# Real-Time System for Audio-Visual Target Speech Enhancement

arXiv: https://arxiv.org/abs/2509.20741 · HTML: https://mlsanity.com/paper/2509.20741/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 24 references that are in the map.
- First posted on arXiv 25 Sep 2025.

## Builds on (most cited first, 16 of 16)

- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation](https://mlsanity.com/paper/1804.03619/) (2018)
- [End-to-end Audio-visual Speech Recognition with Conformers](https://mlsanity.com/paper/2102.06657/) (2021)
- [The Conversation: Deep Audio-Visual Speech Enhancement](https://mlsanity.com/paper/1804.04121/) (2018)
- [Visual Speech Recognition for Multiple Languages in the Wild](https://mlsanity.com/paper/2202.13084/) (2022)
- [Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks](https://mlsanity.com/paper/1709.00944/) (2017)
- [Audio-visual Speech Enhancement Using Conditional Variational Auto-Encoders](https://mlsanity.com/paper/1908.02590/) (2019)
- [Audio-Visual Speech Codecs: Rethinking Audio-Visual Speech Enhancement by Re-Synthesis](https://mlsanity.com/paper/2203.17263/) (2022)
- [FlowAVSE: Efficient Audio-Visual Speech Enhancement with Conditional Flow Matching](https://mlsanity.com/paper/2406.09286/) (2024)
- [Lip-Reading Driven Deep Learning Approach for Speech Enhancement](https://mlsanity.com/paper/1808.00046/) (2018)
- [Improved Lite Audio-Visual Speech Enhancement](https://mlsanity.com/paper/2008.13222/) (2020)
- [On The Compensation Between Magnitude and Phase in Speech Separation](https://mlsanity.com/paper/2108.05470/) (2021)
- [LA-VocE: Low-SNR Audio-visual Speech Enhancement using Neural Vocoders](https://mlsanity.com/paper/2211.10999/) (2022)
- [Real-Time Audio-Visual End-to-End Speech Enhancement](https://mlsanity.com/paper/2303.07005/) (2023)
- [RT-LA-VocE: Real-Time Low-SNR Audio-Visual Speech Enhancement](https://mlsanity.com/paper/2407.07825/) (2024)
- [Real-Time Audio-Visual Speech Enhancement Using Pre-trained Visual Representations](https://mlsanity.com/paper/2507.21448/) (2025)

## Abstract (arXiv)

We present a live demonstration for RAVEN, a real-time audio-visual speech enhancement system designed to run entirely on a CPU. In single-channel, audio-only settings, speech enhancement is traditionally approached as the task of extracting clean speech from environmental noise. More recent work has explored the use of visual cues, such as lip movements, to improve robustness, particularly in the presence of interfering speakers. However, to our knowledge, no prior work has demonstrated an interactive system for real-time audio-visual speech enhancement operating on CPU hardware. RAVEN fills this gap by using pretrained visual embeddings from an audio-visual speech recognition model to encode lip movement information. The system generalizes across environmental noise, interfering speakers, transient sounds, and even singing voices. In this demonstration, attendees will be able to experience live audio-visual target speech enhancement using a microphone and webcam setup, with clean speech playback through headphones.