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08/31/2023
Improving Small Footprint Few-shot Keyword Spotting with Supervision on Auxiliary Data
Few-shot keyword spotting (FS-KWS) models usually require large-scale an...
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08/17/2023
Label Shift Adapter for Test-Time Adaptation under Covariate and Label Shifts
Test-time adaptation (TTA) aims to adapt a pre-trained model to the targ...
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04/02/2023
Progressive Random Convolutions for Single Domain Generalization
Single domain generalization aims to train a generalizable model with on...
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02/26/2023
Scalable Weight Reparametrization for Efficient Transfer Learning
This paper proposes a novel, efficient transfer learning method, called ...
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07/24/2022
Improving Test-Time Adaptation via Shift-agnostic Weight Regularization and Nearest Source Prototypes
This paper proposes a novel test-time adaptation strategy that adjusts t...
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06/28/2022
QTI Submission to DCASE 2021: residual normalization for device-imbalanced acoustic scene classification with efficient design
This technical report describes the details of our TASK1A submission of ...
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06/28/2022
Personalized Keyword Spotting through Multi-task Learning
Keyword spotting (KWS) plays an essential role in enabling speech-based ...
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06/28/2022
Domain Agnostic Few-shot Learning for Speaker Verification
Deep learning models for verification systems often fail to generalize t...
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06/28/2022
Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spotting
Keyword spotting is the task of detecting a keyword in streaming audio. ...
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06/24/2022
Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification
While using two-dimensional convolutional neural networks (2D-CNNs) in i...
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11/24/2021
Distribution Estimation to Automate Transformation Policies for Self-Supervision
In recent visual self-supervision works, an imitated classification obje...
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11/12/2021
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization
It is a practical research topic how to deal with multi-device audio inp...
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12/03/2020
Robust Federated Learning with Noisy Labels
Federated learning is a paradigm that enables local devices to jointly t...
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10/06/2020
Arbitrary Style Transfer using Graph Instance Normalization
Style transfer is the image synthesis task, which applies a style of one...
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08/07/2020
Associative Partial Domain Adaptation
Partial Adaptation (PDA) addresses a practical scenario in which the tar...
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05/16/2020
Partial Domain Adaptation Using Graph Convolutional Networks
Partial domain adaptation (PDA), in which we assume the target label spa...
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10/12/2019