Calculation of Cohort size for the list of Persian high-frequency spondee words
Abstract
Background and Aim: Setting of candidates for a word with similar beginnings is known as the Cohort size. Despite the importance of the number and properties of candidates in word recognition, so far, in none of the tests made for Persian language, the Cohort size is considered. The purpose of current study was the introduction of importance of Cohort size in word recognition and calculation of Cohort size for the list of Persian high-frequency spondee words.
Methods: The spondee words extracted from high-frequency Persian word store. Then, total spondee words with same first syllable in Amid Persian dictionary recorded and Cohort size calculated for each spondee word. Thus, the list of high-frequency spondee words with their Cohort size composed of 4121 words obtained.
Results: The Cohort sizes of word had a wide range from 0 to 87. In the half of the words, the Cohort sizes were less than 14 and in the rest were more than it.
Conclusion: The Cohort size affects the time course and precision of decision making about words. Persian words are not equal in Cohort size. For having more controlled test materials to develop and design different types of auditory tests, it is possible to consider the Cohort size of words along other effective factors.
2. Dumay N, Content A. Searching for syllabic coding units in speech perception. J Mem Lang. 2012;66(4):680-94.
3. Lecumberri MLG, Cooke M, Cutler A. Non-native speech perception in adverse conditions: A review. Speech Commun. 2010;52(11-12):864-86.
4. Calabrese A. Auditory representations and phonological illusions: a linguist’s perspective on the neuropsychological bases of speech perception. J Neurolinguistics. 2012;25(5):355-81.
5. Harley TA. The psychology of language: from data to theory. 3rd ed. New York: Psychology Press; 2008.
6. Theunissen M, Swanepoel de W, Hanekom J. Sentence recognition in noise: variables in compilation and interpretation of tests. Int J Audiol. 2009;48(11):743-57.
7. Thibodeau LM. Speech audiometry. In: Roeser RJ, Valente M, Hosford-Dunn H, editors. Audiology Diagnosis. 2nd ed. New Yourk: Theime Medical Publishers, Inc; 2007.p. 288-311.
8. McArdle R, Hnath-Chisolm T. Speech audiometry. In: Katz J, Medwetsky L, Burkard R, Hood L, editors. Handbook of clinical audiology. 6th ed. Baltimore: Lippincot Williams & Wilkins; 2009.p.64-79.
9. Assi SM. “Farsi Linguistic Database (FLDB)”. International Journal of Lexicography. 1997;10(3):5.
10. Conway CM, Bauernschmidt A, Huang SS, Pisoni DB. Implicit statistical learning in language processing: word predictability is the key. Cognition. 2010;114(3):356-71.
11. Gahl S, Yao Y, Johnson K. Why reduce? Phonological neighborhood density and phonetic reduction in spontaneous speech. J Mem Lang. 2012;66(4):789-806
12. Kim D, Stephens JD, Pitt MA. How does context play a part in splitting words apart? Production and perception of word boundaries in casual speech. J Mem Lang. 2012;66(4):509-29.
13. Astheimer LB, Sanders LD. Predictability affects early perceptual processing of word onsets in continuous speech. Neuropsychologia. 2011;49(12):3512-6.
Issue | Vol 23 No 3 (2014) | |
Section | Research Article(s) | |
Keywords | ||
Speech perception word recognition Cohort model of word recognition Cohort size Persian language |
Rights and permissions | |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |