Konuşma Materyallerindeki Ünlülerin Frekans İçerikleri Açısından Anlaşılırlığa Etkilerinin Karşılaştırılması

Abstract

Amaç: Bu çalışmada ünlülerinin frekans içerikleri açısından Türkçe tek heceli konuşma materyallerinin anlaşılırlıklarına etkilerinin karşılaştırılması amaçlandı. Gereç ve Yöntem: Ünsüz-ünlü-ünsüz biçimindeki tek heceli anlamlı konuşma materyallerinin yüksek frekans enerjileri farklı düzeylerde süzülerek filtrelenmiş türevleri oluşturuldu. Bu materyaller ve türevleri normal işiten genç yetişkinlere dinletilerek her birinin anlaşılırlık oranı belirlendi. Farklı filtre düzeylerinden elde edilen anlaşılırlık oranları kullanılarak materyallerin spektrumlarındaki yüksek frekanslı bölgelerin anlaşılırlık açısından önem değerleri hesaplandı. Tüm materyaller içerdikleri ünlülere göre gruplandırılarak grupların yüksek frekans önem değerleri istatistiksel olarak birbirleriyle karşılaştırıldı. Bulgular: Tek yönlü varyans analizine göre ünlüler arasında yüksek frekans önem puanları açısından istatistiksel olarak anlamlı fark vardı. Grupların yüksek frekans önem puanlarına dayalı yapılan ikili karşılaştırmalarda /a/, /o/ ve /u/ grupları arasında anlamlı bir fark bulunmazken her birinin /e/, /i/ ve /ı/ gruplarından farklılaştığı, /e/, /i/ ve /ı/ grupları arasında anlamlı bir fark olmadığı ortaya çıktı. Diğer taraftan /ü/ ve /ö/ gruplarının yüksek frekans önem puanlarının hiçbir gruptan anlamlı olarak farklılaşmadığı görüldü. Sonuç: Bu çalışmanın sonucuna göre /a/, /o/ ve /u/ ünlülerinin alçak frekanslılar, /ü/ ve /ö/ ünlülerinin orta frekanslılar ve /ı/, /i/ ve /e/ ünlülerinin yüksek frekanslılar olarak kategorize edilmesi önerilebilir. Bu kategorizasyon özellikle konuşma listelerinin kısaltılmış versiyonlarında listeler arasında daha geçerli bir fonemik dengeleme yapabilmek için kullanılabilir.

Keywords

• Konuşma odyometrisi
• fonemik dengeleme
• tek heceli konuşma testleri
• konuşma materyalleri

Comparison of the Effects of Vowels in Speech Materials on Intelligibility in Terms of Their Frequency Components

Abstract

Objectives: In this study, it was aimed to compare the effects of vowels on the intelligibility of Turkish monosyllabic speech materials in terms of their frequency content. Materials and Methods: The high-frequency energies of the speech materials comprised of monosyllable meaningful words in consonant-vowel-consonant format were filtered so that their filtered derivatives were generated. These materials and their derivatives were presented to normal-hearing young adults, and the intelligibility rates of each material were determined. The significance values of the high-frequency regions in the spectra of the materials in terms of intelligibility were calculated using their intelligibility rates obtained from different filter levels. All materials were grouped according to their vowel content, and the high-frequency significance values of the groups were compared statistically. Results: According to a one-way analysis of variance, there was a statistically significant difference between the vowel groups in terms of high-frequency significance scores. In the pairwise comparisons based on high-frequency significance values of the groups, there was no significant difference between the /ɑ/, /Ɔ/ and /u/ groups, but each differed from the /ɛ/, /i/ and /ɯ/ groups. On the other hand, the high-frequency significance values of the /y/ and /œ/ groups did not differ significantly from any group (vowels are transcribed with the International Phonetic Alphabet). Conclusion: According to the results of this study, it can be suggested to categorize /a/, /o/ and /u/ vowels as low-frequency, /y/ and /ɯ/ vowels as mid-frequency and /ɯ/, /i/ and /e/ as high-frequency vowels. This categorization may be used to make a more proper phonemic balance between lists, particularly in shortened versions of speech lists.

