Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones
arXiv:2310.06554 · doi:10.1051/aacus/2024032
Abstract
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.
20 pages, 11 figures; Extended version of arXiv:2309.08294 (more detailed description of the problem, additional models considered, more systematic evaluation conducted on a different, larger dataset) -> Updated version (20th march 2024): major changes after internal review; in submission
References in corpus (5)
- Configurable EBEN: Extreme Bandwidth Extension Network to enhance body-conducted speech capture
- Training Strategies for Own Voice Reconstruction in Hearing Protection Devices using an In-ear Microphone
- Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones
- Multi-Microphone Noise Data Augmentation for DNN-based Own Voice Reconstruction for Hearables in Noisy Environments
- Speech-dependent Modeling of Own Voice Transfer Characteristics for In-ear Microphones in Hearables