Issue |
Acta Acust.
Volume 8, 2024
|
|
---|---|---|
Article Number | 28 | |
Number of page(s) | 13 | |
Section | Speech | |
DOI | https://doi.org/10.1051/aacus/2024032 | |
Published online | 28 August 2024 |
Scientific Article
Modeling of speech-dependent own voice transfer characteristics for hearables with an in-ear microphone
1
Fraunhofer Institute for Digital Media Technology IDMT, Oldenburg Branch for Hearing, Speech and Audio Technology HSA, Marie-Curie-Straße 2, 26129 Oldenburg, Germany
2
Carl von Ossietzky University of Oldenburg, Department of Medical Physics and Acoustics and Cluster of Excellence Hearing4all, Carl-von-Ossietzky-Straße 11, 26129 Oldenburg, Germany
* Corresponding author: mattes.ohlenbusch@idmt.fraunhofer.de
Received:
22
March
2024
Accepted:
27
June
2024
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 and 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.
Key words: Own voice / Hearables / System identification / Acoustic modeling / Relative transfer function
© The Author(s), Published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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