Search Results for author:
Found 2 papers, 1 papers with code
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent identification (AID) fine-tuning task.
Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment
We show that fine-tuning with pseudo labels achieves a 5. 35% phoneme error rate reduction and 2. 48% MDD F1 score improvement over a labeled-samples-only fine-tuning baseline.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
