Refining a model of hearing impairment using speech psychophysics

Jepsen, Morten Løve; Dau, Torsten; Ghitza, Oded

doi:10.1121/1.4869256

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…An important extension of the model would be to include aspects of hearing impairment, such as elevated audiometric thresholds, reduced frequency selectivity, loss of compression and other supra-threshold deficits (cf. J€ urgens et al, 2014;Jepsen et al, 2014). The results of the present study suggest that, if a version of the model that can account for consonant perception in unaided HI listeners was established, the effects of hearing-instrument compensation strategies might be well-represented in the model predictions.…”

Section: Perspectivessupporting

confidence: 54%

“…If such a model can account for the effects of specific HA/CI processing strategies on consonant perception, it may provide useful information about the auditory cues that contribute to the recognition of a specific consonant or its confusion with another consonant. Several approaches for modeling consonant perception in NH listeners (Cooke, 2006;J€ urgens and Brand, 2009) and in HI listeners (Holube and Kollmeier, 1996;J€ urgens et al, 2014;Jepsen et al, 2014) have been proposed. While the mentioned models were shown to account for consonant recognition scores in masking noise (or in quiet at low signal levels), they did not account well for the consonant confusions, i.e., the predicted errors were different from the listeners' errors.…”

Section: Introductionmentioning

confidence: 99%

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Predicting effects of hearing-instrument signal processing on consonant perception

Zaar

Schmitt²,

Derleth³

et al. 2017

The Journal of the Acoustical Society of America

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This study investigated the influence of hearing-aid (HA) and cochlear-implant (CI) processing on consonant perception in normal-hearing (NH) listeners. Measured data were compared to predictions obtained with a speech perception model [Zaar and Dau (2017). J. Acoust. Soc. Am. 141, 1051-1064] that combines an auditory processing front end with a correlation-based template-matching back end. In terms of HA processing, effects of strong nonlinear frequency compression and impulse-noise suppression were measured in 10 NH listeners using consonant-vowel stimuli. Regarding CI processing, the consonant perception data from DiNino et al. [(2016). J. Acoust. Soc. Am. 140, 4404-4418] were considered, which were obtained with noise-vocoded vowel-consonant-vowel stimuli in 12 NH listeners. The inputs to the model were the same stimuli as were used in the corresponding experiments. The model predictions obtained for the two data sets showed a large agreement with the perceptual data both in terms of consonant recognition and confusions, demonstrating the model's sensitivity to supra-threshold effects of hearing-instrument signal processing on consonant perception. The results could be useful for the evaluation of hearing-instrument processing strategies, particularly when combined with simulations of individual hearing impairment.

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Section: Perspectivessupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Predicting effects of hearing-instrument signal processing on consonant perception

Zaar

Schmitt²,

Derleth³

et al. 2017

The Journal of the Acoustical Society of America

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, in most of these proposals, the applied auditory model is not sufficiently detailed to provide adequate options for implementing realistic hearing deficits. In the last decades, auditory models have been developed which are more sophisticated and meanwhile can simulate hearing deficits [12][13][14][15]. In [16,17], it is shown that…”

Section: Introductionmentioning

confidence: 99%

A computational study of auditory models in music recognition tasks for normal-hearing and hearing-impaired listeners

Friedrichs

Bauer

Martin

et al. 2017

J AUDIO SPEECH MUSIC PROC.

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The benefit of auditory models for solving three music recognition tasks-onset detection, pitch estimation, and instrument recognition-is analyzed. Appropriate features are introduced which enable the use of supervised classification. The auditory model-based approaches are tested in a comprehensive study and compared to state-of-the-art methods, which usually do not employ an auditory model. For this study, music data is selected according to an experimental design, which enables statements about performance differences with respect to specific music characteristics. The results confirm that the performance of music classification using the auditory model is comparable to the traditional methods. Furthermore, the auditory model is modified to exemplify the decrease of recognition rates in the presence of hearing deficits. The resulting system is a basis for estimating the intelligibility of music which in the future might be used for the automatic assessment of hearing instruments.

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Predicting consonant recognition and confusions in normal-hearing listeners

Zaar

Dau

2017

The Journal of the Acoustical Society of America

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The perception of consonants in background noise has been investigated in various studies and was shown to critically depend on fine details in the stimuli. In this study, a microscopic speech perception model is proposed that represents an extension of the auditory signal processing model by Dau, Kollmeier, and Kohlrausch [(1997). J. Acoust. Soc. Am. 102, 2892-2905]. The model was evaluated based on the extensive consonant perception data set provided by Zaar and Dau [(2015). J. Acoust. Soc. Am. 138, 1253-1267], which was obtained with normal-hearing listeners using 15 consonant-vowel combinations mixed with white noise. Accurate predictions of the consonant recognition scores were obtained across a large range of signal-to-noise ratios. Furthermore, the model yielded convincing predictions of the consonant confusion scores, such that the predicted errors were clustered in perceptually plausible confusion groups. The large predictive power of the proposed model suggests that adaptive processes in the auditory preprocessing in combination with a cross-correlation based template-matching back end can account for some of the processes underlying consonant perception in normal-hearing listeners. The proposed model may provide a valuable framework, e.g., for investigating the effects of hearing impairment and hearing-aid signal processing on phoneme recognition.

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Refining a model of hearing impairment using speech psychophysics

Cited by 3 publications

References 18 publications

Predicting effects of hearing-instrument signal processing on consonant perception

Predicting effects of hearing-instrument signal processing on consonant perception

A computational study of auditory models in music recognition tasks for normal-hearing and hearing-impaired listeners

Predicting consonant recognition and confusions in normal-hearing listeners

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