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7 results for “Hearables”
German own voice recordings with hearable microphones
<p>This dataset is supplementary material to the article "Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with an In-ear Microphone" published in Acta Acustica, vol. 8 (2024).</p> <p>The dataset consists of recordings of own voice speech of 18 talkers (5 female, 13 male) wearing hearable devices in both ears. All talkers were native German speakers. The dataset was recorded in a sound-proof listening booth using the Hearpiece prototype device (closed vent variant) [1].</p> <p>The speech uttered by the talkers is pre-determined text read from a screen. The talkers press a button on the screen to start the recording, read the sentence out loud in a normal voice, and press another button to stop the recording. It was possible for the talkers to re-record a sentence if desired. The sentences read by the talkers originate from the following sources:</p> <ul> <li>The north wind and the sun (German), 6 sentences</li> <li>Berlin and Marburg Sentences [2] (German), 2x100 sentences</li> <li>100 sentences for language learners [3] (German), 100 sentences</li> <li>Some held-out vowels and consonants</li> <li>[some seconds of silence]</li> </ul> <p>The full text read by each talker is written in <code>full_text.txt</code>.</p> <p>The recordings are contained in the folder <code>speech</code>. Each subfolder contains recordings from a different talker (e.g., <code>VP_01</code>). The sentences uttered by each talker are numbered following this scheme: <code>VP_01_0.wav</code> to <code>VP_01_313.wav</code>. Talkers 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.</p> <p>A DPA 6060 lavalier clip microphone and a Tbone SC140 cardiod microphone were recorded as reference signals. From two Hearpiece devices (closed vent), the concha and in-ear microphones were recorded. Audio was recorded at a sampling frequency of 44100 Hz.</p> <p>The channels of the recordings, counting from 0, recorded the following microphones:</p> <ul> <li>0: Lavalier-microphone clipped to the shirt neck, shirt collar etc. of the talker</li> <li>1: Reference microphone about 50 cm in front of the talker</li> <li>2: Left in-ear microphone Hearpiece</li> <li>3: Left concha microphone Hearpiece</li> <li>4: Right in-ear microphone Hearpiece</li> <li>5: Right concha microphone Hearpiece</li> </ul> <p>[1] 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.</p> <p>[2] A. P. Simpson, K. J. Kohler, and T. Rettstadt. "The Kiel Corpus of Read/Spontaneous Speech: Acoustic Data Base, Processing Tools, and Analysis Results". In: Arbeitsberichte Institut für Phonetik Und Digitale Sprachverarbeitung Universität Kiel. Vol. 32. IPDS, Nov. 1997, pp. 243-247.</p> <p>[3] A. Neustein. "100 Sätze Reichen Für Ein Ganzes Leben" (Blog-post). https://deutschlernerblog.de/100-saetze-reichen-fuer-ein-ganzes-leben/. Aug. 2019.</p> <p> </p> <p> </p>
Transfer function measurements for simulating environmental noise at hearable microphones
<p>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].</p> <p>The dataset consists of impulse response measurements for 18 device users (5 female, 13 male) wearing hearable devices in both ears. <br>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.<br>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. <br>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).</p> <p>The measurements are contained in the folder <code>measurements</code>. Each subfolder contains measurements from a different device user (e.g., <code>VP_01</code>). <br>Each file contains the measurement for one direction, e.g. <code>VP_01/data_0.npz</code> contains the measurement of device user <code>VP_01</code> for 22.5° azimuth, <code>VP_01/data_1.npz</code> is the measurement for the same device user for 22.5°+45° and so on.<br>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.</p> <p>The impulse responses for two Hearpiece devices (closed vent), the concha and in-ear microphones were measured.<br>A DPA 6060 lavalier clip microphone and a Tbone SC140 cardiod microphone were also included in the measurement as reference channels. </p> <p>The channels of the measurements (counting from 0):</p> <p> 0: Lavalier-microphone clipped to the shirt neck, shirt collar etc. of the device user<br> 1: Reference microphone about 50 cm in front of the device user<br> 2: Left in-ear microphone Hearpiece<br> 3: Left concha microphone Hearpiece<br> 4: Right in-ear microphone Hearpiece<br> 5: Right concha microphone Hearpiece</p> <p><br>The measurement consists of impulse responses from the loudspeaker to the hearable device microphones and reference microphones, and corresponding transfer functions. <br>Measurement metadata is included as well. <br>The measurement files contain a python dictionary with the following fields:</p> <ul> <li><code>test_signal</code>: the signal used for playback, consisting of a pause, the sweep, and another pause</li> <li><code>rec_signal</code>: the recorded signal (sweep played from the loudspeaker, recorded at the microphones)</li> <li><code>sweep</code>: the generated exponential sweep signal without pauses</li> <li><code>T</code>: actual duration of the sweep (~2 Seconds)</li> <li><code>sweep_inv</code>: inverse sweep (inverse w.r.t convolution of the sweep with the system response)</li> <li><code>sweep_inv_spectrum</code>: spectrum of the inverse sweep</li> <li><code>f11</code>: the frequency (in Hz) corresponding to the <code>RampLen</code> of the fade-in at the beginning of the sweep</li> <li><code>T_desd</code>: desired duration of the sweep in seconds (2 Seconds)</li> <li><code>T_rec</code>: recording duration in seconds (3 Seconds)</li> <li><code>start_frequency</code>: Minimum frequency in the measurement / first frequency in the sweep (80 Hz)</li> <li><code>RampLen</code>: Length of the fade-in ramp applied to the beginning of the sweep (based on a Hanning