audio.npy - the recordings of each sweep, arranged by [N_datapoints, N_Microphones, N_samples]
adjusted_audio.npy - audio.npy, but time-adjusted such that the audio files from all datapoints are time-aligned, using the method described in Appendix E.3.
centroid.npy - the x,y locations of the human in the room. Shape is [N_datapoints, 2]
deconvolved.npy - the RIRs. Shape is [N_datapoints, N_Microphones, N_samples]
directlines.npy - the sweep signal as measured from a loopback signal, where the output of the audio interface is routed directly into an input. This is used to estimate the delay in the system. The shape is [N_datapoints, N_samples]
skeletons.npy - the poses and joint locations as captured by each of the three cameras. The shape is [N_datapoints, N_Cameras, N_joints, 3]. The indexing of the joints is provided here.
music_audio.npy - the recordings of each music file, arranged by [N_datapoints, N_Microphones, N_samples]
adjusted_music.npy - music_audio.npy, but time-adjusted such that the audio files from all datapoints are time-aligned, using the method described in Appendix E.3.
music_directlines.npy - the music signal as measured from a loopback signal, where the output of the audio interface is routed directly into an input. This is used to estimate the delay in the system. The shape is [N_datapoints, N_samples]
music_deconvolved.npy - RIRs as measured by deconvolving the music source from the music recording. Shape is [N_datapoints, N_Microphones, N_samples]
music_sources.npy - the source signal of each music file. Shape is [N_datapoints, N_samples]