A Training Framework for Stereo-Aware Speech Enhancement Using Deep Neural Networks-Reference-Cited by-同舟云学术

A Training Framework for Stereo-Aware Speech Enhancement Using Deep Neural Networks

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

Author:

Toloosham Bahareh¹,Koishida Kazuhito²

Affiliation:

1. Harvard University,School of Engineering and Applied Sciences,Cambridge,MA

2. Microsoft Corporation,One Microsoft Way,Redmond,WA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746070.pdf?arnumber=9746070

Reference33 articles.

1. Speech enhancement based on Bayesian decision and spectral amplitude estimation

2. Method for the subjective assessment of intermediate quality level of audio systems;series;Int Telecom Union Radio Communion Assembly,2014

3. Perceptual objective listening quality assessment (polqa), the third generation itu-t standard for end-to-end speech quality measurement part i—temporal alignment;beerends;J Audio Eng Soc,2013

4. Interspeech 2021 conferencing-speech challenge: Towards far-field multi-channel speech enhancement for video conferencing;rao,2021

5. Complex Ratio Masking for Monaural Speech Separation

Cited by 3 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. Multi-space channel representation learning for mono-to-binaural conversion based audio deepfake detection;Information Fusion;2024-05

2. Real-Time Stereo Speech Enhancement with Spatial-Cue Preservation Based on Dual-Path Structure;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Speech signal analysis and enhancement using combined wavelet Fourier transform with stacked deep learning architecture;International Journal of Speech Technology;2023-09