Tagging via Viterbi Decoding

Published

Jun 1, 2002

Tagging via Viterbi Decoding is an AI model developed by AT&T (United States), first published in June 2002. It works in the language domain, on tasks such as binary classification and part-of-speech tagging.

Epoch AI has no training-compute estimate for this model. It was trained on roughly 929K datapoints.

The reference paper has 2,582 citations.

Full record

Organization: AT&T
Country of organization: United States
Domain: Language
Task: Binary classification, Part-of-speech tagging
Dataset size: 929K
Citations: 2,582