Towards individualised speech enhancement: An SNR preference learning system for multi-modal hearing aids

Kirton-Wingate, Jasper; Ahmed, Shafique; Gogate, Mandar; Tsao, Yu; Hussain, Amir

Abstract

Since the advent of deep learning (DL), speech enhancement (SE) models have performed well under a variety of noise conditions. However, such systems may still introduce sonic artefacts, sound unnatural, and restrict the ability for a user to hear ambient sound which may be of importance. Hearing Aid (HA) users may wish to customise their SE systems to suit their personal preferences and day-to-day lifestyle. In this paper, we introduce a preference learning based SE (PLSE) model for future multi-modal HAs that can contextually exploit audio and visual information to improve listening comfort (LC). The proposed system estimates the Signal-to-noise ratio (SNR) as a basic objective speech quality measure which quantifies the relative amount of background noise present in speech, and directly correlates to the intelligibility of the signal. This is used alongside a preference elicitation framework which learns a predictive function to determine the target SNR. The system is novel, scaling the output of an AudioVisual (AV) DL-based SE model to provide HA users with individualised SE. Preliminary results support the hypothesis of improving the overall subjective LC, without significantly impeding the speech intelligibility.

Citation

Kirton-Wingate, J., Ahmed, S., Gogate, M., Tsao, Y., & Hussain, A. (2023, June). Towards individualised speech enhancement: An SNR preference learning system for multi-modal hearing aids. Presented at 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Rhodes Island, Greece

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
• Start Date: Jun 4, 2023
• End Date: Jun 10, 2023
• Acceptance Date: Apr 15, 2023
• Online Publication Date: Jun 4, 2023
• Publication Date: 2023
• Deposit Date: Jan 22, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Book Title: Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
• ISBN: 9798350302622
• DOI: https://doi.org/10.1109/icasspw59220.2023.10193122
• Public URL: http://researchrepository.napier.ac.uk/Output/3489689
• Publisher URL: https://2023.ieeeicassp.org/