Neural LCS uses learned phoneme and word similarity instead of exact matches to align dysfluent speech to intended text, and it outperforms DTW and Hard LCS on simulated benchmarks.
Dataset (1) VCTK [19]:it includes 109 native English speakers with accented speech
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
dataset 1
citation-polarity summary
fields
eess.AS 1years
2025 1verdicts
CONDITIONAL 1roles
dataset 1polarities
use dataset 1representative citing papers
citing papers explorer
-
Seamless Dysfluent Speech Text Alignment for Disordered Speech Analysis
Neural LCS uses learned phoneme and word similarity instead of exact matches to align dysfluent speech to intended text, and it outperforms DTW and Hard LCS on simulated benchmarks.