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CC BY 4.0 · Int Arch Otorhinolaryngol 2024; 28(03): e492-e501
DOI: 10.1055/s-0044-1785456
Original Research

Contribution of Temporal Fine Structure Cues to Concurrent Vowel Identification and Perception of Zebra Speech

Delora Samantha Serrao
1   National Hearing Care, Armadale, Australia
,
Nikhitha Theruvan
2   Department of Audiology, La Trobe University, Melbourne, Australia
,
Hasna Fathima
3   Department of Audiology and Speech-Language Pathology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
4   Department of Audiology and Speech Language Pathology, National Institute of Speech and Hearing, Trivandrum, Kerala, India
,
Arivudai Nambi Pitchaimuthu 
3   Department of Audiology and Speech-Language Pathology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
5   Department of Audiology, Centre for Hearing Science, All India Institute of Speech & Hearing, Mysuru, India
› Author Affiliations Funding The study has not received any funding.
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Abstract

Introduction The limited access to temporal fine structure (TFS) cues is a reason for reduced speech-in-noise recognition in cochlear implant (CI) users. The CI signal processing schemes like electroacoustic stimulation (EAS) and fine structure processing (FSP) encode TFS in the low frequency whereas theoretical strategies such as frequency amplitude modulation encoder (FAME) encode TFS in all the bands.

Objective The present study compared the effect of simulated CI signal processing schemes that either encode no TFS, TFS information in all bands, or TFS only in low-frequency bands on concurrent vowel identification (CVI) and Zebra speech perception (ZSP).

Methods Temporal fine structure information was systematically manipulated using a 30-band sine-wave (SV) vocoder. The TFS was either absent (SV) or presented in all the bands as frequency modulations simulating the FAME algorithm or only in bands below 525 Hz to simulate EAS. Concurrent vowel identification and ZSP were measured under each condition in 15 adults with normal hearing.

Results The CVI scores did not differ between the 3 schemes (F (2, 28) = 0.62, p = 0.55, η2 p = 0.04). The effect of encoding TFS was observed for ZSP (F (2, 28) = 5.73, p = 0.008, η2 p = 0.29). Perception of Zebra speech was significantly better with EAS and FAME than with SV. There was no significant difference in ZSP scores obtained with EAS and FAME (p = 1.00)

Conclusion For ZSP, the TFS cues from FAME and EAS resulted in equivalent improvements in performance compared to the SV scheme. The presence or absence of TFS did not affect the CVI scores.

Keywords

cochlear implant - speech perception - hearing loss - psychoacoustics - auditory processing - algorithm


Publication History

Received: 21 August 2022

Accepted: 16 January 2024

Article published online:
05 July 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit (https://creativecommons.org/licenses/by/4.0/)

