Modeling within- and across-channel processes in comodulation masking release

Dau, Torsten; Piechowiak, Tobias; Ewert, Stephan D.

doi:10.1121/1.4768882

Cited by 17 publications

(15 citation statements)

References 58 publications

(159 reference statements)

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“…This approach may also be applicable to conditions of across-frequency processing in comodulation masking release (CMR) where comodulated "off-frequency" flanking noise bands can improve signal detection of a pure tone embedded in an "on-frequency" masking noise band (e.g. ; Schooneveldt and Moore, 1987;Hall et al, 1990;Fantini et al, 1993;Piechowiak et al, 2007;Dau et al, 2013). In the model framework presented here, comodulated peripheral filters would be grouped together, and the addition of a pure-tone signal to the on-frequency masker noise band would make that peripheral filter "pop out" and form its own stream, which suggests that temporal coherence may be able to account for the across-frequency processing in CMR.…”

Section: E Perspectivesmentioning

confidence: 98%

Effects of tonotopicity, adaptation, modulation tuning, and temporal coherence in “primitive” auditory stream segregation

Christiansen

Jepsen

Dau

2014

The Journal of the Acoustical Society of America

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The perceptual organization of two-tone sequences into auditory streams was investigated using a modeling framework consisting of an auditory pre-processing front end [Dau et al., J. Acoust. Soc. Am. 102, 2892-2905 (1997)] combined with a temporal coherence-analysis back end [Elhilali et al., Neuron 61, 317-329 (2009)]. Two experimental paradigms were considered: (i) Stream segregation as a function of tone repetition time (TRT) and frequency separation (Δf) and (ii) grouping of distant spectral components based on onset/offset synchrony. The simulated and experimental results of the present study supported the hypothesis that forward masking enhances the ability to perceptually segregate spectrally close tone sequences. Furthermore, the modeling suggested that effects of neural adaptation and processing though modulation-frequency selective filters may enhance the sensitivity to onset asynchrony of spectral components, facilitating the listeners' ability to segregate temporally overlapping sounds into separate auditory objects. Overall, the modeling framework may be useful to study the contributions of bottom-up auditory features on "primitive" grouping, also in more complex acoustic scenarios than those considered here.

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Section: E Perspectivesmentioning

confidence: 98%

Effects of tonotopicity, adaptation, modulation tuning, and temporal coherence in “primitive” auditory stream segregation

Christiansen

Jepsen

Dau

2014

The Journal of the Acoustical Society of America

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“…Viemeister, 1979;Dau et al, 1997;Ewert & Dau, 2000) and the most recent attempts successfully described a wide range of behavioural data (e.g. Piechowiak et al, 2007;Jepsen et al, 2008;Dau et al, 2013;Biberger & Ewert, 2016. In comparison, very few modelling attempts have been made to model for FM sensitivity (Hartmann & Klein, 1980;Moore & Sek, 1992;Ernst & Moore, 2010;Paraouty et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A two‐path model of auditory modulation detection using temporal fine structure and envelope cues

Ewert

Paraouty

Lorenzi

2018

Eur J of Neuroscience

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A model using temporal-envelope cues was previously developed to explain perceptual interference effects between amplitude modulation and frequency modulation (FM). As that model could not accurately predict FM sensitivity and the interference effects, temporal fine structure (TFS) cues were added to the model. Thus, following the initial stage of the model consisting of a linear filter bank simulating cochlear filtering, processing was split into an 'envelope path' based on envelope power cues and a 'TFS path' based on a measure of the distribution of time intervals between successive zero-crossings. This yielded independent detectability indices for envelope and TFS cues, which were optimally combined to produce a single decision statistic. Independent internal noises in the envelope and TFS paths were adjusted to match the data. Simulations indicate that TFS cues are required to account for FM data for young normal-hearing listeners and that TFS processing is impaired for both older normal-hearing and hearing-impaired listeners. The role of TFS was further assessed by relating the monaural FM sensitivity to measures of interaural phase difference, commonly assumed to rely on binaural TFS sensitivity. The model demonstrates that binaural TFS sensitivity is considerably lower than monaural TFS sensitivity. Similar to FM thresholds, interaural phase difference sensitivity declined with age and hearing loss, although higher degradations were observed in binaural temporal processing compared to monaural processing. Overall, this model provides a novel tool to explore the mechanisms involved in FM processing in the normal auditory system and the degradations in FM sensitivity with ageing and hearing loss.

