As described in Vitevitch & Luce (2016) a phonological—or similarity—neighborhood consists of a set of similar-sounding form-based representations that are activated in memory based on how closely those word-forms resemble the stimulus input. Much research has examined how the number and nature of words in a similarity neighborhood influence spoken word perception, spoken word production, word-learning, memory, and other cognitive processes.
There are a variety of ways to operationally define phonological similarity (e.g., "cohort," Phonological Levenshtein Distance 20 [PLD20], etc.). A simple and widely employed method uses a variant of what is known as the Hamming or Levenshtein distance. According to this method, a neighbor of a target word is determined on the basis of the addition, deletion, or substitution of a phoneme in any position of the target word (Greenberg & Jenkins 1964, Landauer & Streeter 1973). For example, the target word cat has neighbors such as scat (via one-phoneme addition); _at (via one-phoneme deletion); and fat, cot, and cab (via one-phoneme substitutions).
The collection of neighbors computed in this manner is commonly referred to as the phonological similarity neighborhood. The number of neighbors is referred to as neighborhood density. By computing the mean of the frequency of occurrence of the neighbors, one obtains a value referred to as neighborhood frequency.
For a review of how neighborhood density influences various cognitive processes consider reading:
Just as we have made available to researchers a web-based calculator to compute phonotactic probability in English, and more recently in other languages, we are now making available a web-based calculator to compute phonological similarity neighborhoods (including neighborhood density and neighborhood frequency).
The English similarity neighborhood calculator uses the same computer-readable phonetic transcription used in the Phonotactic Probability Calculator (PPC) in English.
Recently Dr. Faisal Aljasser (Qassim University) visited KU as a Fulbright Scholar. Together with colleagues at KU Information Technology a similarity neighborhood calculator was also made for Arabic. If you use the calculator to estimate phonological similarity neighborhoods for a set of real Arabic words or made-up nonwords, please be sure to cite this article:
Manuscript in preparation.
The computer readable transcription (and the IPA equivalents) required as input to the Arabic Phonotactic Probability Calculator (APPC) is also required as input to the calculator of Arabic phonological similarity neighborhoods.
The Child Corpus Calculator for Phonotactic Probability and Neighborhood Density that was previously made available by Holly Storkel in the Department of Speech-Language-Hearing: Sciences and Disorders at the University of Kansas has now been included in this web site. If you use the new version of the Child Corpus Calculator to estimate neighborhood density (or phonotactic probability) in a set of real words or made-up nonwords, please continue to cite this article:
Storkel, H. L. & Hoover, J. R. (2010). An on-line calculator to compute phonotactic probability and neighborhood density based on child corpora of spoken American English. Behavior Research Methods, 42, 497-506.
Also on this page is the Beginning Spanish Lexicon, which is a list of Spanish words that adults might typically encounter in a formal language class at a college or university. If you use this calculator to estimate the phonological similarity neighborhoods that you might expect in a learner of Spanish for a set of real Spanish words or made-up nonwords, please continue to cite this article:
Vitevitch, M.S., Stamer, M.K. & Kieweg, D. (2012). The Beginning Spanish Lexicon: A Web-based interface to calculate phonological similarity among Spanish words in adults learning Spanish as a foreign language. Second Language Research, 28, 103-112.
Furthermore, I would greatly appreciate receiving a reprint (electronic or hard copy) of any published work that uses any of these Calculators. Reprints may be sent to:
Department of Psychology
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OR via e-mail: email@example.com