ebook, including accurate transcription and an absence of print artifacts such as end-of-line hyphenation and running headers. The technique, which has particular benefits for readers and libraries that require books in an accessible format, is demonstrated using seven copies of a nineteenth-century novel.