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Effects of spectral smearing on the identification of speech in noise filtered into low- and mid-frequency regions.

Abstract

Léger et al. [J. Acoust. Soc. Am. 131, 1502-1514 (2012)] reported deficits in the identification of consonants in noise by hearing-impaired listeners using stimuli filtered into low- or mid-frequency regions in which audiometric thresholds were normal or near-normal. The deficits could not be fully explained in terms of reduced audibility or temporal-envelope processing. However, previous studies indicate that the listeners may have had reduced frequency selectivity, with auditory filters broadened by a factor of about 1.3, despite having normal or near-normal audiometric thresholds in the tested regions. The present study aimed to determine whether the speech-perception deficits could be explained by such a small reduction of frequency selectivity. Consonant identification was measured for normal-hearing listeners in quiet and in unmodulated and modulated noises using the same method as Léger et al. The signal-to-noise ratio was set to -3 dB for the masked conditions. Various amounts of reduced frequency selectivity were simulated using a spectral-smearing algorithm. Performance was reduced only for spectral-smearing factors greater than 1.7. For all conditions, identification scores for hearing-impaired listeners could not be explained by a mild reduction of frequency selectivity.

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  • Authors

    Léger AC, Moore BC, Gnansia D, Lorenzi C

    Institution

    Equipe Audition, Institut d'Etudes Cognitives, École Normale Supérieure, Paris Sciences et Lettres, 29 rue d'Ulm, 75005 Paris, France. agnes.leger@ens.fr

    Source

    The Journal of the Acoustical Society of America 131:5 2012 May pg 4114-23

    MeSH

    Algorithms
    Auditory Threshold
    Humans
    Noise
    Perceptual Distortion
    Perceptual Masking
    Phonetics
    Signal-To-Noise Ratio
    Sound Spectrography
    Speech Perception
    Young Adult

    Pub Type(s)

    Comparative Study
    Journal Article
    Research Support, Non-U.S. Gov't

    Language

    eng

    PubMed ID

    22559383