most citedImproved End-to-End Dysarthric Speech Recognition via Meta-learning Based Model Re-initialization

6 citations · 6 across the 2 of their papers we have counts for

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eess.AS2022

Speaker Identity Preservation in Dysarthric Speech Reconstruction by Adversarial Speaker Adaptation

Disong Wang, Songxiang Liu, Xixin Wu +4

Dysarthric speech reconstruction (DSR), which aims to improve the quality of dysarthric speech, remains a challenge, not only because we need to restore the speech to be normal, bu…

eess.AS2020★ 6 cited

Improved End-to-End Dysarthric Speech Recognition via Meta-learning Based Model Re-initialization

Disong Wang, Jianwei Yu, Xixin Wu +3

Dysarthric speech recognition is a challenging task as dysarthric data is limited and its acoustics deviate significantly from normal speech. Model-based speaker adaptation is a pr…

eess.AS2020

Learning Explicit Prosody Models and Deep Speaker Embeddings for Atypical Voice Conversion

Disong Wang, Songxiang Liu, Lifa Sun +3

Though significant progress has been made for the voice conversion (VC) of typical speech, VC for atypical speech, e.g., dysarthric and second-language (L2) speech, remains a chall…