Download PDF
J Am Acad Audiol 2001; 12(09): 437-444
DOI: 10.1055/s-0042-1745631
Original Article

Interactive Effects of Low–Pass Filtering and Masking Noise on Word Recognition

Teri Scott
School of Human Communication Disorders, Dalhousie University. Halifax, Nova Scotia
,
Walter B. Green
School of Human Communication Disorders, Dalhousie University. Halifax, Nova Scotia
,
Andrew Stuart
Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
› Author Affiliations
› Further Information
  PDF Download  Permissions and Reprints

Abstract

A word recognition in noise paradigm was employed to examine temporal resolution in individuals with simulated hearing loss. Word recognition scores were obtained for low-pass filtered speech (i.e., cutoff frequencies of 1000, 1250, and 1500 Hz) presented in continuous and interrupted noise at signal-to-noise ratios (SNRs) of–10, 0, and 10 dB. Performance improved with increasing SNR and low–pass frequency filter settings. Generally, word recognition performance was better in the interrupted noise condition than the continuous noise condition. This effect was greatest in the -10 dB SNR condition. Since the continuous/interrupted performance difference steadily declined as a function of low-pass filter cutoff frequency, these findings suggest that one factor leading to poorer speech recognition in individuals with high–frequency hearing impairment may be their dependence on low-frequency hearing channels that are inherently poorer than high-frequency channels for temporal resolution.

Abbreviations: ANOVA = analysis of variance, MS = multiple sclerosis, NU-6 = Northwestern University Auditory Test No. 6, SNR = signal-to-noise ratio

Keywords

Hearing loss - temporal resolution - word recognition


Publication History

Article published online:
07 March 2022

© 2001. American Academy of Audiology. This article is published by Thieme.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • REFERENCES

