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8 Publications
2024 | Conference Paper | LibreCat-ID: 57099
Y. Xie, M. Kuhlmann, F. Rautenberg, Z.-H. Tan, and R. Häb-Umbach, “Speaker and Style Disentanglement of Speech Based on Contrastive Predictive Coding Supported Factorized Variational Autoencoder,” in 2024 32nd European Signal Processing Conference (EUSIPCO), 2024, pp. 436–440.
LibreCat
2023 | Conference Paper | LibreCat-ID: 48355 | 
F. Rautenberg, M. Kuhlmann, J. Wiechmann, F. Seebauer, P. Wagner, and R. Haeb-Umbach, “On Feature Importance and Interpretability of Speaker Representations,” presented at the ITG Conference on Speech Communication, Aachen, 2023.
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| arXiv
2023 | Conference Paper | LibreCat-ID: 46069
F. Seebauer, M. Kuhlmann, R. Haeb-Umbach, and P. Wagner, “Re-examining the quality dimensions of synthetic speech,” 2023.
LibreCat
2023 | Conference Paper | LibreCat-ID: 44849 |
F. Rautenberg et al., “Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics,” in Fortschritte der Akustik - DAGA 2023, Hamburg, 2023, pp. 1409–1412.
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2023 | Conference Paper | LibreCat-ID: 57098
F. Seebauer, M. Kuhlmann, R. Häb-Umbach, and P. Wagner, “DISCERNING DIMENSIONS OF QUALITY FOR STATE OF THE ART SYNTHETIC SPEECH,” presented at the International Congress of Phonetic Sciences (ICPhS), Prague, 2023.
LibreCat
2023 | Conference Paper | LibreCat-ID: 57086
M. Kuhlmann, A. Meise, F. Seebauer, P. Wagner, and R. Häb-Umbach, “Investigating Speaker Embedding Disentanglement on Natural Read Speech,” in Speech Communication; 15th ITG Conference, 2023, pp. 121–125.
LibreCat
2022 | Conference Paper | LibreCat-ID: 33857 |
M. Kuhlmann, F. Seebauer, J. Ebbers, P. Wagner, and R. Haeb-Umbach, “Investigation into Target Speaking Rate Adaptation for Voice Conversion,” 2022, doi: 10.21437/interspeech.2022-10740.
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2021 | Conference Paper | LibreCat-ID: 29304 |
J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, and R. Haeb-Umbach, “Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 3860–3864.
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