"Improving Tail Performance of a Deliberation E2E ASR Model Using a Large ..."

Cal Peyser et al. (2020)

> Home

Details and statistics

DOI: 10.21437/INTERSPEECH.2020-1465

access: open

type: Conference or Workshop Paper

metadata version: 2021-01-29

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - conf/interspeech/PeyserMSAPK20
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/interspeech/PeyserMSAPK20
Cal Peyser, Sepand Mavandadi, Tara N. Sainath, James Apfel, Ruoming Pang, Shankar Kumar:
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus. INTERSPEECH 2020: 4921-4925

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.