An End-to-End Deep Learning Speech Coding and Denoising Strategy for Cochlear Implants-Reference-Cited by-同舟云学术

An End-to-End Deep Learning Speech Coding and Denoising Strategy for Cochlear Implants

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Gajecki Tom¹,Nogueira Waldo¹

Affiliation:

1. Medical University Hannover and Cluster of Excellence Hearing4all,Department of Otolaryngology,Hannover,Germany,30625

Funder

Deutsche Forschungsgemeinschaft

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746963.pdf?arnumber=9746963

Reference29 articles.

1. Deep Learning–Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients

2. Speech enhancement based on neural networks applied to cochlear implant coding strategies

3. Convolutional Neural Network-Based Speech Enhancement for Cochlear Implant Recipients

4. Conv-TasNet: Surpassing Ideal Time–Frequency Magnitude Masking for Speech Separation

5. Wave-u-net: A multi-scale neural network for end-to-end audio source separation;stoller;The International Society for Music Information Retrieval (ISMIR),2018

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1. A Fused Deep Denoising Sound Coding Strategy for Bilateral Cochlear Implants;IEEE Transactions on Biomedical Engineering;2024-07

2. Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives;IEEE Access;2024

3. A Deep Denoising Sound Coding Strategy for Cochlear Implants;IEEE Transactions on Biomedical Engineering;2023-09

4. Knowledge-Enhanced Compressed Measurements for Detection of Frequency-Hopping Spread Spectrum Signals Based on Task-Specific Information and Deep Neural Networks;Entropy;2022-12-21

5. A Deep Denoising Sound Coding Strategy for Cochlear Implants;2022-11-13