THE AUDITORY MODELING TOOLBOX

Models included in the AMT 1.0.0

In order to describe the quality of the models available in the AMT, we rate the implementation of every model by considering its source code and documentation. We also rate the models in terms of their verification, i.e., we rate the results of the implementation versus the results shown in the corresponding publication. The comparison is done within the experiments implemented in the exp_ functions. In the best case, the experiments produce the same results as in the publication - up to some minor layout issues in the graphical representations.

The following table provides an overview of the available models, their documentation, code, and verification status.

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Peripheral modelsFunctionDocCodeVerification
Gammatone filterbankgammatone
Linear filtering for monaural masking (basic)dau1996
Linear filtering for monaural masking (improved)dau1997
Invertible Gammatone filterbankhohmann2002
Dual-resonance nonlinear filterbank (DRNL)lopezpoveda2001
Fast acting compression (CARFAC) modellyon2011
Cochlear transmission-line model (basic)verhulst2012
Cochlear transmission-line model (improved)verhulst2015
Cochlear transmission-line model (improved, incl. brainstem)verhulst2018
Auditory-nerve filterbank (basic)zilany2007
Auditory-nerve filterbank (improved)zilany2014
Auditory nerve filterbank (improved, ready for brainstem)bruce2018
Temporal-modulation sensitivityFunctionDocCodeVerification
Brainstem processing (CN and IC)carney2015
Auditory brainstem responsesroenne2012
Modulation filterbank (based on EPSM)ewert2000
Modulation filterbank (based on nonlinear processing)king2019
Modulation filterbank (based on DRNL)relanoiborra2019
Modulation (leaky-integrator model)viemeister1979
Non-linear adapation networkkarjalainen1996
Binaural processingFunctionDocCodeVerification
Binaural activity (based on cross-correlation)lindemann1986
Binaural signal detectionbreebaart2001
Binaural activity maptakanen2013
Monaural speech perceptionFunctionDocCodeVerification
Intelligibility in noisejoergensen2011
Intelligibility in noisejoergensen2013
Short-time objective intelligibility taal2011
Binaural speech perceptionFunctionDocCodeVerification
Binaral speech intelligibilityculling2004
Blind equalization-cancellation modelhauth2020
Spatial unmaskingjelfs2011
Perceptual similarityFunctionDocCodeVerification
Monaural perceptual similarityosses2021
Binarual perceptual similaritymckenzie2021
Loudness modelsFunctionDocCodeVerification
Stationary soundsmoore1997
Time-varying soundsglasberg2002
Binaural hearing impairedchen2011
Binaural loudnessmoore2016
Spatial modelsFunctionDocCodeVerification
Sound lateral directiondietz2011
Lateralization, supervised trainingmay2011
´Lateralization in cochlear-implant listenerskelvasa2015
Median-plane localizationlangendijk2002
Vertical-plane localization (simple)zakarauskas1993
Sagittal-plane localization (simple)baumgartner2013
Sagittal-plane localization (robust)baumgartner2014
Sagittal-plane localization (nonlinear, for hearing impairements)baumgartner2016
Sound externalization (ILD based)hassager2016
Sound externalization (cue specific)baumgartner2017
Sound externalization (multi-cue)baumgartner2021
Sound externalization (reverberant spaces)li2020
Distance perceptiongeorganti2013
Bayesian spherical sound localization (basic)reijniers2014
Bayesian spherical sound localization (multi-feature)barumerli2021
Bayesian sound localization (dynamic, ITD-based)mclachlan2021
Lateralization in sound reproduction systemswierstorf2013
Directional time-of-arrival (on-axis only)ziegelwanger2013
Directional time-of-arrival in HRTFs (off-axis, robust)ziegelwanger2014
Data from various publicationsFunctionDocCodeVerification
HRTFs and listener-specific sensitivities from Baumgartner et al. (2013)data_baumgartner2013
HRTFs and listener-specific sensitivities from Baumgartner et al. (2014)data_baumgartner2014
HRTFs and listener-specific sensitivities from Baumgartner et al. (2016)data_baumgartner2016
Localization errors and SCCs from Best et al. (2005)data_best2005
Externalization ratings from Boyd et al. (2012)data_best2012
