# A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech

arXiv: https://arxiv.org/abs/2008.04259 · HTML: https://mlsanity.com/paper/2008.04259/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Aug 2020.

## Built on by (most cited first, 23 of 23)

- [DeepFilterNet: A Low Complexity Speech Enhancement Framework for Full-Band Audio based on Deep Filtering](https://mlsanity.com/paper/2110.05588/) (2021)
- [DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement](https://mlsanity.com/paper/2305.08227/) (2023)
- [DeepFilterNet2: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio](https://mlsanity.com/paper/2205.05474/) (2022)
- [Accelerating RNN-based Speech Enhancement on a Multi-Core MCU with Mixed FP16-INT8 Post-Training Quantization](https://mlsanity.com/paper/2210.07692/) (2022)
- [Diffusion-based Speech Enhancement with Schr"odinger Bridge and Symmetric Noise Schedule](https://mlsanity.com/paper/2409.05116/) (2024)
- [Ultra Low Complexity Deep Learning Based Noise Suppression](https://mlsanity.com/paper/2312.08132/) (2023)
- [Perceptual Contrast Stretching on Target Feature for Speech Enhancement](https://mlsanity.com/paper/2203.17152/) (2022)
- [Scalable and Efficient Neural Speech Coding: A Hybrid Design](https://mlsanity.com/paper/2103.14776/) (2021)
- [Adaptive Slimming for Scalable and Efficient Speech Enhancement](https://mlsanity.com/paper/2507.04879/) (2025)
- [In-Ear-Voice: Towards Milli-Watt Audio Enhancement With Bone-Conduction Microphones for In-Ear Sensing Platforms](https://mlsanity.com/paper/2309.02393/) (2023)
- [Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions](https://mlsanity.com/paper/2501.13230/) (2025)
- [LMFCA-Net: A Lightweight Model for Multi-Channel Speech Enhancement with Efficient Narrow-Band and Cross-Band Attention](https://mlsanity.com/paper/2502.11462/) (2025)
- [CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR](https://mlsanity.com/paper/2502.20040/) (2025)
- [From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks](https://mlsanity.com/paper/2602.10666/) (2026)
- [TF-MLPNet: Tiny Real-Time Neural Speech Separation](https://mlsanity.com/paper/2508.03047/) (2025)
- [Lightweight DNN for Full-Band Speech Denoising on Mobile Devices: Exploiting Long and Short Temporal Patterns](https://mlsanity.com/paper/2509.05079/) (2025)
- [Speech Enhancement with Perceptually-motivated Optimization and Dual Transformations](https://mlsanity.com/paper/2209.11905/) (2022)
- [Efficient Monaural Speech Enhancement using Spectrum Attention Fusion](https://mlsanity.com/paper/2308.02263/) (2023)
- [aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio](https://mlsanity.com/paper/2409.03377/) (2024)
- [DFingerNet: Noise-Adaptive Speech Enhancement for Hearing Aids](https://mlsanity.com/paper/2501.10525/) (2025)
- [UL-UNAS: Ultra-Lightweight U-Nets for Real-Time Speech Enhancement via Network Architecture Search](https://mlsanity.com/paper/2503.00340/) (2025)
- [RT-SEMamba: Real-Time Speech Enhancement Mamba via Progressive Knowledge Distillation](https://mlsanity.com/paper/2608.12099/) (2026)
- [Beyond Model Size: Redesigning LiSenNet for embedded speech enhancement](https://mlsanity.com/paper/2609.29866/) (2026)

## Abstract (arXiv)

Over the past few years, speech enhancement methods based on deep learning have greatly surpassed traditional methods based on spectral subtraction and spectral estimation. Many of these new techniques operate directly in the the short-time Fourier transform (STFT) domain, resulting in a high computational complexity. In this work, we propose PercepNet, an efficient approach that relies on human perception of speech by focusing on the spectral envelope and on the periodicity of the speech. We demonstrate high-quality, real-time enhancement of fullband (48 kHz) speech with less than 5% of a CPU core.