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Disambiguation of "Ling, Zhen-Hua"

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Asynchronous F0 and spectrum modeling for HMM-based speech synthesis.

, , and . INTERSPEECH, page 404-407. ISCA, (2009)

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Dr. -Ing. Ling He University of Stuttgart

Haoyu Zheng University of Stuttgart

Dr. rer. nat. Shiang-Yu Huang University of Stuttgart

Jianshu Zheng University of Stuttgart

Jingjing Huang University of Stuttgart

 

Other publications of authors with the same name

Spectral conversion using deep neural networks trained with multi-source speakers., , , and . ICASSP, page 4849-4853. IEEE, (2015)Concept-to-Speech generation with knowledge sharing for acoustic modelling and utterance filtering., , and . Computer Speech & Language, (2016)Mage - reactive articulatory feature control of HMM-based parametric speech synthesis., , , , , , and . SSW, page 207-211. ISCA, (2013)Minimum Kullback-Leibler Divergence Parameter Generation for HMM-Based Speech Synthesis., and . IEEE Trans. Audio, Speech & Language Processing, 20 (5): 1492-1502 (2012)Articulatory Control of HMM-Based Parametric Speech Synthesis Using Feature-Space-Switched Multiple Regression., , and . IEEE Trans. Audio, Speech & Language Processing, 21 (1): 205-217 (2013)Emotional Speech Synthesis Based on Improved Codebook Mapping Voice Conversion., , and . ACII, volume 3784 of Lecture Notes in Computer Science, page 374-381. Springer, (2005)Combing Context and Commonsense Knowledge Through Neural Networks for Solving Winograd Schema Problems., , , , , and . AAAI Spring Symposia, AAAI Press, (2017)Question Answering with Character-Level LSTM Encoders and Model-Based Data Augmentation., , and . CCL, volume 10565 of Lecture Notes in Computer Science, page 295-305. Springer, (2017)Cause-Effect Knowledge Acquisition and Neural Association Model for Solving A Set of Winograd Schema Problems., , , , , , and . IJCAI, page 2344-2350. ijcai.org, (2017)Learning Semantic Word Embeddings based on Ordinal Knowledge Constraints., , , , and . ACL (1), page 1501-1511. The Association for Computer Linguistics, (2015)