DEVELOPMENT OF SENTENCES FOR A TAMIL SPEECH-IN-NOISE TEST: LISTS FOR CHILDREN, YOUNGER ADULTS, AND OLDER ADULTS
Introduction The present study aimed to develop and standardize sentences for speech-in-noise tests in the Tamil language for children, younger adults, and older adults. Material and methods A set of 300 sentences in Tamil was taken from the <i>Production of Language Training Materials in Major Indian Languages</i> (Karanth et al., 2010) and recorded. These sentences were rated by five native Tamil-speaking speech-language pathologists based on naturalness, predictability, and identifiability. Sentences rated by at least 80% of the raters for high naturalness, low predictability, and high identifiability were selected, resulting in 147 sentences for further use. These sentences were mixed with speech-shaped noise at varying signal-to-noise ratios (SNRs), ranging from +5 to –10 dB in 2.5 dB steps. Speech perception in noise was assessed in 90 normal hearing participants (30 children, 30 younger adults, and 30 older adults). The SNR-50 values – representing the SNR at which 50% of the words were correctly identified – was evaluated. Results Perceptual SNR-50 values were calculated for each list, based on the perceptual score obtained by each participant (separately for children, younger adults, and older adults). Statistical analysis determined that some lists had significantly different perceptual scores and were excluded. Seven lists were finalized for each age group, with mean SNR-50 values of –4.76 dB for children, –4.66 dB for younger adults, and –4.65 dB for older adults. Tests confirmed reliability and validity. Conclusions The study found that speech identification scores decreased with poorer SNR levels, with significant differences in SNR-50 values across children, younger adults, and older adults. Separate, equivalent test lists were created for each age group. The test materials showed high test–retest reliability and internal validity, making it possible to distinguish between individuals with normal hearing and those with hearing loss.
Authors
- Arun Kumar
Publication Details
- Journal
- Journal of Hearing Science
- Published
- 2025-03-31
- DOI
- https://doi.org/10.17430/jhs/203028
- Primary Topic
- Speech and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00