"ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed ..."

Chenda Li et al. (2021)

> Home

Details and statistics

DOI: 10.1109/SLT48900.2021.9383615

access: closed

type: Conference or Workshop Paper

metadata version: 2023-03-21

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/slt/Li0ZSCKHHBC021
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/slt/Li0ZSCKHHBC021
Chenda Li, Jing Shi, Wangyou Zhang, Aswin Shanmugam Subramanian, Xuankai Chang, Naoyuki Kamo, Moto Hira, Tomoki Hayashi, Christoph Böddeker, Zhuo Chen, Shinji Watanabe:
ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed for ASR Integration. SLT 2021: 785-792

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.