Fluctuation contrast and speech-on-speech masking: Model midbrain responses to simultaneous speech

  • Laurel H. Carney Departments of Biomedical Engineering, Neuroscience, and Electrical & Computer Engineering, Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA; Hearing Systems, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark

Abstract

At the level of the auditory midbrain, low-frequency fluctuations within each frequency channel drive neurons with band-pass modulation transfer functions (MTFs). The amplitude of low-frequency fluctuations in ascending neural signals is affected by stimulus amplitude due to the gradual saturation of the inner hair cells (IHCs) beginning at moderate sound levels. This level dependence of low-frequency fluctuation amplitudes results in contrast cues at the level of the midbrain: Spectral peaks result in lower responses of cells with bandpass-MTFs, whereas spectral valleys result in higher responses. Here, we focus on model population midbrain responses with different best-modulation frequencies (BMFs) to simultaneous speech. Midbrain responses were simulated for single hearing-in-noise (HINT) sentences and for a pair of simultaneous sentences, spoken by a male and a female. Correlations between population responses to individual male (or female) sentences and responses to simultaneous sentences vary with BMF in the range of the male (or female) fundamental frequencies. The pattern of fluctuation contrast across frequency in the midbrain representation provides a framework for studying speech-on-speech masking for listeners with normal hearing and sensorineural hearing loss.

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Published
2018-01-02
How to Cite
CARNEY, Laurel H.. Fluctuation contrast and speech-on-speech masking: Model midbrain responses to simultaneous speech. Proceedings of the International Symposium on Auditory and Audiological Research, [S.l.], v. 6, p. 75-82, jan. 2018. ISSN 2596-5522. Available at: <https://proceedings.isaar.eu/index.php/isaarproc/article/view/2017-10>. Date accessed: 22 apr. 2018.
Section
2017/2. Neural mechanisms, modeling, and physiological correlates of adaptation