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  • References

  • 1 Smith ZM, Delgutte B, Oxenham AJ. Chimaeric sounds reveal dichotomies in auditory perception. Nature 2002; 416 (6876) 87-90
    CrossrefPubMedSearch in Google Scholar
  • 2 Shannon RV, Zeng FG, Kamath V, Wygonski J, Ekelid M. Speech recognition with primarily temporal cues. Science 1995; 270 (5234) 303-304
    CrossrefPubMedSearch in Google Scholar
  • 3 Loizou PC, Dorman M, Tu Z. On the number of channels needed to understand speech. J Acoust Soc Am 1999; 106 (4 Pt 1): 2097-2103
    CrossrefPubMedSearch in Google Scholar
  • 4 Xu L, Zheng Y. Spectral and temporal cues for phoneme recognition in noise. J Acoust Soc Am 2007; 122 (03) 1758
    CrossrefPubMedSearch in Google Scholar
  • 5 Friesen LM, Shannon RV, Baskent D, Wang X. Speech recognition in noise as a function of the number of spectral channels: comparison of acoustic hearing and cochlear implants. J Acoust Soc Am 2001; 110 (02) 1150-1163
    CrossrefPubMedSearch in Google Scholar
  • 6 Loizou PC, Dorman MF, Tu Z, Fitzke J. Recognition of sentences in noise by normal-hearing listeners using simulations of speak-type cochlear implant signal processors. Ann Otol Rhinol Laryngol Suppl 2000; 185 (12) 67-68
    CrossrefPubMedSearch in Google Scholar
  • 7 Nelson PB, Jin S-H, Carney AE, Nelson DA. Understanding speech in modulated interference: cochlear implant users and normal-hearing listeners. J Acoust Soc Am 2003; 113 (02) 961-968
    CrossrefPubMedSearch in Google Scholar
  • 8 Moore BC. The roles of temporal envelope and fine structure information in auditory perception. Acoust Sci Technol 2019; 40 (02) 61-83
    CrossrefSearch in Google Scholar
  • 9 Nie K, Stickney G, Zeng FG. Encoding frequency modulation to improve cochlear implant performance in noise. IEEE Trans Biomed Eng 2005; 52 (01) 64-73
    CrossrefPubMedSearch in Google Scholar
  • 10 Stickney GS, Nie K, Zeng F-G. Contribution of frequency modulation to speech recognition in noise. J Acoust Soc Am 2005; 118 (04) 2412-2420
    CrossrefPubMedSearch in Google Scholar
  • 11 Gilbert G, Bergeras I, Voillery D, Lorenzi C. Effects of periodic interruptions on the intelligibility of speech based on temporal fine-structure or envelope cues. J Acoust Soc Am 2007; 122 (03) 1336
    CrossrefPubMedSearch in Google Scholar
  • 12 Hopkins K, Moore BCJ, Stone MA. Effects of moderate cochlear hearing loss on the ability to benefit from temporal fine structure information in speech. J Acoust Soc Am 2008; 123 (02) 1140-1153
    CrossrefPubMedSearch in Google Scholar
  • 13 Hopkins K, Moore BCJ. The contribution of temporal fine structure to the intelligibility of speech in steady and modulated noise. J Acoust Soc Am 2009; 125 (01) 442-446
    CrossrefPubMedSearch in Google Scholar
  • 14 Lorenzi C, Gilbert G, Carn H, Garnier S, Moore BCJ. Speech perception problems of the hearing impaired reflect inability to use temporal fine structure. Proc Natl Acad Sci U S A 2006; 103 (49) 18866-18869
    CrossrefPubMedSearch in Google Scholar
  • 15 Shen Y, Pearson DV. Efficiency in glimpsing vowel sequences in fluctuating makers: Effects of temporal fine structure and temporal regularity. J Acoust Soc Am 2019; 145 (04) 2518-2529
    CrossrefPubMedSearch in Google Scholar
  • 16 von Ilberg C, Kiefer J, Tillein J. et al. Electric-acoustic stimulation of the auditory system. New technology for severe hearing loss. ORL J Otorhinolaryngol Relat Spec 1999; 61 (06) 334-340
    CrossrefPubMedSearch in Google Scholar
  • 17 Vermeire K, Punte AK, Van de Heyning P. Better speech recognition in noise with the fine structure processing coding strategy. ORL J Otorhinolaryngol Relat Spec 2010; 72 (06) 305-311
