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Found 6 papers, 2 papers with code
Disentangling Prosody Representations with Unsupervised Speech Reconstruction
Human speech can be characterized by different components, including semantic content, speaker identity and prosodic information.
Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models
Conventional fine-tuning encounters increasing difficulties given the size of current Pre-trained Language Models, which makes parameter-efficient tuning become the focal point of frontier research.
Data Augmentation with Unsupervised Speaking Style Transfer for Speech Emotion Recognition
Once training is completed, EmoAug enriches expressions of emotional speech in different prosodic attributes, such as stress, rhythm and intensity, by feeding different styles into the paralinguistic encoder.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Twin Contrastive Learning for Online Clustering
Specifically, we find that when the data is projected into a feature space with a dimensionality of the target cluster number, the rows and columns of its feature matrix correspond to the instance and cluster representation, respectively.
Ranked #1 on
Short Text Clustering
on Biomedical
Learning With Twin Noisy Labels for Visible-Infrared Person Re-Identification
To solve the TNL problem, we propose a novel method for robust VI-ReID, termed DuAlly Robust Training (DART).
Fast sensor placement by enlarging principle submatrix for large-scale linear inverse problems
Sensor placement for linear inverse problems is the selection of locations to assign sensors so that the entire physical signal can be well recovered from partial observations.
