A sequence-to-sequence voice conversion model trained on a native rater's shadowing utterances can spot unintelligible segments in L2 speech, beating an ASR baseline on the native rater but not on all listeners.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Perception-Based L2 Speech Intelligibility Indicator: Leveraging a Rater's Shadowing and Sequence-to-sequence Voice Conversion
A sequence-to-sequence voice conversion model trained on a native rater's shadowing utterances can spot unintelligible segments in L2 speech, beating an ASR baseline on the native rater but not on all listeners.