SOTAVerified

Audio Generation

Audio generation (synthesis) is the task of generating raw audio such as speech.

( Image credit: MelNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 270 papers

TitleStatusHype
DiffAVA: Personalized Text-to-Audio Generation with Visual Alignment—0
DiffGAP: A Lightweight Diffusion Module in Contrastive Space for Bridging Cross-Model Gap—0
Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models—0
Discrete Optimal Transport and Voice Conversion—0
DPN-GAN: Inducing Periodic Activations in Generative Adversarial Networks for High-Fidelity Audio Synthesis—0
DualSpec: Text-to-spatial-audio Generation via Dual-Spectrogram Guided Diffusion Model—0
Efficient Parallel Audio Generation using Group Masked Language Modeling—0
ELLA-V: Stable Neural Codec Language Modeling with Alignment-guided Sequence Reordering—0
Enhance audio generation controllability through representation similarity regularization—0
EnvSDD: Benchmarking Environmental Sound Deepfake Detection—0
Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation—0
EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer—0
FastWave: Accelerating Autoregressive Convolutional Neural Networks on FPGA—0
FlexLip: A Controllable Text-to-Lip System—0
Foley-Flow: Coordinated Video-to-Audio Generation with Masked Audio-Visual Alignment and Dynamic Conditional Flows—0
FoleyGen: Visually-Guided Audio Generation—0
FreeAudio: Training-Free Timing Planning for Controllable Long-Form Text-to-Audio Generation—0
Geometry-Aware Multi-Task Learning for Binaural Audio Generation from Video—0
Guided Generative Adversarial Neural Network for Representation Learning and High Fidelity Audio Generation using Fewer Labelled Audio Data—0
High-Fidelity Audio Generation and Representation Learning with Guided Adversarial Autoencoder—0
IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling—0
In-Context Prompt Editing For Conditional Audio Generation—0
Incremental Text to Speech for Neural Sequence-to-Sequence Models using Reinforcement Learning—0
InfiniteAudio: Infinite-Length Audio Generation with Consistency—0
IteraTTA: An interface for exploring both text prompts and audio priors in generating music with text-to-audio models—0
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All datasetsAudioCapsClassical music, 5 seconds at 12 kHzSymphony music

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AudioGenFD_openl3185.53—Unverified
2AudioLDM2-largeFD_openl3158.04—Unverified
3Stable Audio 2.0FD_openl3110.62—Unverified
4Stable AudioFD_openl3103.66—Unverified
5ETTAFD_openl380.13—Unverified
6TangoFlux-baseFD_openl379.7—Unverified
7Stable Audio OpenFD_openl378.24—Unverified
8TangoFluxFD_openl375.1—Unverified
9ETTA-FT-AC-100kFD_openl361.79—Unverified
10DiffsoundFAD7.75—Unverified
#ModelMetricClaimedVerifiedStatus
1VAB-Encodec (Ours)Bits per byte40—Unverified
2Sparse Transformer 152M (strided)Bits per byte1.97—Unverified
#ModelMetricClaimedVerifiedStatus
1SymphonyNet Human listening average results3.5—Unverified