Hascheck - The Croatian Academic Spelling Checker

Dembitz, Šandor; Knežević, Predrag; Sokele, Mladen

doi:10.1007/978-1-4471-0575-6_14

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…To remind ourselves, Hascheck started operating as the first spellchecker for Croatian, hence as an under‐resourced language spellchecker, with text coverage of 87% on average for the first three months of public functioning. The text coverage increased relatively quickly to 95%44.…”

Section: The Futurementioning

confidence: 99%

“…All data presented in thisSection refer to web‐phase traffic. Some interesting data on e‐mail traffic can be found in 44.…”

Section: Traffic Datamentioning

confidence: 99%

“…The anticipation can tell the maintainer how many man‐hours per certain period of time are needed in order to perform the complete task of learning.This is extremely important in cases of non‐funded projects as many spellcheckers for non‐central and under‐resourced languages have turned out to be. The particular reasons for not funding Hascheck in its developmental phase are given in 44.Since workload in the operational phase has never exceeded 40 h monthly per maintainer, we have never asked for any type of funding later. However, the Agrokor Group, the largest private company in Croatia and one of the leading regional companies, recognized Hascheck as an infrastructural service valuable for Croatia and gave it a $40 000 grant in March 2010.…”

Section: Behavior Of Spellchecking Parameters In Timementioning

confidence: 99%

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Advantages of online spellchecking: a Croatian example

2010

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Online spellchecking is commonly regarded as an auxiliary way of performing spellchecking. However, it offers a unique opportunity to constantly improve spellchecker linguistic functionality through interaction with the community of spellchecker users. Such a possibility is crucial for spellchecking in non‐central and under‐resourced languages, in order to overcome gaps in NLP tools between them and central languages. The paper describes Hascheck, a Croatian online spellchecker able to learn words from texts it receives. It started as the first Croatian spellchecker, hence as a basic NLP tool for an under‐resourced language, but due to its learning ability it demonstrates linguistic functionality comparable to that of conventional central‐language spellcheckers. Based on these experiences we also discuss the future of online spellchecking in the context of global NLP tasks. Copyright © 2010 John Wiley & Sons, Ltd.

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Section: The Futurementioning

confidence: 99%

“…All data presented in thisSection refer to web‐phase traffic. Some interesting data on e‐mail traffic can be found in 44.…”

Section: Traffic Datamentioning

confidence: 99%

Section: Behavior Of Spellchecking Parameters In Timementioning

confidence: 99%

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Advantages of online spellchecking: a Croatian example

2010

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“…Moreover, there are still no suitable open datasets for research purposes. A rare positive example is the n-gram system collected in scope of Hascheck, a Croatian online academic spell checking service [3] [4].…”

Section: Introductionmentioning

confidence: 99%

N-gram Based Croatian Language Network: Application in a Smart Environment

Soic

Vuković

2022

JCOMSS

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In the field of natural language processing, language networks represent a method for observing linguistic units and their interactions in different linguistic contexts. This paper uses the previously presented Croatian language network for building a solution capable of generating spoken notifications in Croatian language. The novelty of this paper is that it proposes an approach for generating spoken notifications in smart environments by combining specialized services that enable interaction with the environment and human users. The process employed for generating spoken notifications is described in detail. Also, a novel contribution of this paper is the case-study evaluation of the proposed approach in a smart home environment.

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