Identifying cognates by phonetic and semantic similarity

Kondrak, Grzegorz

doi:10.3115/1073336.1073350

Cited by 49 publications

(45 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We employ Arabic-English and Swahili-English bitexts to extract a training set (corpora of sizes 5.4M and 14K sentence pairs, respectively), using a cognate discovery technique (Kondrak, 2001). Phonetically and semantically similar strings are classified as cognates; phonetic similarity is the string similarity between phonetic representations, and semantic similarly is approximated by translation.…”

Section: Resourcesmentioning

confidence: 99%

Cross-Lingual Bridges with Models of Lexical Borrowing

Tsvetkov

Dyer

2016

jair

View full text Add to dashboard Cite

Linguistic borrowing is the phenomenon of transferring linguistic constructions (lexical, phonological, morphological, and syntactic) from a "donor" language to a "recipient" language as a result of contacts between communities speaking different languages. Borrowed words are found in all languages, and-in contrast to cognate relationships-borrowing relationships may exist across unrelated languages (for example, about 40% of Swahili's vocabulary is borrowed from the unrelated language Arabic). In this work, we develop a model of morpho-phonological transformations across languages. Its features are based on universal constraints from Optimality Theory (OT), and we show that compared to several standard-but linguistically more naïve-baselines, our OT-inspired model obtains good performance at predicting donor forms from borrowed forms with only a few dozen training examples, making this a cost-effective strategy for sharing lexical information across languages. We demonstrate applications of the lexical borrowing model in machine translation, using resource-rich donor language to obtain translations of out-of-vocabulary loanwords in a lower resource language. Our framework obtains substantial improvements (up to 1.6 BLEU) over standard baselines.

show abstract

Section: Resourcesmentioning

confidence: 99%

Cross-Lingual Bridges with Models of Lexical Borrowing

Tsvetkov

Dyer

2016

jair

View full text Add to dashboard Cite

show abstract

“…Kondrak (2001) uses a modified LD measure to detect cognates, as do Schepens, Dijkstra and Grootjen (2012) on a larger scale, and using only standard orthography. They report a classification performance of over 90%.…”

Section: Related Workmentioning

confidence: 99%

Measuring Foreign Accent Strength in English

et al. 2014

View full text Add to dashboard Cite

With an eye toward measuring the strength of foreign accents in American English, we evaluate the suitability of a modified version of the Levenshtein distance for comparing (the phonetic transcriptions of) accented pronunciations. Although this measure has been used successfully inter alia to study the differences among dialect pronunciations, it has not been applied to studying foreign accents. Here, we use it to compare the pronunciation of non-native English speakers to native American English speech. Our results indicate that the Levenshtein distance is a valid native-likeness measurement, as it correlates strongly (r = -0.81) with the average “native-like” judgments given by more than 1000 native American English raters.

show abstract

“…Cognates are words in different languages having the same etymology and a common ancestor. The methods for cognate detection proposed so far are mostly based on orthographic/phonetic and semantic similarities (Kondrak, 2001;Frunza et al, 2005), but the term "cognates" is often used with a somewhat different meaning, denoting words with high orthographic/phonetic and cross-lingual meaning similarity, the condition of common etymology being left aside. We focus on etymology and we introduce an automatic strategy for detecting pairs of…”

Section: Relationships Identificationmentioning

confidence: 99%