Literature DB >> 27586738

Auditory "bubbles": Efficient classification of the spectrotemporal modulations essential for speech intelligibility.

Jonathan H Venezia1, Gregory Hickok1, Virginia M Richards1.   

Abstract

Speech intelligibility depends on the integrity of spectrotemporal patterns in the signal. The current study is concerned with the speech modulation power spectrum (MPS), which is a two-dimensional representation of energy at different combinations of temporal and spectral (i.e., spectrotemporal) modulation rates. A psychophysical procedure was developed to identify the regions of the MPS that contribute to successful reception of auditory sentences. The procedure, based on the two-dimensional image classification technique known as "bubbles" (Gosselin and Schyns (2001). Vision Res. 41, 2261-2271), involves filtering (i.e., degrading) the speech signal by removing parts of the MPS at random, and relating filter patterns to observer performance (keywords identified) over a number of trials. The result is a classification image (CImg) or "perceptual map" that emphasizes regions of the MPS essential for speech intelligibility. This procedure was tested using normal-rate and 2×-time-compressed sentences. The results indicated: (a) CImgs could be reliably estimated in individual listeners in relatively few trials, (b) CImgs tracked changes in spectrotemporal modulation energy induced by time compression, though not completely, indicating that "perceptual maps" deviated from physical stimulus energy, and (c) the bubbles method captured variance in intelligibility not reflected in a common modulation-based intelligibility metric (spectrotemporal modulation index or STMI).

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Mesh:

Year:  2016        PMID: 27586738      PMCID: PMC5848825          DOI: 10.1121/1.4960544

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  60 in total

1.  Spectrotemporal features of the auditory cortex: the activation in response to dynamic ripples.

Authors:  Dave R M Langers; Walter H Backes; Pim van Dijk
Journal:  Neuroimage       Date:  2003-09       Impact factor: 6.556

2.  Tuning for spectro-temporal modulations as a mechanism for auditory discrimination of natural sounds.

Authors:  Sarah M N Woolley; Thane E Fremouw; Anne Hsu; Frédéric E Theunissen
Journal:  Nat Neurosci       Date:  2005-09-04       Impact factor: 24.884

3.  Dissociations in perceptual learning revealed by adult age differences in adaptation to time-compressed speech.

Authors:  Jonathan E Peelle; Arthur Wingfield
Journal:  J Exp Psychol Hum Percept Perform       Date:  2005-12       Impact factor: 3.332

4.  Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex.

Authors:  Huan Luo; David Poeppel
Journal:  Neuron       Date:  2007-06-21       Impact factor: 17.173

5.  Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing.

Authors:  Søren Jørgensen; Torsten Dau
Journal:  J Acoust Soc Am       Date:  2011-09       Impact factor: 1.840

Review 6.  Neural processing of natural sounds.

Authors:  Frédéric E Theunissen; Julie E Elie
Journal:  Nat Rev Neurosci       Date:  2014-06       Impact factor: 34.870

7.  Effect of reducing slow temporal modulations on speech reception.

Authors:  R Drullman; J M Festen; R Plomp
Journal:  J Acoust Soc Am       Date:  1994-05       Impact factor: 1.840

8.  The modulation transfer function for speech intelligibility.

Authors:  Taffeta M Elliott; Frédéric E Theunissen
Journal:  PLoS Comput Biol       Date:  2009-03-06       Impact factor: 4.475

9.  Reconstructing speech from human auditory cortex.

Authors:  Brian N Pasley; Stephen V David; Nima Mesgarani; Adeen Flinker; Shihab A Shamma; Nathan E Crone; Robert T Knight; Edward F Chang
Journal:  PLoS Biol       Date:  2012-01-31       Impact factor: 8.029

10.  Encoding of natural sounds at multiple spectral and temporal resolutions in the human auditory cortex.

Authors:  Roberta Santoro; Michelle Moerel; Federico De Martino; Rainer Goebel; Kamil Ugurbil; Essa Yacoub; Elia Formisano
Journal:  PLoS Comput Biol       Date:  2014-01-02       Impact factor: 4.475

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  12 in total

1.  Measuring time-frequency importance functions of speech with bubble noise.

Authors:  Michael I Mandel; Sarah E Yoho; Eric W Healy
Journal:  J Acoust Soc Am       Date:  2016-10       Impact factor: 1.840

2.  Identification of the Spectrotemporal Modulations That Support Speech Intelligibility in Hearing-Impaired and Normal-Hearing Listeners.

Authors:  Jonathan H Venezia; Allison-Graham Martin; Gregory Hickok; Virginia M Richards
Journal:  J Speech Lang Hear Res       Date:  2019-04-15       Impact factor: 2.297

3.  Forward masking of spectrotemporal modulation detection.

Authors:  Christopher Conroy; Andrew J Byrne; Gerald Kidd
Journal:  J Acoust Soc Am       Date:  2022-02       Impact factor: 1.840

4.  Rapid computations of spectrotemporal prediction error support perception of degraded speech.

Authors:  Ediz Sohoglu; Matthew H Davis
Journal:  Elife       Date:  2020-11-04       Impact factor: 8.140

5.  Speech-Driven Spectrotemporal Receptive Fields Beyond the Auditory Cortex.

Authors:  Jonathan H Venezia; Virginia M Richards; Gregory Hickok
Journal:  Hear Res       Date:  2021-07-10       Impact factor: 3.672

6.  Hierarchy of speech-driven spectrotemporal receptive fields in human auditory cortex.

Authors:  Jonathan H Venezia; Steven M Thurman; Virginia M Richards; Gregory Hickok
Journal:  Neuroimage       Date:  2018-11-28       Impact factor: 7.400

7.  Perceptually Salient Regions of the Modulation Power Spectrum for Musical Instrument Identification.

Authors:  Etienne Thoret; Philippe Depalle; Stephen McAdams
Journal:  Front Psychol       Date:  2017-04-13

8.  CLEESE: An open-source audio-transformation toolbox for data-driven experiments in speech and music cognition.

Authors:  Juan José Burred; Emmanuel Ponsot; Louise Goupil; Marco Liuni; Jean-Julien Aucouturier
Journal:  PLoS One       Date:  2019-04-04       Impact factor: 3.240

9.  Spectrotemporal modulation provides a unifying framework for auditory cortical asymmetries.

Authors:  Adeen Flinker; Werner K Doyle; Ashesh D Mehta; Orrin Devinsky; David Poeppel
Journal:  Nat Hum Behav       Date:  2019-03-04

10.  Mechanisms of Spectrotemporal Modulation Detection for Normal- and Hearing-Impaired Listeners.

Authors:  Emmanuel Ponsot; Léo Varnet; Nicolas Wallaert; Elza Daoud; Shihab A Shamma; Christian Lorenzi; Peter Neri
Journal:  Trends Hear       Date:  2021 Jan-Dec       Impact factor: 3.293

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