Conventional speech identification test in Marathi for adults
DOI:
https://doi.org/10.18203/issn.2454-5929.ijohns20163467Keywords:
Speech identification performance, Phonemic balance, Equivalence analysis, Performance-intensity function testing, Reliability, ValidityAbstract
Background: The present study aimed to develop conventional speech identification in Marathi for assessing adults by considering word frequency, familiarity, words in common use and phonemic balancing.
Methods: A total of four word lists were developed with each word list consisting of 25 words out of which 60% are monosyllabic words in CVC structure, and 40% are disyllabic words in CVCV structure. Equivalence analysis and performance-intensity function testing was carried out using four word lists on native speakers of Marathi belonging to different regions of Maharashtra (i.e. Vidarbha, Marathwada, Khandesh and Northern Maharashtra, Konkan and Pune) who were equally divided into five groups based on above mentioned regions.
Results: The results revealed that there was no statistically significant difference (p >0.05) in the speech identification performance between groups for each word list, and between word lists for each group. The performance-intensity (PI) function curve showed semi-linear function, and the groups’ mean slope of the curve indicated an average slope of 4.5% increase in speech identification score per dB for four word lists. Although, there is no data available on speech identification tests for adults in Marathi, most of the findings of the study are in line with the findings of research reports on other Indian languages.
Conclusions: The four word lists developed were found to be equally difficult for all the groups and can be used interchangeably. Thus, the developed word lists were found to be reliable and valid materials for assessing speech identification performance of adults in Marathi.
References
Mendel LL. Considerations in Pediatric Audiology. International Journal of Audiology. 2008;47:546-53.
Gelfand SA. Essentials of Audiology, 2nd Ed, New York: Thieme Medical Publishers; 2007.
De NS. Hindi PB List for Speech Audiometry and Discrimination Test. Indian Journal of Otolaryngology. 1973;25:64-75.
Dayalan S. Development and Standardization of Phonetically Balanced Test Materials in Tamil Language. Unpublished Master’s Dissertation, Mysore: University of Mysore; 1976.
Mallikarjuna. Phonetically balanced words in Gujarati: In Kacker, S.K. and Basavaraj, V. Indian Speech, Language and Hearing Test: The ISHA Battery, Mysore: ISHA; 1984.
Yathiraj A, Vijayalakshmi CS. Phonemically Balanced Word List in Kannada: Developed in Department of Audiology. Mysore: AIISH; 2005.
Mangaiahi L. Development and Standardization of Spondee and Phonetically Balanced (PB) Word List in Mizo Language. Unpublished Master’s Dissertation, Mysore: University of Mysore; 2009.
Kholia L. Development and Standardization of Speech Material in Rajasthani Language. Unpublished Master’s Dissertation, Mysore: University of Mysore; 2010.
Kumar SBR, Mohanty P. Speech Recognition Performance by Adults: A Proposal for a Battery for Telugu. Theory and Practice in Language Studies. 2012;2(2):193-204.
Waghmare P, Mohite J, Gore G. Development of Marathi Speech Recognition Test (Pediatric): A Preliminary Report. Journal of Indian Speech and Hearing Association. 2011;25(1):59-64.
Hirsh IJ, Davis H, Silverman SR, Reynolds EG, Eldert E, Benson RW. Development of materials for speech audiometry. Journal Speech and Hearing Research. 1952;17:321-37.
Martin FN, Champlin CA, Perez DD. The Question of Phonetic Balance in Word Recognition Testing. Journal of American Academy of Audiology. 2000;11:489-93.
Luce PA, Pisoni DB. Recognizing Spoken Words: The Neighborhood Activation Model. Ear and Hearing. 1998;19:1-36.
Lehiste I, Peterson GE. Linguistic Considerations in the Study of Speech Intelligibility. Journal of Acoustic Society of America. 1959;31:280-7.
Thorndike DL, Lorge I. The Teachers Word Book of 30,000 Words. New York: Colombia University Press; 1944.
Lehiste I, Peterson GE. Revised CNC Lists for Auditory Tests. Journal of Speech and Hearing Disorders. 1962;27:62-70.
Causey GD, Hood LJ, Hermanson CL, Bowling LS. The Maryland CNC Test: Normative Studies. Audiology. 1984;23:552-68.
Nissen SL, Harris RW, Jennings L, Eggett DL, Buck H. Psychometrically Equivalent Mandarin Disyllabic Speech Discrimination Materials Spoken by Male and Female Talkers. International Journal of Audiology. 2005;44:379-90.
Stevens KN. Toward a Model for Lexical Access Based on Acoustic Landmarks. Journal of Acoustic Society of America. 2002;111(4):1872-91.
Kumar SBR, Mohanty P. Speech Recognition Performance by Children: A Battery for Telugu. Journal of the Linguistic Society of India. 2012;73:101-15.
Turrini M, Cutugno F, Maturi P, Prosser S, Leoni FA, Arslan E. Bisyllabic Words for Speech Audiometry: A New Italian Material. Acta Otorhinolaryngologica Italica. 1993;13:63–77.
Pagliuca G, Monaghan P. Discovering Large Grain-Sizes in a Transparent Orthography: Insights from a Connectionist Model of Reading for Italian. Journal of Cognitive Psychology. 2010;22(5):813-25.
Mendel LL, Danhauer JL. Audiologic Evaluation and Management and Speech Perception Assessment. San Diego: Singular Publishing Company; 1997
Wang S, Mannell R, Newall P, Zhang H, Han D. Development and Evaluation of Mandarin Disyllabic Materials for Speech Audiometry in China. International Journal of Audiology. 2007;46(12):719-31.
Gold S, Lubinsky R, Shahar A. Speech Discrimination Scores at Low Sensation Levels as Possible Index of Malingering. Journal of Audiological Research. 1981;21:137-41.
Silman S, Silverman CA. Auditory Diagnosis, New York: Academic Press; 1991.
Devi ET. Development and Standardization of Speech Test Material in Manipuri Language. Unpublished Master’s Dissertation, Mysore: University of Mysore; 1985.