    CrossrefPubMedSearch in Google Scholar
  • 18 Liepins R, Kaider A, Honeder C. et al. Formant frequency discrimination with a fine structure sound coding strategy for cochlear implants. Hear Res 2020; 392: 107970
    CrossrefPubMedSearch in Google Scholar
  • 19 Zhou H, Yu G, Meng Q. Enhancing the temporal fine structure with the temporal limits encoder for cochlear implants: Effects on pitch discrimination. J Acoust Soc Am 2020; 148 (04) 2711-2711
    CrossrefSearch in Google Scholar
  • 20 Hopkins K, Moore BCJ. The importance of temporal fine structure information in speech at different spectral regions for normal-hearing and hearing-impaired subjects. J Acoust Soc Am 2010; 127 (03) 1595-1608
    CrossrefPubMedSearch in Google Scholar
  • 21 Swaminathan J, Heinz MG. Psychophysiological analyses demonstrate the importance of neural envelope coding for speech perception in noise. J Neurosci 2012; 32 (05) 1747-1756
    CrossrefPubMedSearch in Google Scholar
  • 22 Apoux F, Youngdahl CL, Yoho SE, Healy EW. Dual-carrier vocoder: Evidence of a primary role of temporal fine structure in streaming. J Acoust Soc Am 2014; 135 (04) 2164-2164
    CrossrefSearch in Google Scholar
  • 23 Paredes-Gallardo A, Madsen SMK, Dau T, Marozeau J. The Role of Temporal Cues in Voluntary Stream Segregation for Cochlear Implant Users. Trends Hear 2018; 22: 2331216518773226
    CrossrefPubMedSearch in Google Scholar
  • 24 Qin MK, Oxenham AJ. Effects of simulated cochlear-implant processing on speech reception in fluctuating maskers. J Acoust Soc Am 2003; 114 (01) 446-454
    CrossrefPubMedSearch in Google Scholar
  • 25 Summers RJ, Bailey PJ, Roberts B. Effects of differences in fundamental frequency on across-formant grouping in speech perception. J Acoust Soc Am 2010; 128 (06) 3667-3677
    CrossrefPubMedSearch in Google Scholar
  • 26 Kumar AU, Rayanagoudar P, Nambi A. Concurrent Vowel Identification and Speech Perception in Noise in Individuals With Cochlear Hearing Loss. Acta Acust United Acust 2013; 99 (06) 952-959
    CrossrefSearch in Google Scholar
  • 27 Gaudrain E, Carlyon RP. Using Zebra-speech to study sequential and simultaneous speech segregation in a cochlear-implant simulation. J Acoust Soc Am 2013; 133 (01) 502-518
    CrossrefPubMedSearch in Google Scholar
  • 28 de Cheveigné A. Vowel-specific effects in concurrent vowel identification. J Acoust Soc Am 1999; 106 (01) 327-340
    CrossrefPubMedSearch in Google Scholar
  • 29 Meddis R, Hewitt MJ. Modeling the identification of concurrent vowels with different fundamental frequencies. J Acoust Soc Am 1992; 91 (01) 233-245
    CrossrefPubMedSearch in Google Scholar
  • 30 Devergie A, Grimault N, Tillmann B, Berthommier F. Effect of rhythmic attention on the segregation of interleaved melodies. J Acoust Soc Am 2010; 128 (01) EL1-EL7
    CrossrefPubMedSearch in Google Scholar
  • 31 Paredes-Gallardo A, Madsen SMK, Dau T, Marozeau J. The Role of Place Cues in Voluntary Stream Segregation for Cochlear Implant Users. Trends Hear 2018; 22: 2331216517750262
    CrossrefPubMedSearch in Google Scholar
  • 32 Carlson RV, Boyd KM, Webb DJ. The revision of the Declaration of Helsinki: past, present and future. Br J Clin Pharmacol 2004; 57 (06) 695-713
    CrossrefPubMedSearch in Google Scholar
  • 33 Methi R, Avinash, Kumar AU. Development of sentence material for quick speech in noise test (Quick SIN) in Kannada. J Indian Speech Hear Assoc. 2009; 23 (01) 59-65
    Search in Google Scholar
  • 34 Jin S-H, Liu C. English vowel identification in quiet and noise: effects of listeners' native language background. Front Neurosci 2014; 8: 305
    PubMedSearch in Google Scholar
  • 35 Sagi E, Svirsky MA. Information transfer analysis: a first look at estimation bias. J Acoust Soc Am 2008; 123 (05) 2848-2857
