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Found 8 papers, 1 papers with code
Cross-lingual Knowledge Distillation via Flow-based Voice Conversion for Robust Polyglot Text-To-Speech
In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker.
Multimodal Brain Disease Classification with Functional Interaction Learning from Single fMRI Volume
The low representation ability of FC leads to poor performance in clinical practice, especially when dealing with multimodal medical data involving multiple types of visual signals and textual records for brain diseases.
Mix and Match: An Empirical Study on Training Corpus Composition for Polyglot Text-To-Speech (TTS)
Training multilingual Neural Text-To-Speech (NTTS) models using only monolingual corpora has emerged as a popular way for building voice cloning based Polyglot NTTS systems.
Unify and Conquer: How Phonetic Feature Representation Affects Polyglot Text-To-Speech (TTS)
In this paper, we conduct a comprehensive study comparing multilingual NTTS systems models trained with both representations.
PARCEL: Physics-based Unsupervised Contrastive Representation Learning for Multi-coil MR Imaging
However, in the absence of high-quality, fully sampled datasets for training, the performance of these methods is limited.
State Action Separable Reinforcement Learning
We observe that although actions directly define the agents' behaviors, for many problems the next state after a state transition matters more than the action taken, in determining the return of such a state transition.
Neural Network Tomography
Network tomography, a classic research problem in the realm of network monitoring, refers to the methodology of inferring unmeasured network attributes using selected end-to-end path measurements.
MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design
In distributed software-defined networks (SDN), multiple physical SDN controllers, each managing a network domain, are implemented to balance centralised control, scalability, and reliability requirements.
