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Berrak Sisman
Berrak Sisman
Electrical & Computer Engineering Department, The University of Texas at Dallas
Verified email at utdallas.edu - Homepage
Title
Cited by
Cited by
Year
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
2762021
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
1422021
Emotional Voice Conversion: Theory, Databases and ESD
K Zhou, B Sisman, R Liu, H Li
Speech Communication, 2022
962022
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
822019
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
742021
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
682020
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
632020
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
612018
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
492019
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
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion
K Zhou, B Sisman, M Zhang, H Li
Proc. Interspeech 2020, 2020
462020
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
462018
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
422019
Transformation of prosody in voice conversion
B Sisman, H Li, KC Tan
Asia-Pacific Signal and Information Processing Association Annual Summit and …, 2017
362017
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
352019
Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability
R Liu, B Sisman, H Li
INTERSPEECH 2021, 2021
322021
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
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
312021
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
302023
Wavelet Analysis of Speaker Dependent and Independent Prosody for Voice Conversion
B Sisman, H Li
Proc. Interspeech, 52-56, 2018
282018
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