Keywords

• Speech audiometry
• phonemic balance
• monosyllabic speech tests
• speech materials

References

1. Bornstein, S. P., Wilson, R. H., & Cambron, N. K. (1994). Low-and high-pass filtered Northwestern University Auditory Test No. 6 for monaural and binaural evaluation. Journal of the American Academy of Audiology, 5(4), 259-264. PMID: 7949299.
2. Byrne, D., Dillon, H., Tran, K., Arlinger, S., Wilbraham, K., Cox, R., ve diğerleri. (1994). An international comparison of long‐term average speech spectra. The journal of the acoustical society of America, 96(4), 2108-2120. https://doi.org/10.1121/1.410152
3. Durankaya, S. M., Şerbetçioğlu, B., Dalkılıç, G., Gürkan, S., & Kırkım, G. (2014). Development of a Turkish monosyllabic word recognition test for adults. Journal of International Advanced Otology, 10(2). https://doi.org/10.5152/iao.2014.118
4. Fabry, D. A., & Van Tasell, D. J. (1986). Masked and filtered simulation of hearing loss: effects on consonant recognition. Journal of Speech, Language, and Hearing Research, 29(2), 170-178. https://doi.org/10.1044/jshr.2902.170
5. Farrer, S. M., & Keith, R. W. (1981). Filtered word testing in the assessment of children's central auditory abilities. Ear and Hearing, 2(6), 267-269. https://doi.org/10.1097/00003446-198111000-00005
6. Fox, R. L. (1989). Dynamic information in the identification and discrimination of vowels. Phonetica, 46(1–3), 97–116. https://doi.org/10.1159/000261831
7. French, N. R., & Steinberg, J. C. (1947). Factors governing the intelligibility of speech sounds. Journal of the Acoustical Society of America, 19(1). https://doi.org/10.1121/1.1916407
8. Gottfried, T. L., Jenkins, J. J., & Strange, W. (1985). Categorial discrimination of vowels produced in syllable context and in isolation. Bulletin of the Psychonomic Society, 23(2), 101-104. https://doi.org/10.3758/BF03329794

9. Harris, R. W., & Swenson, D. W. (1990). Effects of reverberation and noise on speech recognition by adults with various amounts of sensorineural hearing impairment. International Journal of Audiology, 29(6), 314–321. https://doi.org/10.3109/00206099009072862
10. Hopkins, K., & Moore, B. C. (2010). The importance of temporal fine structure information in speech at different spectral regions for normal-hearing and hearing-impaired subjects. The Journal of the Acoustical Society of America, 127(3), 1595-1608. https://doi.org/10.1121/1.3293003
11. Hudgins, C. V., Hawkins, J. E., Kaklin, J. E., & Stevens, S. S. (1947). The development of recorded auditory tests for measuring hearing loss for speech. The Laryngoscope, 57(1), 57-89. https://doi.org/10.1288/00005537-194701000-00005
12. Jerger, J. (2008). Factors affecting word recognition. Journal of the American Academy of Audiology, 19(06), 460-460. https://doi.org/10.3766/jaaa.19.6.1
13. Jerger, J., Jerger, S., & Pirozzolo, F. (1991). Correlational analysis of speech audiometric scores, hearing loss, age, and cognitive abilities in the elderly. Ear and Hearing, 12(2), 103-109. doi: 10.1097/00003446-199104000-00004
14. Kilic ̧ MA. Türkiye Türkçesi’ndeki ünlülerin ses bilgisel özellikleri. In: Özsoy AS, Taylan EE, Aksu-Koc ̧ A, Akar D,Nakipoğlu M, eds. Studies in Turkish Linguistics. Istanbul: Boğazici University Press; 2003:3–18. Journal of speech and hearing research, 12(2), 281-287. https://doi.org/10.1044/jshr.1202.281
15. McArdle, R. C. T. H. (2009). Speech audiometry. In J. Katz (Ed.), Handbook of Clinical Audiology (pp.64–80). Lippincott Williams & Wilkins.
16. Rosen, S., Howell, P., & Bartram, J. F. (1993). Signals and Systems for Speech and Hearing. The Journal of the Acoustical Society of America, 94(6). https://doi.org/10.1121/1.407176
17. Vanpoucke, F., de Sloovere, M., & Plasmans, A. (2022). The Thomas More lists: A phonemically balanced dutch monosyllabic speech audiometry Test. Audiology Research, 12(4), 404–413. https://doi.org/10.3390/AUDIOLRES12040041/S1.
18. Walden, B. E., Schwartz, D. M., Montgomery, A. A., & Prosek, R. A. (1981). A comparison of the effects of hearing impairment and acoustic filtering on consonant recognition. Journal of speech and hearing research, 24(1), 32–43. https://doi.org/10.1044/jshr.2401.32
19. Wilber, L. A. (2007). Standards News: Audiologists and ANSI Standards. Acoustics Today, 3(4). https://doi.org/10.1121/1.2961160
20. Working Group on Speech Understanding and Aging. (1988). Speech understanding and aging. The Journal of the Acoustical Society of America, 83(3), 859–895. https://doi.org/10.1121/1.395965364
21. Yüksel, M., & Gündüz, B. (2018). Long term average speech spectra of Turkish. Logopedics Phoniatrics Vocology, 43(3). https://doi.org/10.1080/14015439.2017.1377286