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ORIGINAL ARTICLE
Year : 2021  |  Volume : 35  |  Issue : 2  |  Page : 27-32

Spoken word frequency in the hindi language: A preliminary database for psycholinguistic studies


1 Department of Otolaryngology, Post Graduate Institute of Medical Education and Research, Chandigarh, India
2 Department of Speech-Language Pathology, Ali Yavar Jung National Institute of Speech and Hearing Disability, Secunderabad, Telangana, India

Correspondence Address:
Himanshu Verma
Department of Otolaryngology, Post Graduate Institute of Medical Education and Research, Chandigarh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jisha.JISHA_24_20

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Objective: Limited studies related to spoken word corpus in the Indian context are available in the literature. To fulfill the demands of the spoken word frequency database in Hindi for advance psycholinguistic and cognitive studies, we tried to establish the preliminary spoken word database of Hindi language for children studying in Grade VI to Grade IX. Methods: To create the spoken word corpus a recorder was given to subjects to record their conversation. The recorded sample was transcribed into Hindi text using voice note II software. The transcribed sample was uploaded into Text Analyzer software, and word frequency, the number of syllables, and lexical density were computed. Results: Spoken word corpus consists of a total of 49,476 words. Lexical density was higher for females than males because the female database contains more unique words. The study also revealed that subjects used functional words and verbs more frequently, followed by nouns. Conclusion: We can conclude that the current database provides information about the high-frequency and low-frequency words used by children studying in Grade VI to Grade IX. This database will be helpful in psycholinguistic and cognitive experiments; however, the present corpus included data from the middle socioeconomic group and contained fewer words. The present study is the preliminary study future study demands and requires an extensive word database.


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