    CrossrefPubMedSearch in Google Scholar
  • 36 Wang MD, Bilger RC. Consonant confusions in noise: a study of perceptual features. J Acoust Soc Am 1973; 54 (05) 1248-1266
    CrossrefPubMedSearch in Google Scholar
  • 37 Sherbecoe RL, Studebaker GA. Supplementary formulas and tables for calculating and interconverting speech recognition scores in transformed arcsine units. Int J Audiol 2004; 43 (08) 442-448
    CrossrefPubMedSearch in Google Scholar
  • 38 Assmann PF, Paschall DD. Pitches of concurrent vowels. J Acoust Soc Am 1998; 103 (02) 1150-1160
    CrossrefPubMedSearch in Google Scholar
  • 39 Culling JF, Darwin CJ. Perceptual and computational separation of simultaneous vowels: cues arising from low-frequency beating. J Acoust Soc Am 1994; 95 (03) 1559-1569
    CrossrefPubMedSearch in Google Scholar
  • 40 Chintanpalli A, Ahlstrom JB, Dubno JR. Computational model predictions of cues for concurrent vowel identification. J Assoc Res Otolaryngol 2014; 15 (05) 823-837
    CrossrefPubMedSearch in Google Scholar
  • 41 Chintanpalli A, Heinz MG. The use of confusion patterns to evaluate the neural basis for concurrent vowel identification. J Acoust Soc Am 2013; 134 (04) 2988-3000
    CrossrefPubMedSearch in Google Scholar
  • 42 Fogerty D, Humes LE. A correlational method to concurrently measure envelope and temporal fine structure weights: effects of age, cochlear pathology, and spectral shaping. J Acoust Soc Am 2012; 132 (03) 1679-1689
    CrossrefPubMedSearch in Google Scholar
  • 43 Smith SS, Chintanpalli A, Heinz MG, Sumner CJ. Revisiting Models of Concurrent Vowel Identification: The Critical Case of No Pitch Differences. Acta Acust United Acust 2018; 104 (05) 922-925
    CrossrefPubMedSearch in Google Scholar
  • 44 Assmann PF, Summerfield Q. Modeling the perception of concurrent vowels: vowels with the same fundamental frequency. J Acoust Soc Am 1989; 85 (01) 327-338
    CrossrefPubMedSearch in Google Scholar
  • 45 Souza P, Rosen S. Effects of envelope bandwidth on the intelligibility of sine- and noise-vocoded speech. J Acoust Soc Am 2009; 126 (02) 792-805
    CrossrefPubMedSearch in Google Scholar
  • 46 Loizou PC, Dorman MF, Powell V. The recognition of vowels produced by men, women, boys, and girls by cochlear implant patients using a six-channel CIS processor. J Acoust Soc Am 1998; 103 (02) 1141-1149
    CrossrefPubMedSearch in Google Scholar
  • 47 Bregman AS. Auditory scene analysis: the perceptual organization of sound. A Bradford book. Cambridge, London:: MIT Press; 1990. :XIII, 773
    CrossrefSearch in Google Scholar
  • 48 Micheyl C, Oxenham AJ. Sequential F0 comparisons between resolved and unresolved harmonics: no evidence for translation noise between two pitch mechanisms. J Acoust Soc Am 2004; 116 (05) 3038-3050
    CrossrefPubMedSearch in Google Scholar
  • 49 Manjunath D, Serrao D, Theruvan N, Muthu P, Nambi A. Contribution of amplitude modulations for concurrent stream segregation: A probe through object-related negativity. Speech Lang Hear 2015; 18 (01) 55-61
    CrossrefSearch in Google Scholar
  • 50 Houtsma AJ, Smurzynski J. Pitch identification and discrimination for complex tones with many harmonics. J Acoust Soc Am 1990; 87 (01) 304-310
    CrossrefSearch in Google Scholar
  • 51 Fogerty D. Perceptual weighting of individual and concurrent cues for sentence intelligibility: frequency, envelope, and fine structure. J Acoust Soc Am 2011; 129 (02) 977-988
    CrossrefPubMedSearch in Google Scholar
  • 52 Hopkins K, Moore BCJ. Development of a fast method for measuring sensitivity to temporal fine structure information at low frequencies. Int J Audiol 2010; 49 (12) 940-946
    CrossrefPubMedSearch in Google Scholar