Browse State-of-the-Art › Lipreading
Lipreading
36 papers with code · 8 benchmarks · 8 datasets archive 2025-07-28
Lipreading is a process of extracting speech by watching lip movements of a speaker in the absence of sound. Humans lipread all the time without even noticing. It is a big part in communication albeit not as dominant as audio. It is a very helpful skill to learn especially for those who are hard of hearing.
Deep Lipreading is the process of extracting speech from a video of a silent talking face using deep neural networks. It is also known by few other names: Visual Speech Recognition (VSR), Machine Lipreading, Automatic Lipreading etc.
The primary methodology involves two stages: i) Extracting visual and temporal features from a sequence of image frames from a silent talking video ii) Processing the sequence of features into units of speech e.g. characters, words, phrases etc. We can find several implementations of this methodology either done in two separate stages or trained end-to-end in one go.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
8 leaderboard tables shown for this task, 8 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.
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
8 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 36 papers with code (103 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.
-
5 Nov 2016 13 repositories listed Syntology ran 0 of 15 samples · 15 unverifiedLipreading is the task of decoding text from the movement of a speaker's mouth.
-
6 Sep 2018 4 repositories listedThe goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio.
-
12 Mar 2017 4 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)We propose an end-to-end deep learning architecture for word-level visual speech recognition.
-
12 Feb 2021 3 repositories listedIn this work, we present a hybrid CTC/Attention model based on a ResNet-18 and Convolution-augmented transformer (Conformer), that can be trained in an end-to-end manner.
-
25 Mar 2023 2 repositories listed Syntology ran 0 of 6 samples · 6 unverifiedRecently, the performance of automatic, visual, and audio-visual speech recognition (ASR, VSR, and AV-ASR, respectively) has been substantially improved, mainly due to the use of larger models and training sets.
-
26 Feb 2022 2 repositories listedHowever, these advances are usually due to the larger training sets rather than the model design.
-
5 Jan 2022 2 repositories listedThe lip-reading WER is further reduced to 26.
-
12 May 2020 2 repositories listedVision is often used as a complementary modality for audio speech recognition (ASR), especially in the noisy environment where performance of solo audio modality significantly deteriorates.
-
23 Jan 2020 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)We present results on the largest publicly-available datasets for isolated word recognition in English and Mandarin, LRW and LRW1000, respectively.
-
16 Oct 2018 2 repositories listedIt has shown a large variation in this benchmark in several aspects, including the number of samples in each class, video resolution, lighting conditions, and speakers' attributes such as pose, age, gender, and make-up.
-
18 Feb 2018 2 repositories listedIn presence of high levels of noise, the end-to-end audiovisual model significantly outperforms both audio-only models.
-
9 Feb 2025 1 repository listedWe also introduce a multi-teacher ensemble method to distill the student, which receives audio-visual data as inputs.
-
1 Feb 2025 1 repository listedIn addition, a thorough ablation study is carried out, where it is studied how the different components that form the architecture influence the quality of speech recognition.
-
4 Nov 2024 1 repository listed Syntology ran 0 of 9 samples · 9 unverified · 9 pointer-only (licence)We demonstrate that training a single model for all three tasks enhances VSR and AVSR performance, overcoming typical optimisation challenges when training from scratch.
-
18 Jun 2024 1 repository listedVisual Speech Recognition (VSR) stands at the intersection of computer vision and speech recognition, aiming to interpret spoken content from visual cues.
-
11 May 2024 1 repository listedIn this paper, we propose Watch Your Mouth, a novel method that leverages depth sensing to enable accurate silent speech recognition.
-
9 May 2024 1 repository listedThe article introduces a novel audio-visual speech command recognition transformer (AVCRFormer) specifically designed for robust AVSR.
-
23 Feb 2024 1 repository listed Syntology ran 8 of 12 samples · 4 unverified · 12 pointer-only (licence)In this paper, we propose a novel framework, namely Visual Speech Processing incorporated with LLMs (VSP-LLM), to maximize the context modeling ability by bringing the overwhelming power of LLMs.
-
12 Feb 2023 1 repository listedSilent speech interface is a promising technology that enables private communications in natural language.
-
12 Dec 2022 1 repository listedWe observe strong results in low- and high-resource labelled data settings when fine-tuning the visual and auditory encoders resulting from a single pre-training stage, in which the encoders are jointly trained.
-
20 Sep 2022 1 repository listedThe powerful modeling capabilities of all-attention-based transformer architectures often cause overfitting and - for natural language processing tasks - lead to an implicitly learned internal language model in the…
-
3 Sep 2022 1 repository listedIn this paper, we systematically investigate the performance of state-of-the-art data augmentation approaches, temporal models and other training strategies, like self-distillation and using word boundary indicators.
-
28 Aug 2022 1 repository listedState-of-the-art neural network language models (NNLMs) represented by long short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming highly complex.
-
4 Apr 2022 1 repository listedWith the multi-head key memories, MVM extracts possible candidate audio features from the memory, which allows the lip reading model to consider the possibility of which pronunciations can be represented from the input…
-
24 Feb 2022 1 repository listed Syntology ran 0 of 6 samples · 6 unverifiedIn particular, audio and visual front-ends are trained on large-scale unimodal datasets, then we integrate components of both front-ends into a larger multimodal framework which learns to recognize parallel audio-visual…
-
5 Jan 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Audio-based automatic speech recognition (ASR) degrades significantly in noisy environments and is particularly vulnerable to interfering speech, as the model cannot determine which speaker to transcribe.
-
14 Dec 2020 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedExtensive experiments show that this simple approach significantly surpasses the state-of-the-art in terms of generalisation to unseen manipulations and robustness to perturbations, as well as shed light on the factors…
-
15 Nov 2020 1 repository listedConsidering the non-negligible effects of these strategies and the existing tough status to train an effective lip reading model, we perform a comprehensive quantitative study and comparative analysis, for the first…
-
13 Jul 2020 1 repository listedHowever, our most promising lightweight models are on par with the current state-of-the-art while showing a reduction of 8.
-
21 May 2020 1 repository listedThe experiments show that our proposed model outperforms various state-of-the-art models and incorporating the memory augmented lateral transformers makes a 3.
Syntology lines on 9 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.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections