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Berrak Sisman
Berrak Sisman
Electrical & Computer Engineering Department, The University of Texas at Dallas
Zweryfikowany adres z utdallas.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
An overview of voice conversion and its challenges: From statistical modeling to deep learning
B Sisman, J Yamagishi, S King, H Li
IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 132-157, 2021
2822021
Seen and unseen emotional style transfer for voice conversion with a new emotional speech dataset
K Zhou, B Sisman, R Liu, H Li
IEEE ICASSP 2021 International Conference on Acoustics, Speech, and Signal …, 2021
1462021
Emotional Voice Conversion: Theory, Databases and ESD
K Zhou, B Sisman, R Liu, H Li
Speech Communication, 2022
1042022
VQVAE Unsupervised Unit Discovery and Multi-scale Code2Spec Inverter for Zerospeech Challenge 2019
A Tjandra, B Sisman, M Zhang, S Sakti, H Li, S Nakamura
Proc. Interspeech 2019, 2019
812019
Expressive TTS Training with Frame and Style Reconstruction Loss
R Liu, B Sisman, G Gao, H Li
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2021
762021
Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training Data
K Zhou, B Sisman, H Li
Proc. Odyssey 2020, Tokyo, Japan, 2020
722020
Teacher-Student Training for Robust Tacotron-based TTS
R Liu, B Sisman, J Li, F Bao, G Gao, H Li
IEEE ICASSP 2020 International Conference on Acoustics, Speech, and Signal …, 2020
642020
A voice conversion framework with tandem feature sparse representation and speaker-adapted wavenet vocoder
B Sisman, M Zhang, H Li
Proc. Interspeech, 1978 -1982, 2018
592018
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion
K Zhou, B Sisman, M Zhang, H Li
Proc. Interspeech 2020, 2020
502020
Group sparse representation with wavenet vocoder adaptation for spectrum and prosody conversion
B Sisman, M Zhang, H Li
IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (6), 1085 …, 2019
502019
Sparse representation of phonetic features for voice conversion with and without parallel data
B Sisman, H Li, KC Tan
Automatic Speech Recognition and Understanding Workshop (ASRU), 2017 IEEE …, 2017
482017
Adaptive Wavenet Vocoder for Residual Compensation in GAN-based Voice Conversion
B Sisman, M Zhang, S Sakti, H Li, S Nakamura
2018 IEEE Spoken Language Technology Workshop (SLT), 282-289, 2018
452018
SINGAN: Singing voice conversion with generative adversarial networks
B Sisman, K Vijayan, M Dong, H Li
Asia-Pacific Signal and Information Processing Association Annual Summit and …, 2019
432019
Transformation of prosody in voice conversion
B Sisman, H Li, KC Tan
Asia-Pacific Signal and Information Processing Association Annual Summit and …, 2017
372017
Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability
R Liu, B Sisman, H Li
INTERSPEECH 2021, 2021
342021
VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech
K Zhou, B Sisman, H Li
2021 IEEE Spoken Language Technology Workshop (SLT 2021), 2021
342021
On the study of Generative Adversarial Networks for Cross-lingual Voice Conversion
B Sisman, M Zhang, M Dong, H Li
IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 2019, 2019
342019
Emotion Intensity and its Control for Emotional Voice Conversion
K Zhou, B Sisman, R Rana, BW Schuller, H Li
IEEE Transactions on Affective Computing, 2023
332023
GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis
R Liu, B Sisman, H Li
IEEE ICASSP 2021 International Conference on Acoustics, Speech, and Signal …, 2021
312021
Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence Training
K Zhou, B Sisman, H Li
INTERSPEECH 2021, 2021
302021
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