Two!Ears documentation contents¶
- First steps
- Binaural simulator
- Robotic platform
- Auditory front-end
- Overview
- Technical description
- Available processors
- Pre-processing (
preProc.m
) - Auditory filter bank
- Inner hair-cell (
ihcProc.m
) - Adaptation (
adaptationProc.m
) - Auto-correlation (
autocorrelationProc.m
) - Rate-map (
ratemapProc.m
) - Spectral features (
spectralFeaturesProc.m
) - Onset strength (
onsetProc.m
) - Offset strength (
offsetProc.m
) - Binary onset and offset maps (
transientMapProc.m
) - Pitch (
pitchProc.m
) - Medial Olivo-Cochlear (MOC) feedback (
mocProc.m
) - Amplitude modulation spectrogram (
modulationProc.m
) - Spectro-temporal modulation spectrogram
- Cross-correlation (
crosscorrelationProc.m
) - Interaural time differences (
itdProc.m
) - Interaural level differences (
ildProc.m
) - Interaural coherence (
icProc.m
) - Precedence effect (
precedenceProc.m
)
- Pre-processing (
- Add your own processors
- Getting started and setting up processor properties
- Implement static methods
- Implement parameters “getter” methods
- Implement the processor constructor
- Preliminary testing
- Implement the core processing method
- Override parent methods
- Allow alternative processing options
- Implement a new signal type
- Recommendations for final testing
- Credits
- Blackboard system
- Introduction
- Usage
- Blackboard architecture
- Knowledge sources
- Abstract knowledge source
- Auditory front-end knowledge source:
AuditoryFrontEndKS
- Auditory signal dependent knowledge source superclass:
AuditoryFrontEndDepKS
- Localisation knowledge sources
- Identification knowledge sources
- Sound quality related knowledge sources
- Stream segregation knowledge sources
- Number of source estimation knowledge sources
- Add your own knowledge sources
- Model training
- Auditory Machine Learning Training and Testing Pipeline
- Database
- Examples
- Localisation with and without head rotations
- Localisation - looking at the results in detail
- DNN-based localisation under reverberant conditions
- GMM-based localisation under reverberant conditions
- Train sound type identification models
- Identification of sound types
- Stream binaural signals from BASS to Matlab
- Control the rotation of a KEMAR motorized head from Matlab
- Prediction of coloration in spatial audio systems
- Prediction of localisation in spatial audio systems
- Development of Two!Ears