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“…The sEPSM X , in contrast, applies a temporal-only modulation-filtering process (as in the original sEPSM), also motivated by physiological data in the auditory brainstem and cortex in cat (Langner and Schreiner, 1988;Schreiner and Urbas, 1988), recent imaging studies in humans (Xiang et al, 2013), as well as computational modeling results from behavioral signal detection and modulation masking studies in humans (e.g., Dau et al, 1997a,b;Verhey et al, 1999;Derleth and Dau, 2000;Jepsen et al, 2008). The approach to measure the variation of modulation activity across frequency after the preprocessing in the model is also consistent with recent concepts in computational auditory scene analysis (Elhilali et al, 2009), CMR (Piechowiak et al, 2007;Dau et al, 2013), and sound texture synthesis (e.g., McDermott and Simoncelli, 2011). Using the across-channel variance as the measure of coherent across-frequency activity has been a pragmatic choice in the present study.…”

Section: B the Role Of Across-frequency Modulation Processingmentioning

confidence: 76%

“…In this model, the contribution to intelligibility from a given modulation channel was assumed to be proportional to the amount of the variance across peripheral channels for that particular modulation channel. Such a mechanism was inspired by models of co-modulation masking release (CMR; e.g., van de Par and Kohlrausch, 1998;Piechowiak et al, 2007;Dau et al, 2013). CMR refers to the greater detectability of a tone centered in a narrow band noise, surrounded by one or more flanking noise bands with co-modulated waveforms, compared to the same situation with uncorrelated flanking noise bands.…”

Section: Introductionmentioning

confidence: 99%

The role of auditory spectro-temporal modulation filtering and the decision metric for speech intelligibility prediction

Chabot-Leclerc

Jørgensen

Dau

2014

The Journal of the Acoustical Society of America

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Speech intelligibility models typically consist of a preprocessing part that transforms stimuli into some internal (auditory) representation and a decision metric that relates the internal representation to speech intelligibility. The present study analyzed the role of modulation filtering in the preprocessing of different speech intelligibility models by comparing predictions from models that either assume a spectro-temporal (i.e., two-dimensional) or a temporal-only (i.e., one-dimensional) modulation filterbank. Furthermore, the role of the decision metric for speech intelligibility was investigated by comparing predictions from models based on the signal-to-noise envelope power ratio, SNRenv, and the modulation transfer function, MTF. The models were evaluated in conditions of noisy speech (1) subjected to reverberation, (2) distorted by phase jitter, or (3) processed by noise reduction via spectral subtraction. The results suggested that a decision metric based on the SNRenv may provide a more general basis for predicting speech intelligibility than a metric based on the MTF. Moreover, the one-dimensional modulation filtering process was found to be sufficient to account for the data when combined with a measure of across (audio) frequency variability at the output of the auditory preprocessing. A complex spectro-temporal modulation filterbank might therefore not be required for speech intelligibility prediction.

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Modeling within- and across-channel processes in comodulation masking release

Cited by 17 publications

References 58 publications

Effects of tonotopicity, adaptation, modulation tuning, and temporal coherence in “primitive” auditory stream segregation

Effects of tonotopicity, adaptation, modulation tuning, and temporal coherence in “primitive” auditory stream segregation

A two‐path model of auditory modulation detection using temporal fine structure and envelope cues

The role of auditory spectro-temporal modulation filtering and the decision metric for speech intelligibility prediction

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