Electrolaryngeal speech enhancement based on a two stage framework with bottleneck feature refinement and voice conversion

Yang, Yaogen; Zhang, Haozhe; Cai, Zexin; Shi, Yao; Li, Ming; Zhang, Dong; Ding, Xiaoqing; Deng, Jian; Wang, Jie

doi:10.1016/j.bspc.2022.104279

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Electrolaryngeal speech enhancement based on a two stage framework with bottleneck feature refinement and voice conversion

Cited by 6 publications

References 30 publications

Speech enhancement using deep complex convolutional neural network (DCCNN) model

Speech enhancement using deep complex convolutional neural network (DCCNN) model

Speech enhancement system using deep neural network optimized with Battle Royale Optimization

Compact deep neural networks for real-time speech enhancement on resource-limited devices

Contact Info

Product

Resources

About