AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

Model reports

Brain-to-Text Benchmark '24

Evaluates 1,200 held-out sentences from one participant (T12). Language model post-processing is part of each system, and results do not establish transfer to another participant or to the different Brain-to-Text '25 dataset.

Evidence available for this benchmark

This source record contains 4 numeric observations. The source distinguishes 4 model identities or configurations. A model may appear more than once; check the version, tools and run budget before comparing. Read results and row-level evidence →

Reported metric
word_error_rate
Recorded unit
percent
Metric direction
lower is better

Start with these resources

Cited documents and dates (1)

Evaluation context and evidence

Source
Model reports
Publisher
Not recorded
Benchmark release
2023-06-01
Collected
Not recorded
Modality
Not recorded

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Reported results 4

Shown in source observation order, not ranked. Dates retain the precision provided by the source.

ModelValueUnitProtocolReported date and basisSource
DCoND-LIFT5.81percent1,200 competitionHoldOut sentences; aggregate word error rate2024-06-01 · document_publicationBrain-to-Text Benchmark '24 leaderboard
PyTorch baseline9.76percent1,200 competitionHoldOut sentences; aggregate word error rate2024-06-01 · document_publicationBrain-to-Text Benchmark '24 leaderboard
TeamCyber submission8.26percent1,200 competitionHoldOut sentences; aggregate word error rate2024-06-01 · document_publicationBrain-to-Text Benchmark '24 leaderboard
Tyler Benster et al. submission8.93percent1,200 competitionHoldOut sentences; aggregate word error rate2024-06-01 · document_publicationBrain-to-Text Benchmark '24 leaderboard