Towards real-world objective speech quality and intelligibility assessment using speech-enhancement residuals and convolutional long short-term memory networks-Reference-Cited by-同舟云学术

Towards real-world objective speech quality and intelligibility assessment using speech-enhancement residuals and convolutional long short-term memory networks

Published:2020-11 Issue:5 Volume:148 Page:3348-3359
ISSN:0001-4966
Container-title:The Journal of the Acoustical Society of America
language:en
Short-container-title:The Journal of the Acoustical Society of America

Author:

Dong Xuan¹^ORCID,Williamson Donald S.¹

Affiliation:

1. Department of Computer Science, Indiana University, Bloomington, Indiana 47408, USA

Funder

Directorate for Computer and Information Science and Engineering

Publisher

Acoustical Society of America (ASA)

Subject

Acoustics and Ultrasonics,Arts and Humanities (miscellaneous)

Link

http://asa.scitation.org/doi/am-pdf/10.1121/10.0002702

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1. From the perspective of perceptual speech quality: The robustness of frequency bands to noise;The Journal of the Acoustical Society of America;2024-03-01

2. Comparative Analysis of Pretrained Models for Speech Enhancement in Noisy Environments;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

3. MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibility Prediction Model for Hearing Aids;Interspeech 2022;2022-09-18

4. Non-intrusive Speech Quality Assessment with a Multi-Task Learning based Subband Adaptive Attention Temporal Convolutional Neural Network;Interspeech 2022;2022-09-18

5. MTI-Net: A Multi-Target Speech Intelligibility Prediction Model;Interspeech 2022;2022-09-18