BMLD thresholds from Breebaart et al. (2001)data_breebaart2001
ABR wave V data from Elberling et al. (2010)data_elberling2010
Notched-noise masking thresholds for the ERB scaledata_glasberg1990
Stapes footplate diplacement from Goode et al. (1994)data_goode1994
Localization performance in sagittal planes from Goupell et al. (2013)data_goupell2013
Tone burst stimuli from Harte et al. (2009)data_harte2009
Externalization ratings from Hartmann and Wittenberg (1996)data_hartmann1996
Externalization ratings from Hassager et al. (2016)data_hassager2016
SRTs tested by Joergensen and Dau (2011)data_joergensen2011
Localization performance and HRTFs from Langendijk et al. (2002)data_langendijk2002
Data from Lindemann (1986a)data_lindenmann1986
Outer and middle ear filter datadata_lopezpoveda2001
Localization polar error rates from Macpherson et al. (2003)data_macpherson2003
Localization performance from Majdak et al. (2010)data_majdak2010
Localization training performance from Majdak et al. (2013)data_majdak2013
Localization performance (CTC condition) from Majdak et al. (2013b)data_majdak2013ctc
Localization performance (non-individualized) from Middlebrooks (1999)data_middlebrooks1999
ABR wave V data as functon of level and sweeping rate from Neely et al. (1988)data_neely1988
Responses to amplitude panning in median plane from Pulkki (2001)data_pulkki2001
"Unity responses" from Roenne (2012)data_roenne2012
Localization response gains from Sabin et al. (2005)data_sabin2005
Data involved in the modeling process of Takanen et al. (2005)data_takanen2005
Masking threshold (binaural/monaural) from van der Par and Kohlrausch (1999)data_vandepar1999
Data involved in the modeling process of Wierstorf et al. (2013)data_wierstorf2013
HRTFs and other data involved in Ziegelwanger et al. (2013)data_ziegelwanger2013
HRTFs and other data involved in Ziegelwanger et al. (2014)data_ziegelwanger2014
Bark scale according to Zwicker (1961)data_zwicker1961
Data from sound externalization experiments Baumgartner et al. (2017)data_baumgartner2017looming
HRTFs and data of a sound externalization model Baumgartner et al. (2017b)data_baumgartner2017
Outer- and middle-ear data from Glasberg and Moore (2002)data_glasberg2002
Legend for the documentation and the code:
  • (Submitted): The model has been submitted to the AMT. There is, however, no working code/documentation in the AMT, or there are compilation errors, or some libraries are missing. The current state of the integration can be provided upon request. In the release version, the model neither appears on the website nor is available for download.
  • (OK): The code fits the AMT conventions just enough for being available for download. The model and its documentation appear on the website, but major work is still required.
  • (Good): The code/documentation follows our conventions, but there are open issues.
  • (Perfect): The code/documentation is fully up to our conventions, no open issues.

Legend for the verifications:
  • (Unknown): The AMT can not run experiments for this model and can not produce results for a verification. This might be the case when the verification code has not been provided or nobody has verified yet.
  • (Untrusted): The verification code is available but the experiments do not reproduce the relevant parts of the publication. Such an implementation shall not be trusted as a basis for further developments.
  • (Qualified): The experiments produce similar results as in the publication in terms of showing trends and explaining the effects, but not necessarily matching the numerical results. Explanation for the differences can be provided, for example, not all original data available, or publication affected by a known and documented bug.
  • (Verified): The experiments produce the same results as in the publication. Minor differences are allowed if randomness is involved in the model, for instance, noise as input signal, probabilistic modeling approaches, and a plausible explanation is provided
Note that the description of a model implementation is only a snapshot of the development since the implementations in the AMT are continuously developed, evaluated, and improved.

Model overview of previous releases: