The article introduces DODUO, a method to learn general dense visual correspondence from in-the-wild images and videos without ground truth supervision. Dense visual correspondence plays a critical role in robotic…
Continue readingThe article discusses the development of Fast-HuBERT, an efficient training framework for self-supervised learning (SSL) models for speech recognition. The authors address the high computational cost of existing SSL models,…
Continue readingThe article focuses on Speech Emotion Recognition (SER), an essential tool in enhancing human-computer interaction by understanding emotional states. The authors propose a novel approach that combines self-supervised feature extraction…
Continue readingThis study examines the effectiveness of audio augmentation in improving self-supervised representation learning (SSRL) models for low resource languages. The researchers compared different augmentation techniques such as pitch variation, noise…
Continue readingThe study introduces a self-supervised approach to visual acoustic matching, aiming to improve the experience of audio perception in diverse spaces. By learning to disentangle room acoustics and re-synthesize audio…
Continue readingThis paper presents a self-supervised sensorimotor pre-training approach for robotics. The authors propose a model, called RPT (Robot Pre-training Transformer), that operates on sequences of sensorimotor tokens. The model is…
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