万灵药 发表于 2025-3-21 18:32:15

书目名称Deep Learning Based Speech Quality Prediction影响因子(影响力)<br>        http://figure.impactfactor.cn/if/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction影响因子(影响力)学科排名<br>        http://figure.impactfactor.cn/ifr/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction网络公开度<br>        http://figure.impactfactor.cn/at/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction网络公开度学科排名<br>        http://figure.impactfactor.cn/atr/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction被引频次<br>        http://figure.impactfactor.cn/tc/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction被引频次学科排名<br>        http://figure.impactfactor.cn/tcr/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction年度引用<br>        http://figure.impactfactor.cn/ii/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction年度引用学科排名<br>        http://figure.impactfactor.cn/iir/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction读者反馈<br>        http://figure.impactfactor.cn/5y/?ISSN=BK0264573<br><br>        <br><br>书目名称Deep Learning Based Speech Quality Prediction读者反馈学科排名<br>        http://figure.impactfactor.cn/5yr/?ISSN=BK0264573<br><br>        <br><br>

附录 发表于 2025-3-21 22:57:49

http://reply.papertrans.cn/27/2646/264573/264573_2.png

懒惰人民 发表于 2025-3-22 04:10:48

3D Clock Routing for Pre-bond Testabilityures are divided into three different stages. First, a frame-based neural network calculates features for each time step. The resulting feature sequence is then modelled by a time-dependency neural network. Finally, a pooling stage aggregates the sequence of features over time to estimate the overal

cinder 发表于 2025-3-22 05:50:29

http://reply.papertrans.cn/27/2646/264573/264573_4.png

灵敏 发表于 2025-3-22 10:44:54

Magda Mostafa,Ruth Baumeister,Martin Tamke dimensions are presented: Noisiness, Coloration, Discontinuity, and Loudness. The resulting dimension scores serve as degradation decomposition and help to understand the underlying reason for a low MOS score. The subjective ground truth values of these scores are perceptual speech quality dimensio

不能仁慈 发表于 2025-3-22 16:09:41

https://doi.org/10.1007/978-3-031-36302-3nd truth MOS that are the target values of the supervised learning approach. In particular, it is common practice to use multiple datasets for training and validation, as subjective data is usually sparse due to the costs that experiments involve. However, these datasets often come from different la

不能仁慈 发表于 2025-3-22 19:07:21

http://reply.papertrans.cn/27/2646/264573/264573_7.png

弯弯曲曲 发表于 2025-3-22 22:00:36

http://reply.papertrans.cn/27/2646/264573/264573_8.png

Peak-Bone-Mass 发表于 2025-3-23 02:08:11

http://reply.papertrans.cn/27/2646/264573/264573_9.png

FEIGN 发表于 2025-3-23 09:14:00

Power Delivery Network Design for 3D IClity prediction models is motivated with a summary of current state-of-the-art speech quality prediction models and their drawbacks. The two objectives and four research questions that are further investigated in this book are then presented with a following outline of the book.
页: [1] 2 3 4 5
查看完整版本: Titlebook: Deep Learning Based Speech Quality Prediction; Gabriel Mittag Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusive l