THE AUDITORY MODELING TOOLBOX
Models included in the AMT (latest release, 1.6.0)
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.
| Peripheral models (chronologically) | Function | Doc | Code | Verification |
| Gammatone filterbank | gammatone |  | |  |
| Linear filtering for monaural masking (basic) | dau1996 |  | |  |
| Linear filtering for monaural masking (improved) | dau1997 | | | |
| Dual-resonance nonlinear filterbank (DRNL) | lopezpoveda2001 | | |  |
| Invertible Gammatone filterbank | hohmann2002 | | | |
| Auditory-nerve filterbank (basic) | zilany2007 | | | |
| Fast acting compression (CARFAC) model | lyon2011 |  | | |
| Cochlear transmission-line model (basic) | verhulst2012 | | | |
| Auditory-nerve filterbank (improved) | zilany2014 | | | |
| Cochlear transmission-line model (improved) | verhulst2015 |  | | |
| Compression in the simultaneous masker phase effect | tabuchi2016 | | | |
| Cochlear transmission-line model (improved, incl. brainstem) | verhulst2018 | | | |
| Auditory nerve filterbank (improved, ready for brainstem) | bruce2018 | | | |
Nonlinear filterbank (based on a broken-stick) including modulation filterbank | king2019 | | | |
| Nonlinear filterbank (based on the DRNL) including modulation filterbank | relanoiborra2019 | | | |
| Auditory-nerve spike generation | decheveigne2023 |  | | |
| Electrically stimulated nerve fiber (aLIFP model) | felsheim2024 | | | |
| Fast acting compression model with two capacitors (CARFAC v2) | lyon2024 | | | |
| Computational auditory signal processing and perception (CASP) model | paulick2024 | | | |
| Temporal-modulation sensitivity (chronologically) | Function | Doc | Code | Verification |
| Modulation (leaky-integrator model) | viemeister1979 | | | |
| Non-linear adapation network | karjalainen1996 | | | |
| Modulation filterbank (based on EPSM) | ewert2000 | | | |
| Auditory brainstem responses | roenne2012 | | | |
| Brainstem processing (CN and IC) | carney2015 | | | |
| Binaural processing (chronologically) | Function | Doc | Code | Verification |
| Binaural activity (based on cross-correlation) | lindemann1986 | | | |
| Binaural signal detection | breebaart2001 | | | |
| Binaural masking level difference | culling2004 | | | |
| Binaural activity map | takanen2013 | | | |
| Binaural processing | smalt2014 | | | |
| Binaural detection model based on interaural coherence | eurich2022 | | | |
| ITDs of hearing-aid users | pausch2022 | | | |
| Binaural masking level difference (dynamic sources) | bischof2023 | | | |
| Monaural speech perception (chronologically) | Function | Doc | Code | Verification |
| Short-time objective intelligibility | taal2011 | | | |
| Intelligibility in noise | joergensen2011 | | | |
| Intelligibility in noise | joergensen2013 | | | |
| Intelligibility with harmonic-cancellation | prudhomme2020 | | | |
| Binaural speech perception (chronologically) | Function | Doc | Code | Verification |
| Binaural intelligibility in stationary noise (from BRIRs) | jelfs2011 | | | |
| Binaural intelligibility of a reverberated speech target | leclere2015 | | | |
| Blind equalization-cancellation model | hauth2020 | | | |
| Binaural intelligibility in non-stationary noise considering audibility | vicente2020 | | | |
| Binaural intelligibility in non-stationary noise (NH listeners only) | vicente2020nh | | | |
| Binaural intelligibility in stationary noise | lavandier2022 | | | |
| Perceptual similarity (chronologically) | Function | Doc | Code | Verification |
| Monaural perceptual similarity | osses2021 | | | |
| Binaural perceptual similarity | mckenzie2022 | | | |
| Binaural perceptual similarity | llado2022 | | | |
| Audio quality (chronologically) | Function | Doc | Code | Verification |
| Binaural audio quality assessement (eMoBi-Q) | eurich2024 | | | |
| Loudness models (chronologically) | Function | Doc | Code | Verification |
| Stationary sounds | moore1997 | | | |
| Time-varying sounds | glasberg2002 | | | |
| Time-varying specific loudness for hearing loss specified by audiogram | bramslow2004 | | | |
| Binaural long-term total loudness for hearing loss specified by hair-cell impairments | chen2011 | | | |
| Binaural time-varying loudness | moore2016 | | | |
