Verónica Romero

The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition

Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies.

Computer Assisted Transcription of Handwritten Text Images

To date, automatic handwriting recognition systems are far from being perfect and often they need a post editing where a human intervention is required to check and correct the results of such systems. We propose to have a new interactive, on-line framework which, rather than full automation, aims at assisting the human in the proper recognition- transcription process; that is, facilitate and speed up their transcription task of handwritten texts. This framework combines the efficiency of automatic handwriting recognition systems with the accuracy of the human transcriptor. The best result is a cost-effective perfect transcription of the handwriting text images.

Multimodal Interactive Handwritten Text Transcription

Read more and get great! Thats what the book enPDFd multimodal interactive handwritten text transcription will give for every reader to read this book. This is an on-line book provided in this website. Even this book becomes a choice of someone to read, many in the world also loves it so much. As what we talk, when you read more every page of this multimodal interactive handwritten text transcription, what you will obtain is something great.

Computer assisted transcription for ancient text images

Paleography experts spend many hours transcribing ancient documents and state-of-the-art handwritten text recognition systems are not suitable for performing this task automatically. We propose here a new interactive, on-line framework which, rather than full automation, aims at assisting the experts in the proper recognition-transcription process; that is, facilitate and speed up the transcription of old documents. This framework combines the efficiency of automatic handwriting recognition systems with the accuracy of the experts, leading to a cost-effective perfect transcription of ancient manuscripts.

Computer Assisted Transcription of Text Images and Multimodal Interaction

Current automatic handwriting text image recognition systems are far from being perfect and, in general, human intervention is required to check and correct the results of such systems. This is both inefficient and uncomfortable to the user. As an alternative to this post-editing process, a multimodal interactive approach is proposed, where user feedback is provided by means of touch-screen pen strokes and/or more traditional keyboard and mouse operation. Experiments suggest that, using this approach, significant amounts of user effort can be saved with respect to the conventional, non-interactive, post-editing process.

Interactive multimodal transcription of text images using a web-based demo system

This document introduces a web based demo of an interactive framework for transcription of handwritten text, where the user feedback is provided by means of pen strokes on a touchscreen. Here, the automatic handwriting text recognition system and the user both cooperate to generate the final transcription.

Handwritten text recognition for historical documents in the transcriptorium project

Transcription of historical handwritten documents is a crucial problem for making easier the access to these documents to the general public. Currently, huge amount of historical handwritten documents are being made available by on-line portals worldwide. It is not realistic to obtain the transcription of these documents manually, and therefore automatic techniques has to be used. tranScriptorium is a project that aims at researching on modern Handwritten Text Recognition (HTR) technology for transcribing historical handwritten documents. The HTR technology used in tranScriptorium is based on models that are learnt automatically from examples. This HTR technology has been used on a Dutch collection from 15th century selected for the tranScriptorium project. This paper provides preliminary HTR results on this Dutch collection that are very encouraging, taken into account that minimal resources have been deployed to develop the transcription system.

Explicit Modelling of Invariances in Bernoulli Mixtures for Binary Images

Bernoulli mixture models have been recently proposed as simple yet powerful probabilistic models for binary images in which each image pattern is modelled by a different Bernoulli prototype (component). A possible limitation of these models, however, is that usual geometric transformations of image patterns are not explicitly modelled and, therefore, each natural transformation of an image pattern has to be independentlymodelled using a different, rigidprototype. In this work, we propose a simple technique to make these rigid prototypes more flexible by explicit modelling of invariances to translation, scaling and rotation. Results are reported on a task of handwritten Indian digits recognition.

Context-aware Gestures for Mixed-Initiative Text Editing UIs

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Interacting with computers following peer review. The version of record is available online at: http://dx.doi.org/10.1093/iwc/iwu019

Category-Based Language Models for Handwriting Recognition of Marriage License Books

Handwritten marriage licenses books have been used for centuries by ecclesiastical institutions to register marriages. These documents have interesting information, useful for demography studies, organized in a list of individual marriage license records, such as an accounting book. The information in these books is usually collected by expert demographers that devote a lot of time to transcribe them. Despite the structure of the text, the automatic transcription and semantic information extraction of these documents is quite difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In this paper, we have defined some categories taking into account the semantic information included in the licenses. Then a category-based language model has been generated and integrated into the handwritten text recognition system. We study how the use of these categories can benefit not only the handwriting recognition step, but also the posterior semantic information extraction and knowledge discovery.