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Introduction Due to the spectral variations of speech sounds, speech materials have become an indispensable tool in clinical evaluation. They could be used to determine the extent to which a person has disruption in the perception of complex signals like speech (Wilson & Margolis, 1983). Beattie, Edgerton and Svihovec (1977) compared the slopes of performance intensity function of NU No. 6 and CID W-22 speech materials and reported that the slope was 4.2% and 4.6% respectively. It suggests that the different test materials can also yield different performance-intensity functions. Speech contains both spectral and temporal information that is important for perception of speech. However, there are variations across languages in the way these spectral/temporal cues contribute in perception of speech. There are spectral variations like differences in formant frequencies and temporal variations like changes in speaking rate across languages. However, it might be complicated to study the influence of these information in speech identification scores by varying both the parameters. Hence, a systematic study is required to see the spectral or temporal influence on speech identification scores by keeping one parameter unaltered. Thus, by varying the spectral properties of speech (like use of filtered speech material) one can determine the contribution of different spectral energy in perception of speech in different languages. Spectrally modified speech stimuli like filtered speech have been used as a monaural low redundancy test to assess Auditory processing disorder (APD) (Bocca, Calearo & Cassinari, 1954). Filtered speech helps to understand the contribution of different frequencies in perception of speech (Bornstein, Wilson & Cambron, 1994). Bornstein et al. (1994) observed that individuals with normal hearing could obtain 70% correct scores with low-pass cut-off frequencies of 1500 Hz and high pass cut off frequency of 2100 Hz. These results suggest that frequencies between 1500 Hz and 2100 Hz are more important in perception of speech. The spectral information above 2100 Hz and below 1500 Hz though important but may not provide adequate information for the perception of speech. The effect of cut-off frequency mainly depends on the spectral energy of the speech sounds and it might change with the language used. Hence, the current study aimed to observe how different spectrally varied speech stimuli can affect the speech identification scores in Telugu speaking young adults with normal hearing. Method Thirty young adults (mean age 21.5 years) having normal hearing (hearing sensitivity less than or equal to 15 dB HL) participated in the study. Speech perception in Noise (SPIN) test was administered to rule out Auditory Processing Disorder (APD) and all the participants had speech identification scores greater than 60% at 0 dB SNR (Orchik & Burgess, 1977). In the present study, phonetically balanced word lists in Telugu were used for spectral modification to determine speech identification scores in young adults having normal hearing. Each list was filtered using low-pass cut-off frequencies of 800, 1200, 1500 and 1700 Hz; and high-pass cut-off frequencies of 1700, 2100, 2500 and 3000 Hz using adobe audition software and the attenuation rate of 115 dB/octave using Butterworth filters. The individuals were instructed to give a written response and the speech identification scores were determined for each cut-off frequency. Results The results of the study showed that there is an increase in speech identification scores with increase in low-pass cut-off frequency and with decrease in high-pass cut off frequency. The participants obtained greater than 70% scores for low-pass cut-off frequency of 1200 Hz or higher and high-pass cut off frequency of 2100 Hz or lower. The results of repeated measures ANOVA shows that there was significant difference in speech identification scores across low cut off frequencies [F (3, 177) = 395.83, p < 0.01] and high cut off frequencies [F (3,177) = 924.67, p < 0.01]. The results of the Bonferroni’s test revealed that the scores of all the cut-off frequencies for both low-pass and high-pass words differed significantly from each other at level of significance of p < 0.01. The discrepancy in the low-pass cut-off frequency for Telugu (1200 Hz) in comparison with English (1500 Hz) could be due to the predominance of low frequency information in Telugu language. Conclusions The present study made an attempt to find out the effect of spectral variations on perception of speech in telugu speaking young adults with normal hearing. The study showed that the spectral information between 1200 Hz and 2100 Hz are important for perception of speech in Telugu. It was also found that slightly lower low cut off frequency is important to perceive the speech in Telugu compared to English language.
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