Emdros is a text database engine for linguistic analysis or annotation of text. It is appliccable especially in corpus linguistics for storing and retrieving linguistic analyses of text, at any linguistic level. Emdros implements the EMdF text database model and the MQL query language. In this paper, I present both, and give an example of how Emdros can be useful in computational linguistics.

Image retrieval is an important research field which has received great attention in the last decades. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. Query in this system contains some keywords and an input...

This paper describes a database of on-line handwritten patterns mixed of text, figures, tables, maps, diagrams and so on. Now, pen-based and touch-based interfaces are spreading into people and their surfaces are getting large. People can write and draw mixed objects without paying attention on the difference of objects or the mode change. Moreover, they may write text in any direction in combi...

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This paper presents a method for an automatic compilation of a phonologically rich text database, which is used in a concatenative text-to-speech (TTS) synthesis system. In this method, linguistic features are predicted from text using Festival’s linguistic engine. A set of phonological units for a specific text is compiled from attribute value lists (AVLs). Phrases/sentences that contain the p...

Methods for linking individuals across historical data sets, typically in combination with AI based transcription models, are developing rapidly. Probably the single most important identifier is personal names. However, names prone to enumeration and errors although modern methods designed handle such challenges these sources of critical should be minimized. For this purpose, improved large-sca...

Combined text and relational database support is increasingly recognized as an emerging need of industry, spanning applications requiring text elds as parts of their data (e.g., for customer support) to those augmenting primary text resources by conventional relational data (e.g., for publication control). In this paper, we propose extensions to SQL2 that provide exible and eecient access to st...