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Found 6 papers, 1 papers with code
MaskMatch: Boosting Semi-Supervised Learning Through Mask Autoencoder-Driven Feature Learning
To overcome this limitation and improve SSL performance, we introduce \algo, a novel algorithm that fully utilizes unlabeled data to boost semi-supervised learning.
Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models
Automated speaker identification (SID) is a crucial step for the personalization of a wide range of speech-enabled services.
Improving Label Assignments Learning by Dynamic Sample Dropout Combined with Layer-wise Optimization in Speech Separation
Despite its success, previous studies showed that PIT is plagued by excessive label assignment switching in adjacent epochs, impeding the model to learn better label assignments.
Self-supervised speech representation learning for keyword-spotting with light-weight transformers
Self-supervised speech representation learning (S3RL) is revolutionizing the way we leverage the ever-growing availability of data.
Progressive Learning for Stabilizing Label Selection in Speech Separation with Mapping-based Method
We investigate the use of the mapping-based method in the time domain and show that it can perform better on a large training set than the masking-based method.
Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search
Secondly, a BERT with locality-constrained attention is proposed to obtain representations of descriptions at different scales.
Ranked #15 on
Text based Person Retrieval
on CUHK-PEDES
