Low-Latency Neural Speech Phase Prediction Based on Parallel Estimation Architecture and Anti-Wrapping Losses for Speech Generation Tasks-Reference-Cited by-同舟云学术

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Low-Latency Neural Speech Phase Prediction Based on Parallel Estimation Architecture and Anti-Wrapping Losses for Speech Generation Tasks

Published:2024 Issue: Volume:32 Page:2283-2296
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Ai Yang¹^ORCID,Ling Zhen-Hua¹^ORCID

Affiliation:

1. National Engineering Research Center of Speech and Language Information Processing, University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10491381.pdf?arnumber=10491381

Reference44 articles.

1. Neural Speech Phase Prediction Based on Parallel Estimation Architecture and Anti-Wrapping Losses

2. Speech enhancement based on deep denoising autoencoder

3. A Regression Approach to Speech Enhancement Based on Deep Neural Networks

4. T-GSA: Transformer with Gaussian-Weighted Self-Attention for Speech Enhancement

5. Speech bandwidth expansion based on deep neural networks

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