CALAM: Linguistic Structure to Annotate Handwritten Text Image Corpus

Author(s):  
Prakash Choudhary ◽  
Neeta Nain
2021 ◽  
Vol 1848 (1) ◽  
pp. 012015
Author(s):  
Yintong Wang ◽  
Wenjie Xiao ◽  
Shuo Li

2020 ◽  
Vol 24 (3) ◽  
pp. 527-562
Author(s):  
Ulrike Zeshan ◽  
Nick Palfreyman

AbstractThis article sets out a conceptual framework and typology of modality effects in the comparison of signed and spoken languages. This is essential for a theory of cross-modal typology. We distinguish between relative modality effects, where a linguistic structure is markedly more common in one modality than in the other, and absolute modality effects, where a structure does not occur in one of the modalities at all. Using examples from a wide variety of sign languages, we discuss examples at the levels of phonology, morphology (including numerals, negation, and aspect) and semantics. At the phonological level, the issue of iconically motivated sub-lexical components in signs, and parallels with sound symbolism in spoken languages, is particularly pertinent. Sensory perception metaphors serve as an example for semantic comparison across modalities. Advocating an inductive approach to cross-modal comparison, we discuss analytical challenges in defining what is comparable across the signed and spoken modalities, and in carrying out such comparisons in a rigorous and empirically substantiated way.


2021 ◽  
Vol 7 (s3) ◽  
Author(s):  
Matthew Stave ◽  
Ludger Paschen ◽  
François Pellegrino ◽  
Frank Seifart

Abstract Zipf’s Law of Abbreviation and Menzerath’s Law both make predictions about the length of linguistic units, based on corpus frequency and the length of the carrier unit. Each contributes to the efficiency of languages: for Zipf, units are more likely to be reduced when they are highly predictable, due to their frequency; for Menzerath, units are more likely to be reduced when there are more sub-units to contribute to the structural information of the carrier unit. However, it remains unclear how the two laws work together in determining unit length at a given level of linguistic structure. We examine this question regarding the length of morphemes in spoken corpora of nine typologically diverse languages drawn from the DoReCo corpus, showing that Zipf’s Law is a stronger predictor, but that the two laws interact with one another. We also explore how this is affected by specific typological characteristics, such as morphological complexity.


2020 ◽  
Vol 22 (1) ◽  
pp. 51-55
Author(s):  
Dawn Behrend

Poverty, Philanthropy and Social Conditions in Victorian Britain published by Adam Matthew Digital is comprised of primary digital materials culled from three major archives in Britain and the UK focused on the experience of poverty in Victorian Britain and efforts involving economic, government, and social reform such as the Poor Law, workhouses, settlement houses, and philanthropic initiatives. Content is derived from the National Archives at Kew, British Library, and Senate House Library and includes pamphlets, correspondence, newspaper clippings, books, and other resources. A small portion of the collection utilizes Adam Matthew Digital’s Handwritten Text Recognition (HTR) to enable keyword searching of handwritten documents. The digitized images and documents are clear, searchable, and user-friendly to access, save, and share. Contract provisions are standard to the product with authenticated access across institutional locations and guidelines for Interlibrary Loan sharing. Pricing is determined by institutional size and enrollment. While the product is a one-time purchase, annual hosting fees apply for ongoing access. Content is currently heavily derived from one archive, the Senate House Library, with pamphlets from this source making up nearly half of the total holdings. Users seeking access to a more extensive collection of similar material may prefer subscribing to JSTOR which includes JSTOR 19th Century British Pamphlets with over 26,000 pamphlets along with secondary scholarly journals and eBooks on the Victorian era. While not providing the primary sources of Poverty, Philanthropy and Social Conditions in Victorian Britain or JSTOR, Historical Abstracts may be an alternative resource in providing access to notable scholarly resources on the period.


MANUSYA ◽  
2011 ◽  
Vol 14 (1) ◽  
pp. 79-97
Author(s):  
Unchalee Singnoi

The present study focuses on the plant naming system in the Thai language based on 1) Brent Berlin’s general principles of categorization of plants and animals in traditional societies (Berlin, 1974, 1992) which suggest that it is worthwhile to think about a plant taxonomy system on the basis of plant names since the names provide the valid key to folk taxonomy and 2) Lakoff’s central guiding principles of cognitive linguistics (Lakoff and Johnson, 2003 and Lakoff 1987). Data on plant names collected from printed materials are selectively analyzed. The study examines the linguistic structure, folk taxonomy and conceptualization of plant terms in the Thai language. It is found that there exists in the Thai language a complex and practical plant naming system establishing a relationship between language, cognition and culture.


Author(s):  
SIMON GÜNTER ◽  
HORST BUNKE

Handwritten text recognition is one of the most difficult problems in the field of pattern recognition. In this paper, we describe our efforts towards improving the performance of state-of-the-art handwriting recognition systems through the use of classifier ensembles. There are many examples of classification problems in the literature where multiple classifier systems increase the performance over single classifiers. Normally one of the two following approaches is used to create a multiple classifier system. (1) Several classifiers are developed completely independent of each other and combined in a last step. (2) Several classifiers are created out of one prototype classifier by using so-called classifier ensemble creation methods. In this paper an algorithm which combines both approaches is introduced and it is used to increase the recognition rate of a hidden Markov model (HMM) based handwritten word recognizer.


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