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Found 11 papers, 1 papers with code
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction
The meaning of a word in Chinese is different in that a word is a compositional unit consisting of multiple characters.
High Quality Audio Coding with MDCTNet
We propose a neural audio generative model, MDCTNet, operating in the perceptually weighted domain of an adaptive modified discrete cosine transform (MDCT).
Effidit: Your AI Writing Assistant
In Effidit, we significantly expand the capacities of a writing assistant by providing functions in five categories: text completion, error checking, text polishing, keywords to sentences (K2S), and cloud input methods (cloud IME).
One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code
Moreover, our model supports self-supervised pretraining with the same sparsely activated way, resulting in better initialized parameters for different modalities.
Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors
We achieve this by introducing a special token \texttt{[null]}, the prediction of which stands for the non-existence of a word.
SkillNet-NLU: A Sparsely Activated Model for General-Purpose Natural Language Understanding
The key feature of our approach is that it is sparsely activated guided by predefined skills.
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction
The meaning of a word in Chinese is different in that a word is a compositional unit consisting of multiple characters.
Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words
(2) how to predict a word via cloze test without knowing the number of wordpieces in advance?
Deep Performer: Score-to-Audio Music Performance Synthesis
Music performance synthesis aims to synthesize a musical score into a natural performance.
GUDN: A novel guide network with label reinforcement strategy for extreme multi-label text classification
Large-scale pre-trained models have brought a new trend to this problem.
Voice Conversion with Conditional SampleRNN
Here we present a novel approach to conditioning the SampleRNN generative model for voice conversion (VC).
