Stress classifiers trained on Wav2vec 2.0 embeddings distinguish stressed and unstressed syllables in Dutch, English, German, Polish and Hungarian, with language-specific structure that separates fixed and variable stress languages.
This model is pre-trained on 500,000 hours of speech recordings across 128 languages, including the five languages featuring in our study
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Word stress in self-supervised speech models: A cross-linguistic comparison
Stress classifiers trained on Wav2vec 2.0 embeddings distinguish stressed and unstressed syllables in Dutch, English, German, Polish and Hungarian, with language-specific structure that separates fixed and variable stress languages.