Search Results for author:
Found 7 papers, 1 papers with code
Predictive Sparse Manifold Transform
PSMT incorporates two layers where the first sparse coding layer represents the input sequence as sparse coefficients over an overcomplete dictionary and the second manifold learning layer learns a geometric embedding space that captures topological similarity and dynamic temporal linearity in sparse coefficients.
Adaptive Texture Filtering for Single-Domain Generalized Segmentation
Domain generalization in semantic segmentation aims to alleviate the performance degradation on unseen domains through learning domain-invariant features.
Pipeline-Invariant Representation Learning for Neuroimaging
We next propose two pipeline-invariant representation learning methodologies, MPSL and PXL, to improve robustness in classification performance and to capture similar neural network representations.
WeSinger: Data-augmented Singing Voice Synthesis with Auxiliary Losses
To improve the accuracy and naturalness of synthesized singing voice, we design several specifical modules and techniques: 1) A deep bi-directional LSTM-based duration model with multi-scale rhythm loss and post-processing step; 2) A Transformer-alike acoustic model with progressive pitch-weighted decoder loss; 3) a 24 kHz pitch-aware LPCNet neural vocoder to produce high-quality singing waveforms; 4) A novel data augmentation method with multi-singer pre-training for stronger robustness and naturalness.
Nana-HDR: A Non-attentive Non-autoregressive Hybrid Model for TTS
Thirdly, a duration predictor instead of an attention model that connects the above hybrid encoder and decoder.
Triple M: A Practical Text-to-speech Synthesis System With Multi-guidance Attention And Multi-band Multi-time LPCNet
In this work, a robust and efficient text-to-speech (TTS) synthesis system named Triple M is proposed for large-scale online application.
Device-independent verification of Einstein-Podolsky-Rosen steering
We first establish the DI verification framework, relying on the measurement-device-independent technique and self-testing, and show it is able to verify all EPR-steerable states.
Quantum Physics
