This dataset is supplementary material to the conference paper "Multi-Microphone Noise Data Augmentation for DNN-based Own Voice Reconstruction for Hearables in Noisy Environments" presented at ICASSP 2024 [1]. The dataset consists of impulse response measurements for 18 device users (5 female, 13 male) wearing hearable devices in both ears. The dataset was recorded in a sound-proof listening room using the Hearpiece prototype device (closed vent variant) [2] with a sampling frequency of 44.1 kHz.Impulse responses were measured with exponential sweeps from 80 Hz to 22.05 kHz with a duration of 3s played from 8 loudspeakers arranged in a circle of approximately 1.5m radius. The loudspeakers were located in the horizontal plane around the device users in 45°-steps (azimuth), starting from 22.5° to the right (where 0° is the front from the device users' perspective). The measurements are contained in the folder measurements. Each subfolder contains measurements from a different device user (e.g., VP_01). Each file contains the measurement for one direction, e.g. VP_01/data_0.npz contains the measurement of device user VP_01 for 22.5° azimuth, VP_01/data_1.npz is the measurement for the same device user for 22.5°+45° and so on.Measurements of device users where the device could not be inserted, or where the fit did not provide sufficient attenuation of external sounds to the in-ear microphone, were excluded. The impulse responses for two Hearpiece devices (closed vent), the concha and in-ear microphones were measured.A DPA 6060 lavalier clip microphone and a Tbone SC140 cardiod microphone were also included in the measurement as reference channels. The channels of the measurements (counting from 0): 0: Lavalier-microphone clipped to the shirt neck, shirt collar etc. of the device user 1: Reference microphone about 50 cm in front of the device user 2: Left in-ear microphone Hearpiece 3: Left concha microphone Hearpiece 4: Right in-ear microphone Hearpiece 5: Right concha microphone Hearpiece The measurement consists of impulse responses from the loudspeaker to the hearable device microphones and reference microphones, and corresponding transfer functions. Measurement metadata is included as well. The measurement files contain a python dictionary with the following fields: test_signal: the signal used for playback, consisting of a pause, the sweep, and another pause rec_signal: the recorded signal (sweep played from the loudspeaker, recorded at the microphones) sweep: the generated exponential sweep signal without pauses T: actual duration of the sweep (~2 Seconds) sweep_inv: inverse sweep (inverse w.r.t convolution of the sweep with the system response) sweep_inv_spectrum: spectrum of the inverse sweep f11: the frequency (in Hz) corresponding to the RampLen of the fade-in at the beginning of the sweep T_desd: desired duration of the sweep in seconds (2 Seconds) T_rec: recording duration in seconds (3 Seconds) start_frequency: Minimum frequency in the measurement / first frequency in the sweep (80 Hz) RampLen: Length of the fade-in ramp applied to the beginning of the sweep (based on a Hanning window) (2048 Samples) pre_pause_len: pause time between starting the measurement and sweep playback (88200 Samples) after_pause_len: pause time after sweep playback (44100 Samples) n_repetitions: Number of repetitions for the measurement (1) n_channels: Number of recorded channels including loopback (7 = 4 Hearpiece, 2 reference, 1 loopback) coh_mat: Mean Squared Coherence per channel (between the measured sweep and the playback sweep signal), has shape (frequencies up to samplerate/2 x channels) ir_loopback: the measured impulse response of the loopback channel, used to measure and compensate system delay from audio interface ir_mic: the measured impulse responses of the hearable and reference microphones, with shape (samples, channels) tf_mic: the measured transfer functions between the loudspeaker and the hearable and reference microphones, with shape (frequencies up to samplerate/2, channels) system_delay: the measured system delay from the audio interface (position of the peak of the correlation between playback sweep and loopback sweep signals) samplerate: The sampling rate used for the measurements (44100 Hz) This dataset is compatible with the German own voice recordings available at https://zenodo.org/records/10844599 (same participants+device insertion and measurement setup). The example script generate_indiv_noise_dataset.py can be used to augment a single-channel noise dataset to obtain simulated individual hearable noise signals,similar to [1] but using impulse responses directly as filters instead of first computing relative transfer functions and then applying them in the STFT domain. [1] M. Ohlenbusch, C. Rollwage, S. Doclo: "Multi-microphone Noise Data Augmentation for DNN-based Own Voice Reconstruction for Hearables in Noisy Environments". In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Seoul, South Korea, Apr. 2024, pp. 416-420.[2] F. Denk, M. Lettau, H. Schepker, S. Doclo, R. Roden, M. Blau, J.-H. Bach, J. Wellmann, and B. Kollmeier: "A One-Size-Fits-All Earpiece with Multiple Microphones and Drivers for Hearing Device Research". In: Proc. AES International Conference on Headphone Technology. San Francisco, USA, Aug. 2019.

The Oldenburg Branch for Hearing, Speech and Audio Technology HSA is funded in the program »Vorab« by the Lower Saxony Ministry of Science and Culture (MWK) and the Volkswagen Foundation for its further development. This work was partly funded by the German Ministry of Science and Education BMBF FK 16SV8811 and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project ID 352015383 - SFB 1330 C1.