Transcription alignment of Latin manuscripts using hidden Markov models
Andreas Fischer|Volkmar Frinken|Alícia Fornés|Horst Bunke
Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used training recognition systems. In this paper, we introduce the Saint Gall database includes as well transcription Latin manuscript from 9th century written in Carolingian script. Although available is high quality human reader, spelling words not accurate when compared with image. Hence, poses several challenges alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an system based on character Hidden Markov Models cope these efficiently aligns complete document pages. On database, demonstrate considerable accuracy achieved, even weakly trained models.