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Lexicon and attention based handwritten text recognition system

Kumari Lalita, Singh Sukhdeep, Rathore Vaibhav Varish Singh, Sharma Anuj

Machine Graphics and Vision

2022

Vol. 31, No. 1/4

75--92

The handwritten text recognition problem is widely studied by the researchers of computer vision community due to its scope of improvement and applicability to daily lives. It is a sub-domain of pattern recognition. Due to advancement of computational power of computers since last few decades neural networks based systems heavily contributed towards providing the state-of-the-art handwritten text recognizers. In the same direction, we have taken two state-of-the art neural networks systems and merged the attention mechanism with it. The attention technique has been widely used in the domain of neural machine translations and automatic speech recognition and now is being implemented in text recognition domain. In this study, we are able to achieve 4.15% character error rate and 9.72% word error rate on IAM dataset, 7.07% character error rate and 16.14% word error rate on GW dataset after merging the attention and word beam search decoder with existing Flor et al. architecture. To analyse further, we have also used system similar to Shi et al. neural network system with greedy decoder and observed 23.27% improvement in character error rate from the base model.

The methodological approach in the management of conservation data for stucco artifacts

Capasso Filippo Edoardo, Castiello Francesca, Dichiara Simona, Giandomenico Manuel, Lacopino Natalie, Maddalena Erika, Mauri Camilla, Muca Sokol, Roscigno Mariagiulia, Schiattone Sofia

Ochrona Dziedzictwa Kulturowego

2019

Nr 8

65--72

Some 90 Roman stucco fragments, coming from the Archaeological Park of Herculaneum, underwent in the conservation-restoration process within the Istituto Superiore per la Conservazione ed il Restauro (ISCR) laboratories in Matera. Before the conservation activity, the wide number of this manufacts brought us to design a data management system, suitable for stucco findings. Nowadays, the international approaches towards data management of this kind of artifacts is extremely heterogeneous and the absence of an unequivocal data sheet makes the cataloguing very complex and laborious. Our studies on the fragments allowed us to draw up a specific cataloguing instrument for this kind of material, carried out with a software structuring data collection in order to respond to different necessities, such as completeness and updatability, required by an efficient data management system.

Constructions with Lexical Integrity

Asudeh A., Dalrymple M., Toivonen I.

Journal of Language Modelling

2013

Vol. 1, No. 1

1--54

Construction Grammar holds that unpredictable form-meaning combinations are not restricted in size. In particular, there may be phrases that have particular meanings that are not predictable from the words that they contain, but which are nonetheless not purely idiosyncratic. In addressing this observation, some construction grammarians have not only weakened the word/phrase distinction, but also denied the lexicon/grammar distinction. In this paper, we consider the word/phrase and lexicon/grammar distinction in light of Lexical-Functional Grammar and its Lexical Integrity Principle. We show that it is not necessary to remove the word/phrase distinction or the lexicon/grammar distinction to capture constructional effects, although we agree that there are important generalizations involving constructions of all sizes that must be captured at both syntactic and semantic levels. We use LFG’s templates, bundles of grammatical descriptions, to factor out grammatical information in such a way that it can be invoked either by words or by construction-specific phrase structure rules. Phrase structure rules that invoke specific templates are thus the equivalent of phrasal constructions in our approach, but Lexical Integrity and the separation of word and phrase are preserved. Constructional effects are captured by systematically allowing words and phrases to contribute comparable information to LFG’s level of functional structure; this is just a generalization of LFG’s usual assumption that “morphology competes with syntax” (Bresnan, 2001).