Neuro-MSBG: An End-to-End Neural Model for Hearing Loss Simulation

• URL: http://arxiv.org/abs/2507.15396v1
• Date: Mon, 21 Jul 2025 08:58:31 GMT
• Title: Neuro-MSBG: An End-to-End Neural Model for Hearing Loss Simulation
• Authors: Hui-Guan Yuan, Ryandhimas E. Zezario, Shafique Ahmed, Hsin-Min Wang, Kai-Lung Hua, Yu Tsao,
• Abstract summary: Neuro-MSBG is a lightweight end-to-end model with a personalized audiogram encoder for effective time-frequency modeling.<n>It reduces simulation runtime by a factor of 46 (from 0.970 seconds to 0.021 seconds for a 1 second input)
• Score: 29.459592567418913
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Hearing loss simulation models are essential for hearing aid deployment. However, existing models have high computational complexity and latency, which limits real-time applications and lack direct integration with speech processing systems. To address these issues, we propose Neuro-MSBG, a lightweight end-to-end model with a personalized audiogram encoder for effective time-frequency modeling. Experiments show that Neuro-MSBG supports parallel inference and retains the intelligibility and perceptual quality of the original MSBG, with a Spearman's rank correlation coefficient (SRCC) of 0.9247 for Short-Time Objective Intelligibility (STOI) and 0.8671 for Perceptual Evaluation of Speech Quality (PESQ). Neuro-MSBG reduces simulation runtime by a factor of 46 (from 0.970 seconds to 0.021 seconds for a 1 second input), further demonstrating its efficiency and practicality.

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