Browse State-of-the-Art › Speech Enhancement

Speech Enhancement

280 papers with code · 17 benchmarks · 24 datasets archive 2025-07-28

AudioSpeech

Speech Enhancement is a signal processing task that involves improving the quality of speech signals captured under noisy or degraded conditions. The goal of speech enhancement is to make speech signals clearer, more intelligible, and more pleasant to listen to, which can be used for various applications such as voice recognition, teleconferencing, and hearing aids. A representative Github project with online demo : ClearerVoice-Studio.

( Image credit: A Fully Convolutional Neural Network For Speech Enhancement )

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

18 leaderboard tables shown for this task, 17 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 18 until expanded.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
VoiceBank + DEMAND (42 rows) ROSE-CD(PESQ) Robust One-step Speech Enhancement via Consistency Distillation code — Compare
Deep Noise Suppression (DNS) Challenge (36 rows) ZipEnhancer (M) — — — Compare
CHiME-3 (6 rows) Inter-Channel Conv-TasNet Inter-channel Conv-TasNet for multichannel speech enhancement — — Compare
EARS-WHAM (6 rows) Schrödinger Bridge (PESQ loss) Investigating Training Objectives for Generative Speech Enhancement code — Compare
EasyCom (6 rows) MaxDI (Baseline) EasyCom: An Augmented Reality Dataset to Support Algorithms for... code — Compare
DNS Challenge (5 rows) ZipEnhancer (M) — — — Compare
VB-DemandEx (4 rows) MambAttention MambAttention: Mamba with Multi-Head Attention for Generalizable... code — Compare
WHAMR! (4 rows) SepFormer Exploring Self-Attention Mechanisms for Speech Separation code — Compare
WSJ0 + DEMAND + RNNoise (3 rows) DCUNet-MC Monaural Speech Enhancement with Complex Convolutional Block... code — Compare
RealMAN (2 rows) CleanMel-L-map CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech... code — Compare
VoiceBank+DEMAND (2 rows) ROSE-CD Robust One-step Speech Enhancement via Consistency Distillation code — Compare
DEMAND (1 row) Wave-U-Net Improved Speech Enhancement with the Wave-U-Net code — Compare
GRID corpus (mixed-speech) (1 row) Audio-Visual concat-ref Face Landmark-based Speaker-Independent Audio-Visual Speech... code — Compare
LibriSpeechDuplicate (1 row) SE-MelGAN SE-MelGAN -- Speaker Agnostic Rapid Speech Enhancement — — Compare
spatialized DNS challenge (1 row) DeFT-AN DeFT-AN: Dense Frequency-Time Attentive Network for Multichannel... code — Compare
TCD-TIMIT corpus (mixed-speech) (1 row) Audio-Visual concat-ref Face Landmark-based Speaker-Independent Audio-Visual Speech... code — Compare
WHAM! (1 row) SepFormer Exploring Self-Attention Mechanisms for Speech Separation code — Compare
DNS-4 (0 rows) no rows in the archive — —

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

24 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

4 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 280 papers with code (982 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

Syntology lines on 16 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.

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