  • American National Standards Institute. (1996). Specifications for Audiometers. (ANSI S3.6–1996). New York: ANSI.
  • American National Standards Institute. (1999). Criteria for Permissible Ambient Noise During Audiometeric Testing. (ANSI S3.1–1999). New York: ANSI.
  • American Speech–Language–Hearing Association. (1990). Guidelines for screening for hearing impairments and middle ear disorders. ASHA 32(Suppl 2): 17–24.
  • Bacon SP, Opie JM, Montoya DY. (1994). Speech recognition thresholds in temporally complex backgrounds: effects of hearing loss and noise masking. J Acoust Soc Am 95:2993.
  • Bacon SP, Viemeister NF. (1985). Temporal modulation transfer functions in normal–hearing and hearing– impaired listeners. Audiology 24:117–134.
  • Bornstein SP, Wilson RH, Cambron NK. (1994). Low– and high–pass filtered Northwestern University Auditory Test No. 6 for monaural and binaural evaluation. J Am Acad Audiol 5:259–264.
  • Dubno JR, Dirks DD, Morgan DE. (1984). Effects of age and mild hearing loss on speech recognition in noise. J Acoust Soc Am 76:87—96.
  • Festen JM, Plomp R. (1990). Effects of fluctuating noise and interfering speech on the speech–reception threshold for impaired and normal hearing. J Acoust Soc Am 88:1725–1736.
  • Florentine M, Buus S. (1984). Temporal gap detection in sensorineural and simulated hearing impairments. J Speech Hear Res 27:449–455.
  • French NR, Steinberg JC. (1947). Factors governing the intelligibility of speech sounds. J Acoust Soc Am 19:90–119.
  • Givens GD, Jacobs–Condit L. (1981). Consonant identification in quiet and in noise with the normal and the sensorineural hearing–impaired. J Audit Res 21:279–285.
  • Glasberg BR, Moore BCJ, Patterson RD, Nimmo–Smith I. (1984). Dynamic range and asymmetry of the auditory filter. J Acoust Soc Am 76:419–427.
  • Gustafsson HA, Arlinger SD. (1994). Masking of speech by amplitude–modulated noise. J Acoust Soc Am 95:518–529.
  • Humes LE, Espinoza–Varas B, Watson CS. (1988). Modeling sensorineural hearing loss. I. Model and retrospective evaluation. J Acoust Soc Am 83:188–202.
  • Moore BCJ. (1989). An Introduction to the Psychology of Hearing. 3rd Ed. London: Academic Press.
  • Moore BCJ, Glasberg BR, Donaldson E, McPherson T, Plack CJ. (1989). Detection of temporal gaps in sinusoids by normally hearing and hearing–impaired subjects. J Acoust Soc Am 85:1266–1275.
  • Needleman AR, Crandell CC. (1995). Speech recognition in noise by hearing–impaired and noise–masked normalhearing listeners. J Am Acad Audiol 6:414–424.
  • Payton KL, Uchanski RM, Braida LD. (1994). Intelligibility of conversational and clear speech in noise and reverberation for listeners with normal and impaired hearing. J Acoust Soc Am 95:1581–1592.
  • Pekkarinen E, Salmivalli A, Suonpaa J. (1990). Effect of noise on word discrimination by subjects with impaired hearing, compared with those with normal hearing. Scand Audiol 19:31–36.
  • Phillips DP. (1987). Stimulus intensity and loudness recruitment: neural correlates. JAcoust Soc Am 82:1–12.
  • Phillips DP, Hall SE. (1986). Spike–rate intensity functions of cat cortical neurons studied with combined tone–noise stimuli. J Acoust Soc Am 80:170–187.
  • Phillips DP, Rappaport JM, Gulliver JM. (1994). Impaired word recognition in noise by patients with noise–induced cochlear hearing loss: contribution of a temporal resolution defect. Am J Otol 15:679–686.
  • Pollack I. (1948). Effects of high pass and low pass filtering on the intelligibility of speech in noise. J Acoust Soc Am 20:259–266.
  • Rappaport JM, Phillips DP, Gulliver JM. (1994). Disturbed speech intelligibility in noise despite a normal audiogram: a defect in temporal resolution? J Otolaryngol 22:447–453.
  • Rappaport JM, Gulliver JM, Phillips DP, Van Dorpe RA, Maxner CE, Bhan V. (1994). Auditory temporal resolution in multiple sclerosis. J Otolaryngol 23:307–324.
  • Shailer MJ, Moore BCJ. (1987). Gap detection and the auditory filter: phase effects using sinusoidal stimuli. J Acoust Soc Am 81:1110–1117.
  • Stuart A. (1995). Temporal Resolution ofCochlear–Output Channels in Normal and Hearing–Impaired Listeners. Unpublished doctoral dissertation, Dalhousie University, Halifax, Nova Scotia.
  • Stuart A, Carpenter M. (1999). Unilateral auditory temporal resolution deficit: a case study. J Communic Disord 32:317–325.
  • Stuart A, Phillips DP. (1996). Word recognition in continuous and interrupted broadband noise by young normal–hearing, older normal–hearing, and presbyacu– sic listeners. Ear Hear 17:478–489.
  • Stuart A, Phillips DP. (1997). Word recognition in continuous noise, interrupted noise, and in quiet by normal–hearing listeners at two sensation levels. Scand Audiol 26:112–116.
  • Stuart A, Phillips DP. (1998). Deficits in auditory temporal resolution revealed by a comparison of word recognition under interrupted and continuous noise masking. Semin Hear 19:333–344.
  • Stuart A, Phillips DP, Green WB. (1995). Word recognition performance in continuous and interrupted noise by normal–hearing and simulated hearing–impaired listeners. Am J Otol 16:658–663.
  • Studebaker G. (1985). A “rationalized” arcsine transform. J Speech Hear Res 28:455–462.
  • Tillman TW, Carhart R. (1966). An Expanded Test for Speech Discrimination Using CNC Monosyllabic Words: Northwestern University Auditory Test No. 6. Technical report SAM–TR–66–55. Brooks Air Force Base, TX: USAF School of Aerospace Medicine.
  • Turner CW, Souza PE, Forget LN. (1995). Use of temporal envelope cues in speech recognition by normal and hearing–impaired listeners. J Acoust Soc Am 97:2568–2576.
  • Wagenaar WA. (1969). Note on the construction of digram– balanced Latin squares. Psychol Bull 72:384–386.
  • Wilson RH, Zizz CA, Shanks JE, Causey GD. (1990). Normative data in quiet, broadband noise, and competing message for Northwestern University Auditory Test No. 6 by a female speaker. J Speech Hear Disord 55:771–778.