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20192025
most citedAny-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling

84 citations · 183 across the 32 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

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★ 84 cited

Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling

Songxiang Liu, Yuewen Cao, Disong Wang +3

This paper proposes an any-to-many location-relative, sequence-to-sequence (seq2seq), non-parallel voice conversion approach, which utilizes text supervision during training. In th…

eess.AS2020★ 12 cited

Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification

Xu Li, Na Li, Jinghua Zhong +5

Recently adversarial attacks on automatic speaker verification (ASV) systems attracted widespread attention as they pose severe threats to ASV systems. However, methods to defend a…

eess.AS2020★ 6 cited

Bayesian x-vector: Bayesian Neural Network based x-vector System for Speaker Verification

Xu Li, Jinghua Zhong, Jianwei Yu +4

Speaker verification systems usually suffer from the mismatch problem between training and evaluation data, such as speaker population mismatch, the channel and environment variati…

cs.CL2020★ 1 cited

Deep segmental phonetic posterior-grams based discovery of non-categories in L2 English speech

Xu Li, Xixin Wu, Xunying Liu +1

Second language (L2) speech is often labeled with the native, phone categories. However, in many cases, it is difficult to decide on a categorical phone that an L2 segment belongs…