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The trajectoRIR Database: Room Acoustic Recordings Along a Trajectory of Moving Microphones

Stefano Damiano, Kathleen MacWilliam, Valerio Lorenzoni, Thomas Dietzen, Toon van Waterschoot

Abstract

Data availability is essential in the development of acoustic signal processing algorithms, especially when it comes to data-driven approaches that demand large and diverse training datasets. For this reason, an increasing number of databases have been published in recent years, including either room impulse responses (RIRs) or audio recordings during motion. In this paper we introduce the trajectoRIR database, an extensive, multi-array collection of both dynamic and stationary acoustic recordings along a controlled trajectory in a room. Specifically, the database contains moving-microphone recordings and stationary RIRs that spatially sample the room acoustics along an L-shaped trajectory. This combination makes trajectoRIR unique and applicable to a wide range of tasks, including sound source localization and tracking, spatially dynamic sound field reconstruction, auralization, and system identification. The recording room has a reverberation time of 0.5 s, and the three different microphone configurations employed include a dummy head, with additional reference microphones located next to the ears, 3 first-order Ambisonics microphones, two circular arrays of 16 and 4 channels, and a 12-channel linear array. The motion of the microphones was achieved using a robotic cart traversing a 4.62 m-long rail at three speeds: [0.2, 0.4, 0.8] m/s. Audio signals were reproduced using two stationary loudspeakers. The collected database features 8648 stationary RIRs, as well as perfect sweeps, speech, music, and stationary noise recorded during motion. Python functions are provided to access the recorded audio and retrieve the associated geometric information.

The trajectoRIR Database: Room Acoustic Recordings Along a Trajectory of Moving Microphones

Abstract

Data availability is essential in the development of acoustic signal processing algorithms, especially when it comes to data-driven approaches that demand large and diverse training datasets. For this reason, an increasing number of databases have been published in recent years, including either room impulse responses (RIRs) or audio recordings during motion. In this paper we introduce the trajectoRIR database, an extensive, multi-array collection of both dynamic and stationary acoustic recordings along a controlled trajectory in a room. Specifically, the database contains moving-microphone recordings and stationary RIRs that spatially sample the room acoustics along an L-shaped trajectory. This combination makes trajectoRIR unique and applicable to a wide range of tasks, including sound source localization and tracking, spatially dynamic sound field reconstruction, auralization, and system identification. The recording room has a reverberation time of 0.5 s, and the three different microphone configurations employed include a dummy head, with additional reference microphones located next to the ears, 3 first-order Ambisonics microphones, two circular arrays of 16 and 4 channels, and a 12-channel linear array. The motion of the microphones was achieved using a robotic cart traversing a 4.62 m-long rail at three speeds: [0.2, 0.4, 0.8] m/s. Audio signals were reproduced using two stationary loudspeakers. The collected database features 8648 stationary RIRs, as well as perfect sweeps, speech, music, and stationary noise recorded during motion. Python functions are provided to access the recorded audio and retrieve the associated geometric information.

Paper Structure

This paper contains 29 sections, 14 equations, 10 figures, 7 tables.

Figures (10)

  • Figure 1: View of the recording setup in the AIL room, with the MC2 array configuration.
  • Figure 2: Scheme of the trajectory built using the rail system and used to record the database. The direction of the cartesian axes is also reported for reference (the actual coordinate system is centered in P1, as indicated by the red arrow). Loudspeaker positions are labeled SL (loudspeaker left) and SR (loudspeaker right). All indicated dimensions are approximate and only for illustrative purposes: accurate geometrical information is provided in the database.
  • Figure 3: Positioning of the rail system within the AIL room. The absolute coordinates of all positions and of the two loudspeakers can be retrieved using the geometrical information provided in the database.
  • Figure 4: Pictures (left column) and top view of the polar plots (right column) of the MC1 (a), MC2 (b) and MC3 (c) microphone array configurations.
  • Figure 5: Stacked plot of RIRs along the trajectory, computed using the ULA1 microphone of the MC3 configuration and the SL loudspeaker.
  • ...and 5 more figures