# Efficient Low-Latency Speech Enhancement with Mobile Audio Streaming Networks

arXiv: https://arxiv.org/abs/2008.07244 · HTML: https://mlsanity.com/paper/2008.07244/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Aug 2020.

## Built on by (most cited first, 2 of 2)

- [Short-Term Memory Convolutions](https://mlsanity.com/paper/2302.04331/) (2023)
- [SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model](https://mlsanity.com/paper/2410.03813/) (2024)

## Abstract (arXiv)

We propose Mobile Audio Streaming Networks (MASnet) for efficient low-latency speech enhancement, which is particularly suitable for mobile devices and other applications where computational capacity is a limitation. MASnet processes linear-scale spectrograms, transforming successive noisy frames into complex-valued ratio masks which are then applied to the respective noisy frames. MASnet can operate in a low-latency incremental inference mode which matches the complexity of layer-by-layer batch mode. Compared to a similar fully-convolutional architecture, MASnet incorporates depthwise and pointwise convolutions for a large reduction in fused multiply-accumulate operations per second (FMA/s), at the cost of some reduction in SNR.