| Spatial models (chronologically) | Function | Doc | Code | Verification |
| Vertical-plane localization (simple) | zakarauskas1993 | | | |
| Median-plane localization | langendijk2002 | | | |
| Sound lateral direction | dietz2011 | | | |
| Lateralization, supervised training | may2011 | | | |
| Directional time-of-arrival (on-axis only) | ziegelwanger2013 | | | |
| Directional time-of-arrival in HRTFs (off-axis, robust) | ziegelwanger2014 | | | |
| ´Lateralization in cochlear-implant listeners | kelvasa2015 | | | |
| Sagittal-plane localization (simple) | baumgartner2013 | | | |
| Distance perception | georganti2013 | | | |
| Lateralization in sound reproduction systems | wierstorf2013 | | | |
| Sagittal-plane localization (robust) | baumgartner2014 | | | |
| Bayesian spherical sound localization (basic) | reijniers2014 | | | |
| Sagittal-plane localization (nonlinear, for hearing impairements) | baumgartner2016 | | | |
| Sound externalization (ILD based) | hassager2016 | | | |
| Sound externalization (reverberant spaces) | li2020 | | | |
| Sound externalization (multi-cue) | baumgartner2021 | | | |
| Bayesian sound localization (dynamic, ITD-based) | mclachlan2021 | | | |
| Bayesian spherical sound localization (static, multi-feature) | barumerli2023 | | | |
| Contextual lateralization based on interaural level differences | laback2023 | | |  |
| Headphone effect on time to localize a target (with FrAMBI) | llado2024 | | | |
| Data from various publications (chronologically) | Function | Doc | Code | Verification |
| Bark scale | data_zwicker1961 | | | |
| Data from Lindemann (1986a) | data_lindenmann1986 | | | |
| ABR wave V data as functon of level and sweeping rate | data_neely1988 | | | |
| Notched-noise masking thresholds for the ERB scale | data_glasberg1990 | | | |
| Stapes footplate diplacement | data_goode1994 | | | |
| Externalization ratings | data_hartmann1996 | | | |
| Localization performance (non-individualized) | data_middlebrooks1999 | | | |
| Masking threshold (binaural and monaural) | data_vandepar1999 | | | |
| BMLD thresholds | data_breebaart2001 | | | |
| Outer and middle ear filter data | data_lopezpoveda2001 | | | |
| Responses to amplitude panning in median plane | data_pulkki2001 | | | |
| Outer- and middle-ear data | data_glasberg2002 | | | |
| Localization performance and HRTFs | data_langendijk2002 | | | |
| Localization polar error rates | data_macpherson2003 | | | |
| Localization errors and spatial correlation coefficients (SCCs) | data_best2005 | | | |
| Localization response gains | data_sabin2005 | | | |
| Data involved in the modeling process | data_takanen2005 | | | |
| Tone bursts | data_harte2009 | | | |
| ABR wave V data | data_elberling2010 | | | |
| Localization performance | data_majdak2010 | | | |
| Signal reception thresholds | data_joergensen2011 | | | |
| Externalization ratings | data_best2012 | | | |
| "Unity responses" from Roenne (2012) | data_roenne2012 | | | |
| HRTFs and listener-specific sensitivities | data_baumgartner2013 | | | |
| Localization performance in sagittal planes | data_goupell2013 | | | |
| Localization training performance | data_majdak2013 | | | |
| Localization performance in the crosstalk cancellation (CTC) conditions | data_majdak2013ctc | | | |
| Data involved in the modeling process | data_wierstorf2013 | | | |
| HRTFs and other data involved | data_ziegelwanger2013 | | | |
| HRTFs and listener-specific sensitivities | data_baumgartner2014 | | | |
| HRTFs and other data involved | data_ziegelwanger2014 | | | |
| HRTFs and listener-specific sensitivities | data_baumgartner2016 | | | |
| Externalization ratings | data_hassager2016 | | | |
| HRTFs and data of a sound externalization model | data_baumgartner2017 | | | |
| Data from sound externalization experiments | data_baumgartner2017looming | | | |
| Reverberant harmonic complex tone | data_bischof2023 | | | |
| Single-unit responses from the auditory nerve of gerbils | data_heeringa2024 | | | |
- (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 seen in the code repository. 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
Model overview of previous releases:
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