Computationally Efficient DNN-Based Approximation of an Auditory Model for Applications in Speech Processing-Reference-Cited by-同舟云学术

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Computationally Efficient DNN-Based Approximation of an Auditory Model for Applications in Speech Processing

Published:2021-06-06 Issue: Volume: Page:
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Container-title:ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Nagathil Anil,Gobel Florian,Nelus Alexandru,Bruce Ian C.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9413349/9413350/09413993.pdf?arnumber=9413993

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. How to Train Your Ears: Auditory-Model Emulation for Large-Dynamic-Range Inputs and Mild-to-Severe Hearing Losses;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. WaveNet-based approximation of a cochlear filtering and hair cell transduction model;The Journal of the Acoustical Society of America;2023-07-01

3. A DNN-Based Hearing-Aid Strategy For Real-Time Processing: One Size Fits All;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. A Neural-Network Framework for the Design of Individualised Hearing-Loss Compensation;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023

5. A Non-Intrusive Speech Quality Evaluation Method Based on the Audiogram and Weighted Frequency Information for Hearing Aid;IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences;2023-01-01

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