window) (2048 Samples)</li> <li><code>pre_pause_len</code>: pause time between starting the measurement and sweep playback (88200 Samples)</li> <li><code>after_pause_len</code>: pause time after sweep playback (44100 Samples)</li> <li><code>n_repetitions</code>: Number of repetitions for the measurement (1)</li> <li><code>n_channels</code>: Number of recorded channels including loopback (7 = 4 Hearpiece, 2 reference, 1 loopback)</li> <li><code>coh_mat</code>: Mean Squared Coherence per channel (between the measured sweep and the playback sweep signal), has shape (frequencies up to <code>samplerate</code>/2 x channels)</li> <li><code>ir_loopback</code>: the measured impulse response of the loopback channel, used to measure and compensate system delay from audio interface</li> <li><code>ir_mic</code>: the measured impulse responses of the hearable and reference microphones, with shape (samples, channels)</li> <li><code>tf_mic</code>: the measured transfer functions between the loudspeaker and the hearable and reference microphones, with shape (frequencies up to <code>samplerate</code>/2, channels)</li> <li><code>system_delay</code>: the measured system delay from the audio interface (position of the peak of the correlation between playback sweep and loopback sweep signals)</li> <li><code>samplerate</code>: The sampling rate used for the measurements (44100 Hz)</li> </ul> <p>This dataset is compatible with the German own voice recordings available at <a href="../records/10844599" target="_blank" rel="noopener">https://zenodo.org/records/10844599</a> (same participants+device insertion and measurement setup).</p> <p>The example script <code>generate_indiv_noise_dataset.py</code> can be used to augment a single-channel noise dataset to obtain simulated individual hearable noise signals,<br>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.</p> <p><br>[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.<br>[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.</p>
Data for: Hearable devices with sound bubbles
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Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones: Audio Examples
<p>This upload contains audio examples for the preprint "Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones".</p> <p>The audio files correspond to subplots of the spectrogram shown in the default preview, starting from the upper left corner (subplot 0) to the upper right corner (subplot 1) and so on.</p> <h2>Abstract</h2> <p>Many hearables contain an in-ear microphone, which may be used to capture the own voice of its user. However, due to the hearable occluding the ear canal, the in-ear microphone mostly records body-conducted speech, typically suffering from band-limitation effects and amplification at low frequencies. Since the occlusion effect is determined by the ratio between the air-conducted and body-conducted components of own voice, the own voice transfer characteristics between the outer face of the hearable and the in-ear microphone depend on the speech content and the individual talker. In this paper, we propose a speech-dependent model of the own voice transfer characteristics based on phoneme recognition, assuming a linear time-invariant relative transfer function for each phoneme. We consider both individual models as well as models averaged over several talkers. Experimental results based on recordings with a prototype hearable show that the proposed speech-dependent model enables to simulate in-ear signals more accurately than a speech-independent model in terms of technical measures, especially under utterance mismatch and talker mismatch. Additionally, simulation results show that talker-averaged models generalize better to different talkers than individual models.</p> <p> </p> <p>The examples are also available here: <a href="https://m-ohlenbusch.github.io/own_voice_modeling_examples/" target="_blank" rel="noopener">https://m-ohlenbusch.github.io/own_voice_modeling_examples/</a></p> <p>Arxiv preprint: <a href="https://arxiv.org/abs/2310.06554">https://arxiv.org/abs/2310.06554</a></p>
Hearables: Ear-ECG and PPG for Detection of Cardiac Arrhythmias
ClinicalTrials.gov study NCT06667258. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Hearables: feasibility of recording cardiac rhythms from head and in-ear locations
Mobile technologies for the recording of vital signs and neural signals are envisaged to underpin the operation of future health services. For practical purposes, unobtrusive devices are favoured, such as those embedded in a helmet or incorporated onto an earplug. However, these locations have so far been underexplored, as the comparably narrow neck impedes the propagation of vital signals from the torso to the head surface. To establish the principles behind electrocardiogram (ECG) recordings from head and ear locations, we first introduce a realistic three-dimensional biophysics model for the propagation of cardiac electric potentials to the head surface, which demonstrates the feasibility of head-ECG recordings. Next, the proposed biophysics propagation model is verified over comprehensive real-world experiments based on head- and in-ear-ECG measurements. It is shown both that the proposed model is an excellent match for the recordings, and that the quality of head- and ear-ECG is sufficient for a reliable identification of the timing and shape of the characteristic P-, Q-, R-, S- and T-waves within the cardiac cycle. This opens up a range of new possibilities in the identification and management of heart conditions, such as myocardial infarction and atrial fibrillation, based on 24/7 continuous in-ear measurements. The study therefore paves the way for the incorporation of the cardiac modality into future 'hearables', unobtrusive devices for health monitoring.
Data from: Hearables: feasibility of recording cardiac rhythms from head and in-ear locations
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