• Refine your search:
  • 
    Keyword:
    
    • FOS Computer and information sciences (8)
    • Audio and Speech Processing eess.AS (7)
    • Computation and Language cs.CL (7)
    • FOS Electrical engineering, electronic engineering, information engineering (7)
    • Sound cs.SD (7)
    • Computational Linguistics (2)
    • Artificial Intelligence cs.AI (1)
    • Condensed Matter Physics (1)
    • Deep Learning (1)
    • Electromagnetism (1)
    •   more
  • 
    Creator / Publisher
  • 
    Year:
    
    • 2022 (1)
    • 2021 (4)
    • 2020 (5)
  • 
    Medium:
    
    • Online (10)
  • 
    Type
  • 
    BLLDB-Access

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 Emotion Intensity and its Control for Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Rana, Rajib. - : arXiv, 2022 BASE Show details 2 Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence Training ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2021 BASE Show details 3 Identity Conversion for Emotional Speakers: A Study for Disentanglement of Emotion Style and Speaker Identity ... Du, Zongyang; Sisman, Berrak; Zhou, Kun. - : arXiv, 2021 BASE Show details 4 CRSLab: An Open-Source Toolkit for Building Conversational Recommender System ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cheng, Yuan; Li, Yaliang. - : Underline Science Inc., 2021 BASE Show details 5 Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Zhou, Kun. - : Underline Science Inc., 2021 BASE Show details 6 VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2020 BASE Show details 7 Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset ... Zhou, Kun; Sisman, Berrak; Liu, Rui. - : arXiv, 2020 BASE Show details 8 Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Zhang, Mingyang. - : arXiv, 2020 BASE Show details 9 Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training Data ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2020 Abstract: Emotional voice conversion aims to convert the spectrum and prosody to change the emotional patterns of speech, while preserving the speaker identity and linguistic content. Many studies require parallel speech data between different emotional patterns, which is not practical in real life. Moreover, they often model the conversion of fundamental frequency (F0) with a simple linear transform. As F0 is a key aspect of intonation that is hierarchical in nature, we believe that it is more adequate to model F0 in different temporal scales by using wavelet transform. We propose a CycleGAN network to find an optimal pseudo pair from non-parallel training data by learning forward and inverse mappings simultaneously using adversarial and cycle-consistency losses. We also study the use of continuous wavelet transform (CWT) to decompose F0 into ten temporal scales, that describes speech prosody at different time resolution, for effective F0 conversion. Experimental results show that our proposed framework outperforms ... : accepted by Speaker Odyssey 2020 in Tokyo, Japan ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://arxiv.org/abs/2002.00198 https://dx.doi.org/10.48550/arxiv.2002.00198 BASE Hide details 10 VAW-GAN for Singing Voice Conversion with Non-parallel Training Data ... Lu, Junchen; Zhou, Kun; Sisman, Berrak. - : arXiv, 2020 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 10 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0