Youzhi Tu

Orcid: 0000-0002-9580-2414

According to our database1, Youzhi Tu authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Links

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Bibliography

2024
Contrastive Self-Supervised Speaker Embedding With Sequential Disentanglement.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

Promoting Independence of Depression and Speaker Features for Speaker Disentanglement in Speech-Based Depression Detection.
Proceedings of the IEEE International Conference on Acoustics, 2024

Contrastive Speaker Embedding With Sequential Disentanglement.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Phonetic-aware speaker embedding for far-field speaker verification.
CoRR, 2023

Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations.
Proceedings of the International Conference on Machine Learning, 2023

2022
Aggregating Frame-Level Information in the Spectral Domain With Self-Attention for Speaker Embedding.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

A Survey on Text-Dependent and Text-Independent Speaker Verification.
IEEE Access, 2022

2021
Mutual Information Enhanced Training for Speaker Embedding.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Short-Time Spectral Aggregation for Speaker Embedding.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Variational Domain Adversarial Learning With Mutual Information Maximization for Speaker Verification.
IEEE ACM Trans. Audio Speech Lang. Process., 2020

Information Maximized Variational Domain Adversarial Learning for Speaker Verification.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Variational Domain Adversarial Learning for Speaker Verification.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Semi-supervised Nuisance-attribute Networks for Domain Adaptation.
Proceedings of the IEEE International Conference on Acoustics, 2019


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