Papers Audio Denoising
“Audio Denoising” 태그가 달린 논문 26편 · 필터 해제
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 DenoisingAccelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Linear recurrent neural networks enable powerful long-range sequence modeling with constant memory usage and time-per-token during inference. These architectures hold promise for streaming applications at the edge, but d…
Audio DenoisingDenoisingGPUModel CompressionCleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning
This paper presents CleanUMamba, a time-domain neural network architecture designed for real-time causal audio denoising directly applied to raw waveforms. CleanUMamba leverages a U-Net encoder-decoder structure, incorpo…
Audio DenoisingDecoderDenoisingMamba+1aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio
We present aTENNuate, a simple deep state-space autoencoder configured for efficient online raw speech enhancement in an end-to-end fashion. The network's performance is primarily evaluated on raw speech denoising, with …
Audio DenoisingDenoisingSpeech DenoisingSpeech Enhancement+1Diffusion Gaussian Mixture Audio Denoise
Recent diffusion models have achieved promising performances in audio-denoising tasks. The unique property of the reverse process could recover clean signals. However, the distribution of real-world noises does not compl…
Audio DenoisingDenoisingComplex Image Generation SwinTransformer Network for Audio Denoising
Achieving high-performance audio denoising is still a challenging task in real-world applications. Existing time-frequency methods often ignore the quality of generated frequency domain images. This paper converts the au…
Audio DenoisingDenoisingImage GenerationEfficient Video and Audio processing with Loihi 2
Loihi 2 is an asynchronous, brain-inspired research processor that generalizes several fundamental elements of neuromorphic architecture, such as stateful neuron models communicating with event-driven spikes, in order to…
Audio DenoisingDenoisingLearning Spatial Features from Audio-Visual Correspondence in Egocentric Videos
We propose a self-supervised method for learning representations based on spatial audio-visual correspondences in egocentric videos. Our method uses a masked auto-encoding framework to synthesize masked binaural (multi-c…
Active Speaker DetectionAudio DenoisingDenoisingThe Intel Neuromorphic DNS Challenge
A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutio…
Audio DenoisingDenoisingAudio Denoising for Robust Audio Fingerprinting
Music discovery services let users identify songs from short mobile recordings. These solutions are often based on Audio Fingerprinting, and rely more specifically on the extraction of spectral peaks in order to be robus…
Audio DenoisingData AugmentationDenoisingBirdSoundsDenoising: Deep Visual Audio Denoising for Bird Sounds
Audio denoising has been explored for decades using both traditional and deep learning-based methods. However, these methods are still limited to either manually added artificial noise or lower denoised audio quality. To…
Audio DenoisingDenoisingImage SegmentationNoise Estimation+2Self-Supervised Speech Denoising Using Only Noisy Audio Signals
In traditional speech denoising tasks, clean audio signals are often used as the training target, but absolutely clean signals are collected from expensive recording equipment or in studios with the strict environments. …
Audio DenoisingDenoisingSpeech DenoisingSelf-Supervised Inference in State-Space Models
We perform approximate inference in state-space models with nonlinear state transitions. Without parameterizing a generative model, we apply Bayesian update formulas using a local linearity approximation parameterized by…
Audio DenoisingDenoisingState Space ModelsVariational InferenceAudio Attacks and Defenses against AED Systems -- A Practical Study
In this paper, we evaluate deep learning-enabled AED systems against evasion attacks based on adversarial examples. We test the robustness of multiple security critical AED tasks, implemented as CNNs classifiers, as well…
Audio DenoisingDenoisingEvent Detectionspeech-recognition+1On the Design of Deep Priors for Unsupervised Audio Restoration
Unsupervised deep learning methods for solving audio restoration problems extensively rely on carefully tailored neural architectures that carry strong inductive biases for defining priors in the time or spectral domain.…
Audio DenoisingDenoising