An Overview of Phonetic Encoding Algorithms

Vykhovanets, V. S.; Du, Jian Hua; Sakulin, Sergey

doi:10.1134/s0005117920100082

Cited by 4 publications

(3 citation statements)

References 52 publications

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“…In general, applications of phonetic encoding algorithms are widely used in modern information technology, both in the original and modified forms, a detailed list is given in Vykhovanets et al . (2020).…”

Section: Discussionmentioning

confidence: 99%

SoundexGR: An algorithm for phonetic matching for the Greek language

Kavros

Tzitzikas

2022

Nat. Lang. Eng.

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Text usually suffers from typos which can negatively affect various Information Retrieval and Natural Language Processing tasks. Although there is a wide variety of choices for tackling this issue in the English language, this is not the case for other languages. For the Greek language, most of the existing phonetic algorithms provide rather insufficient support. For this reason, in this paper, we introduce an algorithm for phonetic matching designed for the Greek language: we start from the original Soundex and we redesign and extend it for accommodating the Greek language’s phonetic rules, ending up to a family of algorithms, that we call ${\tt Soundex}_{GR}$ . Then, we report various experimental results showcasing how the algorithm behaves in different scenarios, and we provide comparative results for various parameters of the algorithm for revealing the trade-off between precision and recall in datasets with different kinds of errors. We also provide comparative results with matching using stemming, full phonemic transcription, and edit distance, that demonstrate that ${\tt Soundex}_{GR}$ performs better (indicatively, it achieves F-Score over 95% in collections of similar-sounded words). The simplicity, efficiency, and effectiveness of the proposed algorithm make it applicable and adaptable to a wide range of tasks.

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Section: Discussionmentioning

confidence: 99%

SoundexGR: An algorithm for phonetic matching for the Greek language

Kavros

Tzitzikas

2022

Nat. Lang. Eng.

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“…Since people often spell the same word in different ways, we have also introduced a word suggestion module. We have obtained the list of suggestions using double metaphone encoding [1]- [3] since the encoding can produce multiple encodings for the same word with different pronunciations, Jaro-Winkler similarity algorithm [4], [5] since the algorithm gives higher accuracy in multi-byte Bangla characters than other similar algorithms and (K-nearest neighbors) K-NN since it gives higher accuracy in suggesting closest Bangla words [6]. The double metaphone encoding method has been used to encode the input into corresponding English letters, the Jaro-Winkler similarity algorithm compares the encodings to determine similarities, and K-NN generates suggestions based on the nearest matches.…”

Section: Introductionmentioning

confidence: 99%

Inclusive bidirectional conversion system between Chittagonian and standard Bangla

Hossain

Milon²,

Sabbir

et al. 2022

Bulletin EEI

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In recent years, the Bangla language has come out as a very prominent figure in the world of natural language processing. Many researchers have produced exemplary works on the language, but there has not been any notable work on its highly enriched dialects due to the lack of resources and the diversity and complexity in its grammatical structure. This paper has suggested a bidirectional conversion system for one of the most widely used dialects of Bangla; the Chittagonian dialect. Our method employs a bidirectional lexicon that uses binary search, word-to-word mapping, and morphological transformations. The system has achieved an accuracy rate of 95.86% for Chittagonian to standard Bangla and 93.89% in the case of standard Bangla to Chittagonian. We have also provided an efficient word suggestion module, and it has yielded satisfactory results.

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“… 3 The use of phonetic algorithms significantly improved the efficiency of record linkage between the two sources. In particular, we use both the “SOUNDEX” and the “NYSIIS” algorithms (Vykhovanets et al 2020). …”

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confidence: 99%

Immigration, Poverty, and Infant and Child Mortality in the City of Madrid, 1916–1926

Mazzoni

Fariñas²

2023

Soc. sci. hist.

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In this paper, we study differential infant and child mortality according to the origin of the mothers, natives of Madrid or immigrants, between 1916 and 1926. From 1880 to 1939, Madrid experienced spectacular demographic growth, with a massive influx of immigrants, mainly from the Castilian Plateau. Using the city’s records of births and deaths, which we linked for the study period, we demonstrate an important spatial heterogeneity in infant and child mortality across the city. Although the development of the town was planned in the 1860s, the infrastructure and the real estate market were overwhelmed by the continuous arrival of new inhabitants. Moreover, major investments in public health increased the gap between the wealthy districts and peripheral areas. These improvements deepened inequality. During years marked by the waves of the influenza pandemic, we isolate the impact of poverty, which threatened the survival of newborns through poor nutrition, deficient hygienic infrastructures and deplorable housing conditions. Such features explain the impressive association between summer and the risk of dying from enteritis, diarrhea and other diseases of the same type among weaned children. However, the mortality differentials between the offspring of native and migrant mothers were surprisingly small, which we explained in terms of behavioral adaptation to the large city and its mass society.

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An Overview of Phonetic Encoding Algorithms

Cited by 4 publications

References 52 publications

SoundexGR: An algorithm for phonetic matching for the Greek language

SoundexGR: An algorithm for phonetic matching for the Greek language

Inclusive bidirectional conversion system between Chittagonian and standard Bangla

Immigration, Poverty, and Infant and Child Mortality in the City of Madrid, 1916–1926

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