Audio Denoising
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Benchmarks
Most implemented
Co-Separating Sounds of Visual Objects
Speech Denoising Without Clean Training Data: A Noise2Noise Approach
Learning to Separate Object Sounds by Watching Unlabeled Video
Complex Image Generation SwinTransformer Network for Audio Denoising
The Intel Neuromorphic DNS Challenge
Papers
Scalable Operator Learning via Nyström Approximation With Denoising Applications
In this paper, we study Nyström subsampling for vector-valued regression in vector-valued reproducing kernel Hilbert spaces. Standard kernel methods often suffer from prohibitive computational costs due to the constructi…
Image DenoisingAudio DenoisingAutomatic Contextual Audio Denoising
Audio context determines which sound components and sources are relevant and which can be perceived as irrelevant (noise) by listeners. For example, traffic noise is informative in urban surveillance but noise for a phon…
Audio DenoisingCan Multimodal Large Language Models Understand Pathologic Movements? A Pilot Study on Seizure Semiology
Multimodal Large Language Models (MLLMs) have demonstrated robust capabilities in recognizing everyday human activities, yet their potential for analyzing clinically significant involuntary movements in neurological diso…
Audio DenoisingPose EstimationSEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models
Large Audio Language Models (LALMs) have been widely applied in real-time scenarios, such as in-car assistants and online meeting comprehension. In practice, audio inputs are often corrupted by device and environmental n…
Audio DenoisingADNAC: Audio Denoiser using Neural Audio Codec
Audio denoising is critical in signal processing, enhancing intelligibility and fidelity for applications like restoring musical recordings. This paper presents a proof-of-concept for adapting a state-of-the-art neural a…
Audio DenoisingOn the Contribution of Lexical Features to Speech Emotion Recognition
Although paralinguistic cues are often considered the primary drivers of speech emotion recognition (SER), we investigate the role of lexical content extracted from speech and show that it can achieve competitive and in …
Speech Emotion RecognitionAudio Denoising