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GRID corpus (mixed-speech) Benchmark (Lipreading)
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.
The archive carries no text for this table; the description above is the archive's text for the task Lipreading. archive 2025-07-28
Over time archive 2025-07-28
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Direction inferred from the metric name, not from the archive: Word Error Rate (WER) (lower is better). Points are placed at the row's paper date; 5 of 5 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | |||||
|---|---|---|---|---|---|---|---|---|
| 1 | CTC/Attention | 1.2 | ✓ | Paper | Code | 2022 | linked, not harvested | report |
| 2 | LCANet | 2.9 | – | Paper | – | 2018 | no code linked | report |
| 3 | LipNet (with Face Cutout) | 2.9 | – | Paper | Code | 2020 | linked, not harvested | report |
| 4 | WAS | 3 | ✓ | Paper | – | 2016 | no code linked | report |
| 5 | LipNet | 4.6 | – | Paper | Code | 2016 | 0 of 15 ran · 15 unverified | report |
All 5 rows shown. 5 link to a paper page on this site; 2 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 1 rows have a graph line, from 1 distinct papers; 0 rows (0 papers) have at least one sample that ran. Counting each paper once: Syntology ran 0 of 15 samples; 15 unverified. Separately, 0 of those 15 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
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