VoiceBank-DEMAND
Emerging52papers using it
2022first seen
VoiceBank-DEMAND is a dataset used to evaluate speech quality by providing diverse audio samples with corresponding perceptual mean opinion scores (MOS).
Papers using VoiceBank-DEMAND (48)
- Mp-senet: A Speech Enhancement Model With Parallel Denoising Of Magnitude And Phase SpectraInvestigating Self-supervised Learning For Speech Enhancement And SeparationA Multi-dimensional Deep Structured State Space Approach To Speech Enhancement Using Small-footprint ModelsExploiting Consistency-preserving Loss And Perceptual Contrast Stretching To Boost Ssl-based Speech EnhancementPrimeK-Net: Multi-scale Spectral Learning via Group Prime-Kernel
Convolutional Neural Networks for Single Channel Speech EnhancementSingle-channel Speech Enhancement With Deep Complex U-networks And Probabilistic Latent Space ModelsZipenhancer: Dual-path Down-up Sampling-based Zipformer For Monaural Speech EnhancementBSS-CFFMA: Cross-domain Feature Fusion And Multi-attention Speech Enhancement Network Based On Self-supervised EmbeddingZipEnhancer: Dual-Path Down-Up Sampling-based Zipformer for Monaural
Speech EnhancementPosterior Transition Modeling for Unsupervised Diffusion-Based Speech EnhancementMagnitude-phase Dual-path Speech Enhancement Network Based On Self-supervised Embedding And Perceptual Contrast Stretch BoostingxLSTM-SENet: xLSTM for Single-Channel Speech EnhancementEffective Noise-aware Data Simulation For Domain-adaptive Speech Enhancement Leveraging Dynamic Stochastic PerturbationMagnitude-Phase Dual-Path Speech Enhancement Network based on
Self-Supervised Embedding and Perceptual Contrast Stretch BoostingFew-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language ModelsSpeech Enhancement Based on Drifting ModelsDiffusion-based Frameworks for Unsupervised Speech EnhancementBeyond Performance: Probing Representation Dynamics In Speech Enhancement ModelsI-DCCRN-VAE: An Improved Deep Representation Learning Framework for Complex VAE-based Single-channel Speech EnhancementMeanFlowSE: one-step generative speech enhancement via conditional mean flowInvestigation of Speech and Noise Latent Representations in Single-channel VAE-based Speech EnhancementEffiFusion-GAN: Efficient Fusion Generative Adversarial Network for Speech EnhancementRobust One-step Speech Enhancement via Consistency DistillationDo We Need EMA for Diffusion-Based Speech Enhancement? Toward a Magnitude-Preserving Network ArchitectureaTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw AudioMUSE: Flexible Voiceprint Receptive Fields And Multi-path Fusion Enhanced Taylor Transformer For U-net-based Speech EnhancementThlnet: Two-stage Heterogeneous Lightweight Network For Monaural Speech EnhancementA Neural Denoising Vocoder For Clean Waveform Generation From Noisy Mel-spectrogram Based On Amplitude And Phase PredictionsA General Unfolding Speech Enhancement Method Motivated by Taylor's
TheoremMP-SENet: A Speech Enhancement Model with Parallel Denoising of
Magnitude and Phase SpectraSCP-GAN: Self-Correcting Discriminator Optimization for Training
Consistency Preserving Metric GAN on Speech Enhancement TasksDiffusion-based Generative Speech Source SeparationTHLNet: two-stage heterogeneous lightweight network for monaural speech
enhancementA Multi-dimensional Deep Structured State Space Approach to Speech
Enhancement Using Small-footprint ModelsAn Investigation of Incorporating Mamba for Speech EnhancementSpeech enhancement deep-learning architecture for efficient edge
processingBSS-CFFMA: Cross-Domain Feature Fusion and Multi-Attention Speech
Enhancement Network based on Self-Supervised EmbeddingTridentSE: Guiding Speech Enhancement with 32 Global TokensCold Diffusion for Speech EnhancementEfficient Monaural Speech Enhancement using Spectrum Attention FusionSpiking Structured State Space Model for Monaural Speech EnhancementMUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion
Enhanced Taylor Transformer for U-Net-based Speech EnhancementExploiting Consistency-Preserving Loss and Perceptual Contrast
Stretching to Boost SSL-based Speech EnhancementEffective Noise-aware Data Simulation for Domain-adaptive Speech
Enhancement Leveraging Dynamic Stochastic PerturbationSpeech-Declipping Transformer with Complex Spectrogram and Learnerble
Temporal FeaturesA Neural Denoising Vocoder for Clean Waveform Generation from Noisy
Mel-Spectrogram based on Amplitude and Phase PredictionsFrom KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based MethodologySingle-Channel Speech Enhancement with Deep Complex U-Networks and
Probabilistic Latent Space Models