Associated dataset for "Evaluation of Sensor Self-Noise in Binaural Rendering of Spherical Microphone Array Signals"

The conducted instrumental and perceptual evaluation utilize the Real-Time Spherical Microphone Renderer (ReTiSAR) for binaural reproduction in Python. However, the provided execution configurations (see below) are probably not exactly in accordance with the latest ReTiSAR code base. Hence, the at the time employed code state should be used in order to exactly reproduce the rendering results in this data set. The frozen code state for this data set is available at:
https://github.com/AppliedAcousticsChalmers/ReTiSAR/releases/tag/v2020.ICASSP

Download the rendering pipeline and follow the setup instructions! Use the here included Conda environment file when setting up the Python environment. In this way you should obtain exactly the same Python setup as utilized in the instrumental and perceptual evaluation in the publication:

conda env create --file ReTiSAR_environment_freeze.yml

source activate ReTiSAR_ICASSP_freeze

Directory "SNR":

• Tools for instrumental evaluation (Section 4)
• Shell script to capture input and output signals of rendering pipeline for sound field (target / wanted) and self-noise (unwanted) components for all specified configurations
• Matlab script to analyse captured signal and generate system transfer plots (Figure 1 to Figure 3 and further configurations)

Directory "Relative Output Levels":

• Tools for preparation of perceptual evaluation (Section 5)
• Shell script to capture rendered uniformly contributing noise signals for all specified configurations
• Matlab script to analyse and level align captured signals and generate plot result plot (Figure 4)

Directory "Absolute Output Levels":

• Tools for specification of perceptual evaluation (Section 5)
• Shell script to capture reproduced uniformly contributing noise signals for all specified configurations
• Matlab script to analyse the calibrated captured signals yielding the average level in the ear signals of 58.2 dBSPL (Section 5.1)

Files in base directory and directory "Study Results":

• Tools for perceptual evaluation / user study (Section 5)
• Matlab GUI to conduct perceptual user study (employ by executing "ICASSP_gui.m", respective ReTiSAR instances are started and remote controlled by the GUI, raw study results will be stored in "results" directory)
• Matlab script to "calculate_conclusion.m" to analyse the raw study results and generate individual and conclusive result plots (Figure 5, Figure 6 and more)